iVOD / 17023

Field Value
IVOD_ID 17023
IVOD_URL https://ivod.ly.gov.tw/Play/Full/1M/17023
日期 2025-11-12
會議資料.會議代碼 委員會-11-4-26-9
會議資料.會議代碼:str 第11屆第4會期社會福利及衛生環境委員會第9次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 9
會議資料.種類 委員會
會議資料.委員會代碼[0] 26
會議資料.委員會代碼:str[0] 社會福利及衛生環境委員會
會議資料.標題 第11屆第4會期社會福利及衛生環境委員會第9次全體委員會議
影片種類 Full
開始時間 2025-11-12T08:32:30+08:00
結束時間 2025-11-12T14:07:00+08:00
影片長度 05:34:30
支援功能[0] ai-transcript
video_url https://h264media01.ly.gov.tw:443/vod_1/_definst_/mp4:1M/bfaf9b39ac01a685456f1a8eac090e91df7d11ac893db3ce914d0d15f34b2c02546e3a43ff75ae965ea18f28b6918d91.mp4/playlist.m3u8
會議時間 2025-11-12T09:00:00+08:00
會議名稱 立法院第11屆第4會期社會福利及衛生環境委員會第9次全體委員會議(事由:邀請勞動部部長列席報告業務概況,並備質詢。)
委員名稱 完整會議
委員發言時間 08:32:30 - 14:07:00
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 1639.31909375
transcript.pyannote[0].end 1644.28034375
transcript.pyannote[1].speaker SPEAKER_06
transcript.pyannote[1].start 1645.15784375
transcript.pyannote[1].end 1645.24221875
transcript.pyannote[2].speaker SPEAKER_06
transcript.pyannote[2].start 1646.00159375
transcript.pyannote[2].end 1648.97159375
transcript.pyannote[3].speaker SPEAKER_18
transcript.pyannote[3].start 1648.97159375
transcript.pyannote[3].end 1649.73096875
transcript.pyannote[4].speaker SPEAKER_06
transcript.pyannote[4].start 1649.73096875
transcript.pyannote[4].end 1649.74784375
transcript.pyannote[5].speaker SPEAKER_18
transcript.pyannote[5].start 1650.10221875
transcript.pyannote[5].end 1677.10221875
transcript.pyannote[6].speaker SPEAKER_18
transcript.pyannote[6].start 1677.15284375
transcript.pyannote[6].end 1692.34034375
transcript.pyannote[7].speaker SPEAKER_18
transcript.pyannote[7].start 1692.72846875
transcript.pyannote[7].end 1736.97471875
transcript.pyannote[8].speaker SPEAKER_18
transcript.pyannote[8].start 1737.17721875
transcript.pyannote[8].end 1764.97034375
transcript.pyannote[9].speaker SPEAKER_18
transcript.pyannote[9].start 1765.61159375
transcript.pyannote[9].end 1782.41909375
transcript.pyannote[10].speaker SPEAKER_03
transcript.pyannote[10].start 1785.47346875
transcript.pyannote[10].end 1788.69659375
transcript.pyannote[11].speaker SPEAKER_03
transcript.pyannote[11].start 1789.89471875
transcript.pyannote[11].end 1801.03221875
transcript.pyannote[12].speaker SPEAKER_03
transcript.pyannote[12].start 1801.25159375
transcript.pyannote[12].end 1803.02346875
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 1805.85846875
transcript.pyannote[13].end 1807.05659375
transcript.pyannote[14].speaker SPEAKER_03
transcript.pyannote[14].start 1809.30096875
transcript.pyannote[14].end 1811.37659375
transcript.pyannote[15].speaker SPEAKER_03
transcript.pyannote[15].start 1812.43971875
transcript.pyannote[15].end 1812.50721875
transcript.pyannote[16].speaker SPEAKER_03
transcript.pyannote[16].start 1812.55784375
transcript.pyannote[16].end 1815.86534375
transcript.pyannote[17].speaker SPEAKER_03
transcript.pyannote[17].start 1817.82284375
transcript.pyannote[17].end 1817.87346875
transcript.pyannote[18].speaker SPEAKER_29
transcript.pyannote[18].start 1817.87346875
transcript.pyannote[18].end 1817.89034375
transcript.pyannote[19].speaker SPEAKER_03
transcript.pyannote[19].start 1817.89034375
transcript.pyannote[19].end 1817.97471875
transcript.pyannote[20].speaker SPEAKER_29
transcript.pyannote[20].start 1817.97471875
transcript.pyannote[20].end 1817.99159375
transcript.pyannote[21].speaker SPEAKER_03
transcript.pyannote[21].start 1817.99159375
transcript.pyannote[21].end 1818.07596875
transcript.pyannote[22].speaker SPEAKER_03
transcript.pyannote[22].start 1818.36284375
transcript.pyannote[22].end 1820.45534375
transcript.pyannote[23].speaker SPEAKER_03
transcript.pyannote[23].start 1821.82221875
transcript.pyannote[23].end 1824.42096875
transcript.pyannote[24].speaker SPEAKER_03
transcript.pyannote[24].start 1825.36596875
transcript.pyannote[24].end 1828.26846875
transcript.pyannote[25].speaker SPEAKER_03
transcript.pyannote[25].start 1829.55096875
transcript.pyannote[25].end 1831.64346875
transcript.pyannote[26].speaker SPEAKER_03
transcript.pyannote[26].start 1832.89221875
transcript.pyannote[26].end 1836.58784375
transcript.pyannote[27].speaker SPEAKER_03
transcript.pyannote[27].start 1837.88721875
transcript.pyannote[27].end 1839.76034375
transcript.pyannote[28].speaker SPEAKER_03
transcript.pyannote[28].start 1841.22846875
transcript.pyannote[28].end 1843.65846875
transcript.pyannote[29].speaker SPEAKER_03
transcript.pyannote[29].start 1844.62034375
transcript.pyannote[29].end 1846.99971875
transcript.pyannote[30].speaker SPEAKER_03
transcript.pyannote[30].start 1848.24846875
transcript.pyannote[30].end 1850.59409375
transcript.pyannote[31].speaker SPEAKER_03
transcript.pyannote[31].start 1852.45034375
transcript.pyannote[31].end 1855.36971875
transcript.pyannote[32].speaker SPEAKER_03
transcript.pyannote[32].start 1855.89284375
transcript.pyannote[32].end 1856.60159375
transcript.pyannote[33].speaker SPEAKER_26
transcript.pyannote[33].start 1856.02784375
transcript.pyannote[33].end 1856.31471875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 1856.31471875
transcript.pyannote[34].end 1856.33159375
transcript.pyannote[35].speaker SPEAKER_03
transcript.pyannote[35].start 1857.73221875
transcript.pyannote[35].end 1859.08221875
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 1859.25096875
transcript.pyannote[36].end 1861.88346875
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 1863.06471875
transcript.pyannote[37].end 1865.61284375
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 1866.87846875
transcript.pyannote[38].end 1868.85284375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 1870.18596875
transcript.pyannote[39].end 1872.02534375
transcript.pyannote[40].speaker SPEAKER_03
transcript.pyannote[40].start 1873.40909375
transcript.pyannote[40].end 1875.06284375
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 1876.54784375
transcript.pyannote[41].end 1878.57284375
transcript.pyannote[42].speaker SPEAKER_03
transcript.pyannote[42].start 1880.64846875
transcript.pyannote[42].end 1883.11221875
transcript.pyannote[43].speaker SPEAKER_03
transcript.pyannote[43].start 1884.49596875
transcript.pyannote[43].end 1888.91721875
transcript.pyannote[44].speaker SPEAKER_03
transcript.pyannote[44].start 1892.39346875
transcript.pyannote[44].end 1895.39721875
transcript.pyannote[45].speaker SPEAKER_24
transcript.pyannote[45].start 1906.63596875
transcript.pyannote[45].end 1910.85471875
transcript.pyannote[46].speaker SPEAKER_24
transcript.pyannote[46].start 1911.39471875
transcript.pyannote[46].end 1918.29659375
transcript.pyannote[47].speaker SPEAKER_24
transcript.pyannote[47].start 1918.71846875
transcript.pyannote[47].end 1929.60284375
transcript.pyannote[48].speaker SPEAKER_24
transcript.pyannote[48].start 1929.75471875
transcript.pyannote[48].end 1956.97409375
transcript.pyannote[49].speaker SPEAKER_24
transcript.pyannote[49].start 1957.46346875
transcript.pyannote[49].end 2070.89721875
transcript.pyannote[50].speaker SPEAKER_24
transcript.pyannote[50].start 2071.16721875
transcript.pyannote[50].end 2104.46159375
transcript.pyannote[51].speaker SPEAKER_24
transcript.pyannote[51].start 2105.62596875
transcript.pyannote[51].end 2119.07534375
transcript.pyannote[52].speaker SPEAKER_24
transcript.pyannote[52].start 2119.31159375
transcript.pyannote[52].end 2146.05846875
transcript.pyannote[53].speaker SPEAKER_24
transcript.pyannote[53].start 2146.42971875
transcript.pyannote[53].end 2157.02721875
transcript.pyannote[54].speaker SPEAKER_24
transcript.pyannote[54].start 2157.56721875
transcript.pyannote[54].end 2164.31721875
transcript.pyannote[55].speaker SPEAKER_24
transcript.pyannote[55].start 2164.80659375
transcript.pyannote[55].end 2172.50159375
transcript.pyannote[56].speaker SPEAKER_24
transcript.pyannote[56].start 2172.94034375
transcript.pyannote[56].end 2269.36409375
transcript.pyannote[57].speaker SPEAKER_24
transcript.pyannote[57].start 2269.65096875
transcript.pyannote[57].end 2280.88971875
transcript.pyannote[58].speaker SPEAKER_24
transcript.pyannote[58].start 2281.66596875
transcript.pyannote[58].end 2334.01221875
transcript.pyannote[59].speaker SPEAKER_24
transcript.pyannote[59].start 2334.51846875
transcript.pyannote[59].end 2346.78659375
transcript.pyannote[60].speaker SPEAKER_24
transcript.pyannote[60].start 2349.30096875
transcript.pyannote[60].end 2402.22096875
transcript.pyannote[61].speaker SPEAKER_24
transcript.pyannote[61].start 2402.47409375
transcript.pyannote[61].end 2415.77159375
transcript.pyannote[62].speaker SPEAKER_24
transcript.pyannote[62].start 2416.29471875
transcript.pyannote[62].end 2417.59409375
transcript.pyannote[63].speaker SPEAKER_24
transcript.pyannote[63].start 2418.03284375
transcript.pyannote[63].end 2425.22159375
transcript.pyannote[64].speaker SPEAKER_24
transcript.pyannote[64].start 2425.81221875
transcript.pyannote[64].end 2443.66596875
transcript.pyannote[65].speaker SPEAKER_24
transcript.pyannote[65].start 2443.90221875
transcript.pyannote[65].end 2445.42096875
transcript.pyannote[66].speaker SPEAKER_24
transcript.pyannote[66].start 2445.67409375
transcript.pyannote[66].end 2449.82534375
transcript.pyannote[67].speaker SPEAKER_24
transcript.pyannote[67].start 2450.44971875
transcript.pyannote[67].end 2484.68909375
transcript.pyannote[68].speaker SPEAKER_24
transcript.pyannote[68].start 2485.16159375
transcript.pyannote[68].end 2486.41034375
transcript.pyannote[69].speaker SPEAKER_24
transcript.pyannote[69].start 2486.79846875
transcript.pyannote[69].end 2550.83909375
transcript.pyannote[70].speaker SPEAKER_03
transcript.pyannote[70].start 2553.84284375
transcript.pyannote[70].end 2555.66534375
transcript.pyannote[71].speaker SPEAKER_03
transcript.pyannote[71].start 2556.72846875
transcript.pyannote[71].end 2556.88034375
transcript.pyannote[72].speaker SPEAKER_03
transcript.pyannote[72].start 2558.16284375
transcript.pyannote[72].end 2562.55034375
transcript.pyannote[73].speaker SPEAKER_03
transcript.pyannote[73].start 2562.68534375
transcript.pyannote[73].end 2587.10346875
transcript.pyannote[74].speaker SPEAKER_16
transcript.pyannote[74].start 2592.35159375
transcript.pyannote[74].end 2594.96721875
transcript.pyannote[75].speaker SPEAKER_16
transcript.pyannote[75].start 2595.16971875
transcript.pyannote[75].end 2601.26159375
transcript.pyannote[76].speaker SPEAKER_16
transcript.pyannote[76].start 2601.53159375
transcript.pyannote[76].end 2603.37096875
transcript.pyannote[77].speaker SPEAKER_16
transcript.pyannote[77].start 2603.64096875
transcript.pyannote[77].end 2605.09221875
transcript.pyannote[78].speaker SPEAKER_16
transcript.pyannote[78].start 2605.37909375
transcript.pyannote[78].end 2607.15096875
transcript.pyannote[79].speaker SPEAKER_03
transcript.pyannote[79].start 2607.58971875
transcript.pyannote[79].end 2608.72034375
transcript.pyannote[80].speaker SPEAKER_24
transcript.pyannote[80].start 2614.03596875
transcript.pyannote[80].end 2614.69409375
transcript.pyannote[81].speaker SPEAKER_16
transcript.pyannote[81].start 2614.74471875
transcript.pyannote[81].end 2665.82534375
transcript.pyannote[82].speaker SPEAKER_22
transcript.pyannote[82].start 2633.05409375
transcript.pyannote[82].end 2633.47596875
transcript.pyannote[83].speaker SPEAKER_22
transcript.pyannote[83].start 2635.82159375
transcript.pyannote[83].end 2636.73284375
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 2652.12284375
transcript.pyannote[84].end 2652.25784375
transcript.pyannote[85].speaker SPEAKER_29
transcript.pyannote[85].start 2652.25784375
transcript.pyannote[85].end 2652.29159375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 2652.29159375
transcript.pyannote[86].end 2652.42659375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 2662.50096875
transcript.pyannote[87].end 2662.95659375
transcript.pyannote[88].speaker SPEAKER_24
transcript.pyannote[88].start 2665.04909375
transcript.pyannote[88].end 2665.43721875
transcript.pyannote[89].speaker SPEAKER_16
transcript.pyannote[89].start 2666.17971875
transcript.pyannote[89].end 2667.61409375
transcript.pyannote[90].speaker SPEAKER_16
transcript.pyannote[90].start 2667.88409375
transcript.pyannote[90].end 2670.33096875
transcript.pyannote[91].speaker SPEAKER_24
transcript.pyannote[91].start 2668.77846875
transcript.pyannote[91].end 2669.16659375
transcript.pyannote[92].speaker SPEAKER_16
transcript.pyannote[92].start 2670.39846875
transcript.pyannote[92].end 2672.74409375
transcript.pyannote[93].speaker SPEAKER_24
transcript.pyannote[93].start 2671.81596875
transcript.pyannote[93].end 2678.85284375
transcript.pyannote[94].speaker SPEAKER_16
transcript.pyannote[94].start 2675.32596875
transcript.pyannote[94].end 2675.59596875
transcript.pyannote[95].speaker SPEAKER_16
transcript.pyannote[95].start 2675.95034375
transcript.pyannote[95].end 2676.27096875
transcript.pyannote[96].speaker SPEAKER_16
transcript.pyannote[96].start 2677.04721875
transcript.pyannote[96].end 2730.52409375
transcript.pyannote[97].speaker SPEAKER_24
transcript.pyannote[97].start 2681.56971875
transcript.pyannote[97].end 2681.80596875
transcript.pyannote[98].speaker SPEAKER_29
transcript.pyannote[98].start 2690.05784375
transcript.pyannote[98].end 2690.07471875
transcript.pyannote[99].speaker SPEAKER_13
transcript.pyannote[99].start 2690.07471875
transcript.pyannote[99].end 2690.15909375
transcript.pyannote[100].speaker SPEAKER_29
transcript.pyannote[100].start 2690.15909375
transcript.pyannote[100].end 2690.19284375
transcript.pyannote[101].speaker SPEAKER_13
transcript.pyannote[101].start 2690.19284375
transcript.pyannote[101].end 2690.22659375
transcript.pyannote[102].speaker SPEAKER_29
transcript.pyannote[102].start 2690.22659375
transcript.pyannote[102].end 2690.26034375
transcript.pyannote[103].speaker SPEAKER_24
transcript.pyannote[103].start 2731.50284375
transcript.pyannote[103].end 2753.57534375
transcript.pyannote[104].speaker SPEAKER_16
transcript.pyannote[104].start 2739.45096875
transcript.pyannote[104].end 2739.68721875
transcript.pyannote[105].speaker SPEAKER_29
transcript.pyannote[105].start 2739.68721875
transcript.pyannote[105].end 2739.80534375
transcript.pyannote[106].speaker SPEAKER_16
transcript.pyannote[106].start 2741.00346875
transcript.pyannote[106].end 2741.96534375
transcript.pyannote[107].speaker SPEAKER_29
transcript.pyannote[107].start 2741.96534375
transcript.pyannote[107].end 2742.96096875
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 2742.96096875
transcript.pyannote[108].end 2742.99471875
transcript.pyannote[109].speaker SPEAKER_29
transcript.pyannote[109].start 2746.62284375
transcript.pyannote[109].end 2746.63971875
transcript.pyannote[110].speaker SPEAKER_16
transcript.pyannote[110].start 2746.63971875
transcript.pyannote[110].end 2747.06159375
transcript.pyannote[111].speaker SPEAKER_16
transcript.pyannote[111].start 2753.54159375
transcript.pyannote[111].end 2758.11471875
transcript.pyannote[112].speaker SPEAKER_24
transcript.pyannote[112].start 2755.60034375
transcript.pyannote[112].end 2756.07284375
transcript.pyannote[113].speaker SPEAKER_24
transcript.pyannote[113].start 2756.44409375
transcript.pyannote[113].end 2757.06846875
transcript.pyannote[114].speaker SPEAKER_24
transcript.pyannote[114].start 2757.67596875
transcript.pyannote[114].end 2758.92471875
transcript.pyannote[115].speaker SPEAKER_16
transcript.pyannote[115].start 2759.65034375
transcript.pyannote[115].end 2779.02284375
transcript.pyannote[116].speaker SPEAKER_24
transcript.pyannote[116].start 2765.03346875
transcript.pyannote[116].end 2766.50159375
transcript.pyannote[117].speaker SPEAKER_29
transcript.pyannote[117].start 2773.92659375
transcript.pyannote[117].end 2773.94346875
transcript.pyannote[118].speaker SPEAKER_24
transcript.pyannote[118].start 2773.94346875
transcript.pyannote[118].end 2774.19659375
transcript.pyannote[119].speaker SPEAKER_24
transcript.pyannote[119].start 2778.22971875
transcript.pyannote[119].end 2778.92159375
transcript.pyannote[120].speaker SPEAKER_24
transcript.pyannote[120].start 2779.02284375
transcript.pyannote[120].end 2784.79409375
transcript.pyannote[121].speaker SPEAKER_16
transcript.pyannote[121].start 2780.11971875
transcript.pyannote[121].end 2781.40221875
transcript.pyannote[122].speaker SPEAKER_24
transcript.pyannote[122].start 2785.01346875
transcript.pyannote[122].end 2793.01221875
transcript.pyannote[123].speaker SPEAKER_16
transcript.pyannote[123].start 2793.68721875
transcript.pyannote[123].end 2795.59409375
transcript.pyannote[124].speaker SPEAKER_24
transcript.pyannote[124].start 2793.78846875
transcript.pyannote[124].end 2794.73346875
transcript.pyannote[125].speaker SPEAKER_24
transcript.pyannote[125].start 2795.05409375
transcript.pyannote[125].end 2807.38971875
transcript.pyannote[126].speaker SPEAKER_16
transcript.pyannote[126].start 2796.57284375
transcript.pyannote[126].end 2797.12971875
transcript.pyannote[127].speaker SPEAKER_16
transcript.pyannote[127].start 2801.28096875
transcript.pyannote[127].end 2801.71971875
transcript.pyannote[128].speaker SPEAKER_16
transcript.pyannote[128].start 2802.20909375
transcript.pyannote[128].end 2803.12034375
transcript.pyannote[129].speaker SPEAKER_16
transcript.pyannote[129].start 2807.35596875
transcript.pyannote[129].end 2807.37284375
transcript.pyannote[130].speaker SPEAKER_16
transcript.pyannote[130].start 2807.38971875
transcript.pyannote[130].end 2833.30971875
transcript.pyannote[131].speaker SPEAKER_16
transcript.pyannote[131].start 2833.84971875
transcript.pyannote[131].end 2839.57034375
transcript.pyannote[132].speaker SPEAKER_24
transcript.pyannote[132].start 2839.57034375
transcript.pyannote[132].end 2840.61659375
transcript.pyannote[133].speaker SPEAKER_16
transcript.pyannote[133].start 2841.27471875
transcript.pyannote[133].end 2843.63721875
transcript.pyannote[134].speaker SPEAKER_24
transcript.pyannote[134].start 2843.63721875
transcript.pyannote[134].end 2844.71721875
transcript.pyannote[135].speaker SPEAKER_16
transcript.pyannote[135].start 2844.10971875
transcript.pyannote[135].end 2870.68784375
transcript.pyannote[136].speaker SPEAKER_24
transcript.pyannote[136].start 2870.19846875
transcript.pyannote[136].end 2872.02096875
transcript.pyannote[137].speaker SPEAKER_24
transcript.pyannote[137].start 2872.24034375
transcript.pyannote[137].end 2885.94284375
transcript.pyannote[138].speaker SPEAKER_22
transcript.pyannote[138].start 2882.17971875
transcript.pyannote[138].end 2883.07409375
transcript.pyannote[139].speaker SPEAKER_22
transcript.pyannote[139].start 2885.94284375
transcript.pyannote[139].end 2886.29721875
transcript.pyannote[140].speaker SPEAKER_29
transcript.pyannote[140].start 2886.29721875
transcript.pyannote[140].end 2886.31409375
transcript.pyannote[141].speaker SPEAKER_24
transcript.pyannote[141].start 2886.93846875
transcript.pyannote[141].end 2894.80221875
transcript.pyannote[142].speaker SPEAKER_16
transcript.pyannote[142].start 2894.80221875
transcript.pyannote[142].end 2896.30409375
transcript.pyannote[143].speaker SPEAKER_24
transcript.pyannote[143].start 2894.83596875
transcript.pyannote[143].end 2894.90346875
transcript.pyannote[144].speaker SPEAKER_24
transcript.pyannote[144].start 2894.97096875
transcript.pyannote[144].end 2897.24909375
transcript.pyannote[145].speaker SPEAKER_16
transcript.pyannote[145].start 2896.96221875
transcript.pyannote[145].end 2897.87346875
transcript.pyannote[146].speaker SPEAKER_24
transcript.pyannote[146].start 2897.77221875
transcript.pyannote[146].end 2900.33721875
transcript.pyannote[147].speaker SPEAKER_16
transcript.pyannote[147].start 2900.18534375
transcript.pyannote[147].end 2901.13034375
transcript.pyannote[148].speaker SPEAKER_24
transcript.pyannote[148].start 2900.84346875
transcript.pyannote[148].end 2902.63221875
transcript.pyannote[149].speaker SPEAKER_16
transcript.pyannote[149].start 2902.59846875
transcript.pyannote[149].end 2902.61534375
transcript.pyannote[150].speaker SPEAKER_16
transcript.pyannote[150].start 2902.63221875
transcript.pyannote[150].end 2903.76284375
transcript.pyannote[151].speaker SPEAKER_24
transcript.pyannote[151].start 2903.32409375
transcript.pyannote[151].end 2921.61659375
transcript.pyannote[152].speaker SPEAKER_16
transcript.pyannote[152].start 2907.76221875
transcript.pyannote[152].end 2909.17971875
transcript.pyannote[153].speaker SPEAKER_16
transcript.pyannote[153].start 2910.09096875
transcript.pyannote[153].end 2910.44534375
transcript.pyannote[154].speaker SPEAKER_16
transcript.pyannote[154].start 2919.55784375
transcript.pyannote[154].end 2920.43534375
transcript.pyannote[155].speaker SPEAKER_16
transcript.pyannote[155].start 2921.04284375
transcript.pyannote[155].end 2931.18471875
transcript.pyannote[156].speaker SPEAKER_24
transcript.pyannote[156].start 2931.18471875
transcript.pyannote[156].end 2940.61784375
transcript.pyannote[157].speaker SPEAKER_16
transcript.pyannote[157].start 2938.33971875
transcript.pyannote[157].end 2939.97659375
transcript.pyannote[158].speaker SPEAKER_29
transcript.pyannote[158].start 2939.97659375
transcript.pyannote[158].end 2940.04409375
transcript.pyannote[159].speaker SPEAKER_24
transcript.pyannote[159].start 2940.98909375
transcript.pyannote[159].end 2948.88659375
transcript.pyannote[160].speaker SPEAKER_16
transcript.pyannote[160].start 2943.55409375
transcript.pyannote[160].end 2943.99284375
transcript.pyannote[161].speaker SPEAKER_16
transcript.pyannote[161].start 2944.83659375
transcript.pyannote[161].end 2945.74784375
transcript.pyannote[162].speaker SPEAKER_16
transcript.pyannote[162].start 2948.41409375
transcript.pyannote[162].end 2971.81971875
transcript.pyannote[163].speaker SPEAKER_24
transcript.pyannote[163].start 2949.30846875
transcript.pyannote[163].end 2949.76409375
transcript.pyannote[164].speaker SPEAKER_24
transcript.pyannote[164].start 2972.89971875
transcript.pyannote[164].end 2973.55784375
transcript.pyannote[165].speaker SPEAKER_24
transcript.pyannote[165].start 2973.87846875
transcript.pyannote[165].end 2987.88471875
transcript.pyannote[166].speaker SPEAKER_16
transcript.pyannote[166].start 2986.07909375
transcript.pyannote[166].end 2988.93096875
transcript.pyannote[167].speaker SPEAKER_24
transcript.pyannote[167].start 2988.52596875
transcript.pyannote[167].end 2991.68159375
transcript.pyannote[168].speaker SPEAKER_16
transcript.pyannote[168].start 2990.60159375
transcript.pyannote[168].end 2992.59284375
transcript.pyannote[169].speaker SPEAKER_24
transcript.pyannote[169].start 2992.13721875
transcript.pyannote[169].end 3005.40096875
transcript.pyannote[170].speaker SPEAKER_16
transcript.pyannote[170].start 2996.11971875
transcript.pyannote[170].end 2997.31784375
transcript.pyannote[171].speaker SPEAKER_16
transcript.pyannote[171].start 3003.66284375
transcript.pyannote[171].end 3006.51471875
transcript.pyannote[172].speaker SPEAKER_24
transcript.pyannote[172].start 3005.65409375
transcript.pyannote[172].end 3016.70721875
transcript.pyannote[173].speaker SPEAKER_16
transcript.pyannote[173].start 3007.20659375
transcript.pyannote[173].end 3007.72971875
transcript.pyannote[174].speaker SPEAKER_16
transcript.pyannote[174].start 3013.02846875
transcript.pyannote[174].end 3028.50284375
transcript.pyannote[175].speaker SPEAKER_24
transcript.pyannote[175].start 3028.90784375
transcript.pyannote[175].end 3036.75471875
transcript.pyannote[176].speaker SPEAKER_16
transcript.pyannote[176].start 3034.96596875
transcript.pyannote[176].end 3035.89409375
transcript.pyannote[177].speaker SPEAKER_22
transcript.pyannote[177].start 3035.89409375
transcript.pyannote[177].end 3035.92784375
transcript.pyannote[178].speaker SPEAKER_16
transcript.pyannote[178].start 3035.92784375
transcript.pyannote[178].end 3035.97846875
transcript.pyannote[179].speaker SPEAKER_24
transcript.pyannote[179].start 3036.88971875
transcript.pyannote[179].end 3039.87659375
transcript.pyannote[180].speaker SPEAKER_16
transcript.pyannote[180].start 3036.97409375
transcript.pyannote[180].end 3036.99096875
transcript.pyannote[181].speaker SPEAKER_22
transcript.pyannote[181].start 3036.99096875
transcript.pyannote[181].end 3037.39596875
transcript.pyannote[182].speaker SPEAKER_24
transcript.pyannote[182].start 3040.46721875
transcript.pyannote[182].end 3054.28784375
transcript.pyannote[183].speaker SPEAKER_16
transcript.pyannote[183].start 3052.98846875
transcript.pyannote[183].end 3053.56221875
transcript.pyannote[184].speaker SPEAKER_16
transcript.pyannote[184].start 3053.91659375
transcript.pyannote[184].end 3083.61659375
transcript.pyannote[185].speaker SPEAKER_24
transcript.pyannote[185].start 3083.61659375
transcript.pyannote[185].end 3088.03784375
transcript.pyannote[186].speaker SPEAKER_24
transcript.pyannote[186].start 3088.29096875
transcript.pyannote[186].end 3089.35409375
transcript.pyannote[187].speaker SPEAKER_24
transcript.pyannote[187].start 3090.09659375
transcript.pyannote[187].end 3098.50034375
transcript.pyannote[188].speaker SPEAKER_16
transcript.pyannote[188].start 3091.34534375
transcript.pyannote[188].end 3092.10471875
transcript.pyannote[189].speaker SPEAKER_16
transcript.pyannote[189].start 3095.19284375
transcript.pyannote[189].end 3095.46284375
transcript.pyannote[190].speaker SPEAKER_16
transcript.pyannote[190].start 3097.01534375
transcript.pyannote[190].end 3097.08284375
transcript.pyannote[191].speaker SPEAKER_16
transcript.pyannote[191].start 3097.26846875
transcript.pyannote[191].end 3100.20471875
transcript.pyannote[192].speaker SPEAKER_24
transcript.pyannote[192].start 3099.02346875
transcript.pyannote[192].end 3104.60909375
transcript.pyannote[193].speaker SPEAKER_16
transcript.pyannote[193].start 3103.71471875
transcript.pyannote[193].end 3104.52471875
transcript.pyannote[194].speaker SPEAKER_16
transcript.pyannote[194].start 3104.94659375
transcript.pyannote[194].end 3118.09221875
transcript.pyannote[195].speaker SPEAKER_24
transcript.pyannote[195].start 3118.85159375
transcript.pyannote[195].end 3119.35784375
transcript.pyannote[196].speaker SPEAKER_16
transcript.pyannote[196].start 3118.86846875
transcript.pyannote[196].end 3119.71221875
transcript.pyannote[197].speaker SPEAKER_24
transcript.pyannote[197].start 3119.71221875
transcript.pyannote[197].end 3128.72346875
transcript.pyannote[198].speaker SPEAKER_16
transcript.pyannote[198].start 3125.95596875
transcript.pyannote[198].end 3126.25971875
transcript.pyannote[199].speaker SPEAKER_16
transcript.pyannote[199].start 3127.79534375
transcript.pyannote[199].end 3129.38159375
transcript.pyannote[200].speaker SPEAKER_24
transcript.pyannote[200].start 3128.99346875
transcript.pyannote[200].end 3134.17409375
transcript.pyannote[201].speaker SPEAKER_16
transcript.pyannote[201].start 3133.88721875
transcript.pyannote[201].end 3143.11784375
transcript.pyannote[202].speaker SPEAKER_24
transcript.pyannote[202].start 3143.52284375
transcript.pyannote[202].end 3144.97409375
transcript.pyannote[203].speaker SPEAKER_16
transcript.pyannote[203].start 3144.46784375
transcript.pyannote[203].end 3144.60284375
transcript.pyannote[204].speaker SPEAKER_16
transcript.pyannote[204].start 3144.67034375
transcript.pyannote[204].end 3161.39346875
transcript.pyannote[205].speaker SPEAKER_24
transcript.pyannote[205].start 3160.73534375
transcript.pyannote[205].end 3161.88284375
transcript.pyannote[206].speaker SPEAKER_16
transcript.pyannote[206].start 3161.88284375
transcript.pyannote[206].end 3201.94409375
transcript.pyannote[207].speaker SPEAKER_24
transcript.pyannote[207].start 3197.48909375
transcript.pyannote[207].end 3197.87721875
transcript.pyannote[208].speaker SPEAKER_24
transcript.pyannote[208].start 3201.67409375
transcript.pyannote[208].end 3226.31159375
transcript.pyannote[209].speaker SPEAKER_16
transcript.pyannote[209].start 3211.59659375
transcript.pyannote[209].end 3211.64721875
transcript.pyannote[210].speaker SPEAKER_16
transcript.pyannote[210].start 3212.08596875
transcript.pyannote[210].end 3212.25471875
transcript.pyannote[211].speaker SPEAKER_16
transcript.pyannote[211].start 3213.50346875
transcript.pyannote[211].end 3213.89159375
transcript.pyannote[212].speaker SPEAKER_16
transcript.pyannote[212].start 3215.81534375
transcript.pyannote[212].end 3216.57471875
transcript.pyannote[213].speaker SPEAKER_00
transcript.pyannote[213].start 3216.57471875
transcript.pyannote[213].end 3216.59159375
transcript.pyannote[214].speaker SPEAKER_16
transcript.pyannote[214].start 3226.10909375
transcript.pyannote[214].end 3242.37659375
transcript.pyannote[215].speaker SPEAKER_24
transcript.pyannote[215].start 3238.61346875
transcript.pyannote[215].end 3239.15346875
transcript.pyannote[216].speaker SPEAKER_24
transcript.pyannote[216].start 3240.35159375
transcript.pyannote[216].end 3241.61721875
transcript.pyannote[217].speaker SPEAKER_24
transcript.pyannote[217].start 3241.88721875
transcript.pyannote[217].end 3245.36346875
transcript.pyannote[218].speaker SPEAKER_24
transcript.pyannote[218].start 3246.10596875
transcript.pyannote[218].end 3251.84346875
transcript.pyannote[219].speaker SPEAKER_16
transcript.pyannote[219].start 3248.36721875
transcript.pyannote[219].end 3250.10534375
transcript.pyannote[220].speaker SPEAKER_16
transcript.pyannote[220].start 3250.47659375
transcript.pyannote[220].end 3254.00346875
transcript.pyannote[221].speaker SPEAKER_24
transcript.pyannote[221].start 3253.83471875
transcript.pyannote[221].end 3265.61346875
transcript.pyannote[222].speaker SPEAKER_16
transcript.pyannote[222].start 3254.62784375
transcript.pyannote[222].end 3255.72471875
transcript.pyannote[223].speaker SPEAKER_16
transcript.pyannote[223].start 3257.66534375
transcript.pyannote[223].end 3259.82534375
transcript.pyannote[224].speaker SPEAKER_16
transcript.pyannote[224].start 3264.29721875
transcript.pyannote[224].end 3269.37659375
transcript.pyannote[225].speaker SPEAKER_16
transcript.pyannote[225].start 3269.61284375
transcript.pyannote[225].end 3279.53534375
transcript.pyannote[226].speaker SPEAKER_03
transcript.pyannote[226].start 3273.61221875
transcript.pyannote[226].end 3274.06784375
transcript.pyannote[227].speaker SPEAKER_22
transcript.pyannote[227].start 3275.04659375
transcript.pyannote[227].end 3275.08034375
transcript.pyannote[228].speaker SPEAKER_03
transcript.pyannote[228].start 3275.08034375
transcript.pyannote[228].end 3275.89034375
transcript.pyannote[229].speaker SPEAKER_03
transcript.pyannote[229].start 3277.52721875
transcript.pyannote[229].end 3277.83096875
transcript.pyannote[230].speaker SPEAKER_03
transcript.pyannote[230].start 3278.74221875
transcript.pyannote[230].end 3278.92784375
transcript.pyannote[231].speaker SPEAKER_03
transcript.pyannote[231].start 3281.17221875
transcript.pyannote[231].end 3282.60659375
transcript.pyannote[232].speaker SPEAKER_03
transcript.pyannote[232].start 3284.56409375
transcript.pyannote[232].end 3286.84221875
transcript.pyannote[233].speaker SPEAKER_06
transcript.pyannote[233].start 3295.31346875
transcript.pyannote[233].end 3297.22034375
transcript.pyannote[234].speaker SPEAKER_03
transcript.pyannote[234].start 3297.42284375
transcript.pyannote[234].end 3297.99659375
transcript.pyannote[235].speaker SPEAKER_24
transcript.pyannote[235].start 3303.85221875
transcript.pyannote[235].end 3304.34159375
transcript.pyannote[236].speaker SPEAKER_06
transcript.pyannote[236].start 3304.99971875
transcript.pyannote[236].end 3312.35721875
transcript.pyannote[237].speaker SPEAKER_06
transcript.pyannote[237].start 3312.64409375
transcript.pyannote[237].end 3313.82534375
transcript.pyannote[238].speaker SPEAKER_06
transcript.pyannote[238].start 3314.06159375
transcript.pyannote[238].end 3321.97596875
transcript.pyannote[239].speaker SPEAKER_06
transcript.pyannote[239].start 3322.11096875
transcript.pyannote[239].end 3326.19471875
transcript.pyannote[240].speaker SPEAKER_06
transcript.pyannote[240].start 3326.58284375
transcript.pyannote[240].end 3327.22409375
transcript.pyannote[241].speaker SPEAKER_06
transcript.pyannote[241].start 3327.73034375
transcript.pyannote[241].end 3329.04659375
transcript.pyannote[242].speaker SPEAKER_06
transcript.pyannote[242].start 3329.19846875
transcript.pyannote[242].end 3332.26971875
transcript.pyannote[243].speaker SPEAKER_06
transcript.pyannote[243].start 3332.47221875
transcript.pyannote[243].end 3341.26409375
transcript.pyannote[244].speaker SPEAKER_06
transcript.pyannote[244].start 3341.92221875
transcript.pyannote[244].end 3349.46534375
transcript.pyannote[245].speaker SPEAKER_06
transcript.pyannote[245].start 3350.54534375
transcript.pyannote[245].end 3355.94534375
transcript.pyannote[246].speaker SPEAKER_06
transcript.pyannote[246].start 3356.29971875
transcript.pyannote[246].end 3361.15971875
transcript.pyannote[247].speaker SPEAKER_24
transcript.pyannote[247].start 3362.44221875
transcript.pyannote[247].end 3389.86409375
transcript.pyannote[248].speaker SPEAKER_06
transcript.pyannote[248].start 3385.22346875
transcript.pyannote[248].end 3385.67909375
transcript.pyannote[249].speaker SPEAKER_06
transcript.pyannote[249].start 3390.53909375
transcript.pyannote[249].end 3434.12721875
transcript.pyannote[250].speaker SPEAKER_06
transcript.pyannote[250].start 3434.26221875
transcript.pyannote[250].end 3438.85221875
transcript.pyannote[251].speaker SPEAKER_06
transcript.pyannote[251].start 3439.40909375
transcript.pyannote[251].end 3446.41221875
transcript.pyannote[252].speaker SPEAKER_33
transcript.pyannote[252].start 3448.53846875
transcript.pyannote[252].end 3481.27596875
transcript.pyannote[253].speaker SPEAKER_00
transcript.pyannote[253].start 3453.92159375
transcript.pyannote[253].end 3454.42784375
transcript.pyannote[254].speaker SPEAKER_06
transcript.pyannote[254].start 3480.43221875
transcript.pyannote[254].end 3490.50659375
transcript.pyannote[255].speaker SPEAKER_06
transcript.pyannote[255].start 3491.38409375
transcript.pyannote[255].end 3491.68784375
transcript.pyannote[256].speaker SPEAKER_06
transcript.pyannote[256].start 3492.05909375
transcript.pyannote[256].end 3499.78784375
transcript.pyannote[257].speaker SPEAKER_06
transcript.pyannote[257].start 3500.02409375
transcript.pyannote[257].end 3515.11034375
transcript.pyannote[258].speaker SPEAKER_06
transcript.pyannote[258].start 3515.38034375
transcript.pyannote[258].end 3516.96659375
transcript.pyannote[259].speaker SPEAKER_06
transcript.pyannote[259].start 3517.13534375
transcript.pyannote[259].end 3517.47284375
transcript.pyannote[260].speaker SPEAKER_06
transcript.pyannote[260].start 3517.62471875
transcript.pyannote[260].end 3521.92784375
transcript.pyannote[261].speaker SPEAKER_06
transcript.pyannote[261].start 3522.01221875
transcript.pyannote[261].end 3539.32596875
transcript.pyannote[262].speaker SPEAKER_06
transcript.pyannote[262].start 3540.28784375
transcript.pyannote[262].end 3554.05784375
transcript.pyannote[263].speaker SPEAKER_06
transcript.pyannote[263].start 3554.10846875
transcript.pyannote[263].end 3557.17971875
transcript.pyannote[264].speaker SPEAKER_24
transcript.pyannote[264].start 3558.37784375
transcript.pyannote[264].end 3566.83221875
transcript.pyannote[265].speaker SPEAKER_29
transcript.pyannote[265].start 3566.83221875
transcript.pyannote[265].end 3567.18659375
transcript.pyannote[266].speaker SPEAKER_24
transcript.pyannote[266].start 3567.60846875
transcript.pyannote[266].end 3618.68909375
transcript.pyannote[267].speaker SPEAKER_29
transcript.pyannote[267].start 3575.59034375
transcript.pyannote[267].end 3575.97846875
transcript.pyannote[268].speaker SPEAKER_00
transcript.pyannote[268].start 3586.93034375
transcript.pyannote[268].end 3587.28471875
transcript.pyannote[269].speaker SPEAKER_06
transcript.pyannote[269].start 3606.11721875
transcript.pyannote[269].end 3606.97784375
transcript.pyannote[270].speaker SPEAKER_00
transcript.pyannote[270].start 3606.97784375
transcript.pyannote[270].end 3607.39971875
transcript.pyannote[271].speaker SPEAKER_06
transcript.pyannote[271].start 3618.52034375
transcript.pyannote[271].end 3623.59971875
transcript.pyannote[272].speaker SPEAKER_24
transcript.pyannote[272].start 3624.91596875
transcript.pyannote[272].end 3626.14784375
transcript.pyannote[273].speaker SPEAKER_06
transcript.pyannote[273].start 3625.77659375
transcript.pyannote[273].end 3630.31596875
transcript.pyannote[274].speaker SPEAKER_24
transcript.pyannote[274].start 3630.31596875
transcript.pyannote[274].end 3630.85596875
transcript.pyannote[275].speaker SPEAKER_22
transcript.pyannote[275].start 3630.85596875
transcript.pyannote[275].end 3630.94034375
transcript.pyannote[276].speaker SPEAKER_06
transcript.pyannote[276].start 3630.87284375
transcript.pyannote[276].end 3642.76971875
transcript.pyannote[277].speaker SPEAKER_06
transcript.pyannote[277].start 3643.10721875
transcript.pyannote[277].end 3658.51409375
transcript.pyannote[278].speaker SPEAKER_06
transcript.pyannote[278].start 3658.91909375
transcript.pyannote[278].end 3659.56034375
transcript.pyannote[279].speaker SPEAKER_24
transcript.pyannote[279].start 3660.30284375
transcript.pyannote[279].end 3667.39034375
transcript.pyannote[280].speaker SPEAKER_06
transcript.pyannote[280].start 3667.01909375
transcript.pyannote[280].end 3667.94721875
transcript.pyannote[281].speaker SPEAKER_24
transcript.pyannote[281].start 3667.94721875
transcript.pyannote[281].end 3668.52096875
transcript.pyannote[282].speaker SPEAKER_24
transcript.pyannote[282].start 3669.41534375
transcript.pyannote[282].end 3672.72284375
transcript.pyannote[283].speaker SPEAKER_24
transcript.pyannote[283].start 3672.97596875
transcript.pyannote[283].end 3722.03159375
transcript.pyannote[284].speaker SPEAKER_22
transcript.pyannote[284].start 3680.18159375
transcript.pyannote[284].end 3680.26596875
transcript.pyannote[285].speaker SPEAKER_29
transcript.pyannote[285].start 3680.26596875
transcript.pyannote[285].end 3680.48534375
transcript.pyannote[286].speaker SPEAKER_06
transcript.pyannote[286].start 3722.03159375
transcript.pyannote[286].end 3735.85221875
transcript.pyannote[287].speaker SPEAKER_24
transcript.pyannote[287].start 3722.04846875
transcript.pyannote[287].end 3722.08221875
transcript.pyannote[288].speaker SPEAKER_06
transcript.pyannote[288].start 3735.93659375
transcript.pyannote[288].end 3745.53846875
transcript.pyannote[289].speaker SPEAKER_00
transcript.pyannote[289].start 3743.41221875
transcript.pyannote[289].end 3743.49659375
transcript.pyannote[290].speaker SPEAKER_06
transcript.pyannote[290].start 3745.69034375
transcript.pyannote[290].end 3762.09284375
transcript.pyannote[291].speaker SPEAKER_24
transcript.pyannote[291].start 3763.03784375
transcript.pyannote[291].end 3791.99534375
transcript.pyannote[292].speaker SPEAKER_00
transcript.pyannote[292].start 3770.91846875
transcript.pyannote[292].end 3771.69471875
transcript.pyannote[293].speaker SPEAKER_00
transcript.pyannote[293].start 3779.23784375
transcript.pyannote[293].end 3779.60909375
transcript.pyannote[294].speaker SPEAKER_22
transcript.pyannote[294].start 3786.29159375
transcript.pyannote[294].end 3786.32534375
transcript.pyannote[295].speaker SPEAKER_29
transcript.pyannote[295].start 3786.32534375
transcript.pyannote[295].end 3786.42659375
transcript.pyannote[296].speaker SPEAKER_29
transcript.pyannote[296].start 3786.71346875
transcript.pyannote[296].end 3786.74721875
transcript.pyannote[297].speaker SPEAKER_22
transcript.pyannote[297].start 3786.74721875
transcript.pyannote[297].end 3786.76409375
transcript.pyannote[298].speaker SPEAKER_24
transcript.pyannote[298].start 3792.43409375
transcript.pyannote[298].end 3823.82159375
transcript.pyannote[299].speaker SPEAKER_00
transcript.pyannote[299].start 3813.12284375
transcript.pyannote[299].end 3814.05096875
transcript.pyannote[300].speaker SPEAKER_06
transcript.pyannote[300].start 3817.02096875
transcript.pyannote[300].end 3817.22346875
transcript.pyannote[301].speaker SPEAKER_06
transcript.pyannote[301].start 3823.92284375
transcript.pyannote[301].end 3826.99409375
transcript.pyannote[302].speaker SPEAKER_06
transcript.pyannote[302].start 3827.58471875
transcript.pyannote[302].end 3845.60721875
transcript.pyannote[303].speaker SPEAKER_06
transcript.pyannote[303].start 3846.34971875
transcript.pyannote[303].end 3865.97534375
transcript.pyannote[304].speaker SPEAKER_06
transcript.pyannote[304].start 3866.31284375
transcript.pyannote[304].end 3878.02409375
transcript.pyannote[305].speaker SPEAKER_06
transcript.pyannote[305].start 3878.54721875
transcript.pyannote[305].end 3902.23971875
transcript.pyannote[306].speaker SPEAKER_06
transcript.pyannote[306].start 3902.42534375
transcript.pyannote[306].end 3904.26471875
transcript.pyannote[307].speaker SPEAKER_24
transcript.pyannote[307].start 3904.80471875
transcript.pyannote[307].end 3918.10221875
transcript.pyannote[308].speaker SPEAKER_06
transcript.pyannote[308].start 3908.26409375
transcript.pyannote[308].end 3908.53409375
transcript.pyannote[309].speaker SPEAKER_24
transcript.pyannote[309].start 3918.62534375
transcript.pyannote[309].end 3928.21034375
transcript.pyannote[310].speaker SPEAKER_22
transcript.pyannote[310].start 3928.10909375
transcript.pyannote[310].end 3928.49721875
transcript.pyannote[311].speaker SPEAKER_24
transcript.pyannote[311].start 3928.31159375
transcript.pyannote[311].end 3928.42971875
transcript.pyannote[312].speaker SPEAKER_24
transcript.pyannote[312].start 3928.44659375
transcript.pyannote[312].end 3929.64471875
transcript.pyannote[313].speaker SPEAKER_24
transcript.pyannote[313].start 3929.99909375
transcript.pyannote[313].end 3946.03034375
transcript.pyannote[314].speaker SPEAKER_06
transcript.pyannote[314].start 3943.90409375
transcript.pyannote[314].end 3944.27534375
transcript.pyannote[315].speaker SPEAKER_06
transcript.pyannote[315].start 3946.03034375
transcript.pyannote[315].end 3993.95534375
transcript.pyannote[316].speaker SPEAKER_24
transcript.pyannote[316].start 3994.34346875
transcript.pyannote[316].end 4019.60534375
transcript.pyannote[317].speaker SPEAKER_29
transcript.pyannote[317].start 4004.73846875
transcript.pyannote[317].end 4005.16034375
transcript.pyannote[318].speaker SPEAKER_00
transcript.pyannote[318].start 4008.29909375
transcript.pyannote[318].end 4008.65346875
transcript.pyannote[319].speaker SPEAKER_22
transcript.pyannote[319].start 4015.79159375
transcript.pyannote[319].end 4016.19659375
transcript.pyannote[320].speaker SPEAKER_24
transcript.pyannote[320].start 4020.98909375
transcript.pyannote[320].end 4029.78096875
transcript.pyannote[321].speaker SPEAKER_06
transcript.pyannote[321].start 4023.45284375
transcript.pyannote[321].end 4026.10221875
transcript.pyannote[322].speaker SPEAKER_06
transcript.pyannote[322].start 4027.87409375
transcript.pyannote[322].end 4028.65034375
transcript.pyannote[323].speaker SPEAKER_06
transcript.pyannote[323].start 4030.27034375
transcript.pyannote[323].end 4042.90971875
transcript.pyannote[324].speaker SPEAKER_06
transcript.pyannote[324].start 4043.14596875
transcript.pyannote[324].end 4046.63909375
transcript.pyannote[325].speaker SPEAKER_06
transcript.pyannote[325].start 4046.87534375
transcript.pyannote[325].end 4049.50784375
transcript.pyannote[326].speaker SPEAKER_06
transcript.pyannote[326].start 4050.03096875
transcript.pyannote[326].end 4052.08971875
transcript.pyannote[327].speaker SPEAKER_06
transcript.pyannote[327].start 4052.20784375
transcript.pyannote[327].end 4054.24971875
transcript.pyannote[328].speaker SPEAKER_06
transcript.pyannote[328].start 4054.55346875
transcript.pyannote[328].end 4060.24034375
transcript.pyannote[329].speaker SPEAKER_06
transcript.pyannote[329].start 4060.44284375
transcript.pyannote[329].end 4070.56784375
transcript.pyannote[330].speaker SPEAKER_24
transcript.pyannote[330].start 4071.59721875
transcript.pyannote[330].end 4083.24096875
transcript.pyannote[331].speaker SPEAKER_24
transcript.pyannote[331].start 4083.93284375
transcript.pyannote[331].end 4084.77659375
transcript.pyannote[332].speaker SPEAKER_24
transcript.pyannote[332].start 4085.08034375
transcript.pyannote[332].end 4130.03534375
transcript.pyannote[333].speaker SPEAKER_00
transcript.pyannote[333].start 4086.02534375
transcript.pyannote[333].end 4086.05909375
transcript.pyannote[334].speaker SPEAKER_00
transcript.pyannote[334].start 4092.30284375
transcript.pyannote[334].end 4092.55596875
transcript.pyannote[335].speaker SPEAKER_24
transcript.pyannote[335].start 4130.28846875
transcript.pyannote[335].end 4139.36721875
transcript.pyannote[336].speaker SPEAKER_06
transcript.pyannote[336].start 4139.73846875
transcript.pyannote[336].end 4143.29909375
transcript.pyannote[337].speaker SPEAKER_24
transcript.pyannote[337].start 4139.89034375
transcript.pyannote[337].end 4140.26159375
transcript.pyannote[338].speaker SPEAKER_06
transcript.pyannote[338].start 4143.77159375
transcript.pyannote[338].end 4147.56846875
transcript.pyannote[339].speaker SPEAKER_06
transcript.pyannote[339].start 4147.95659375
transcript.pyannote[339].end 4179.15846875
transcript.pyannote[340].speaker SPEAKER_06
transcript.pyannote[340].start 4179.19221875
transcript.pyannote[340].end 4190.70096875
transcript.pyannote[341].speaker SPEAKER_24
transcript.pyannote[341].start 4190.70096875
transcript.pyannote[341].end 4205.97284375
transcript.pyannote[342].speaker SPEAKER_06
transcript.pyannote[342].start 4195.40909375
transcript.pyannote[342].end 4195.71284375
transcript.pyannote[343].speaker SPEAKER_06
transcript.pyannote[343].start 4205.63534375
transcript.pyannote[343].end 4210.91721875
transcript.pyannote[344].speaker SPEAKER_03
transcript.pyannote[344].start 4209.09471875
transcript.pyannote[344].end 4210.83284375
transcript.pyannote[345].speaker SPEAKER_03
transcript.pyannote[345].start 4216.57034375
transcript.pyannote[345].end 4218.08909375
transcript.pyannote[346].speaker SPEAKER_03
transcript.pyannote[346].start 4218.83159375
transcript.pyannote[346].end 4221.48096875
transcript.pyannote[347].speaker SPEAKER_19
transcript.pyannote[347].start 4227.48846875
transcript.pyannote[347].end 4230.74534375
transcript.pyannote[348].speaker SPEAKER_03
transcript.pyannote[348].start 4231.33596875
transcript.pyannote[348].end 4232.12909375
transcript.pyannote[349].speaker SPEAKER_24
transcript.pyannote[349].start 4237.79909375
transcript.pyannote[349].end 4238.44034375
transcript.pyannote[350].speaker SPEAKER_19
transcript.pyannote[350].start 4238.47409375
transcript.pyannote[350].end 4239.33471875
transcript.pyannote[351].speaker SPEAKER_19
transcript.pyannote[351].start 4239.48659375
transcript.pyannote[351].end 4248.27846875
transcript.pyannote[352].speaker SPEAKER_19
transcript.pyannote[352].start 4249.10534375
transcript.pyannote[352].end 4262.55471875
transcript.pyannote[353].speaker SPEAKER_19
transcript.pyannote[353].start 4262.90909375
transcript.pyannote[353].end 4267.51596875
transcript.pyannote[354].speaker SPEAKER_19
transcript.pyannote[354].start 4268.10659375
transcript.pyannote[354].end 4269.18659375
transcript.pyannote[355].speaker SPEAKER_19
transcript.pyannote[355].start 4269.62534375
transcript.pyannote[355].end 4272.98346875
transcript.pyannote[356].speaker SPEAKER_19
transcript.pyannote[356].start 4273.47284375
transcript.pyannote[356].end 4274.13096875
transcript.pyannote[357].speaker SPEAKER_19
transcript.pyannote[357].start 4274.82284375
transcript.pyannote[357].end 4275.68346875
transcript.pyannote[358].speaker SPEAKER_19
transcript.pyannote[358].start 4275.98721875
transcript.pyannote[358].end 4283.17596875
transcript.pyannote[359].speaker SPEAKER_19
transcript.pyannote[359].start 4283.54721875
transcript.pyannote[359].end 4289.09909375
transcript.pyannote[360].speaker SPEAKER_19
transcript.pyannote[360].start 4289.90909375
transcript.pyannote[360].end 4290.68534375
transcript.pyannote[361].speaker SPEAKER_19
transcript.pyannote[361].start 4290.83721875
transcript.pyannote[361].end 4291.86659375
transcript.pyannote[362].speaker SPEAKER_19
transcript.pyannote[362].start 4292.03534375
transcript.pyannote[362].end 4324.87409375
transcript.pyannote[363].speaker SPEAKER_00
transcript.pyannote[363].start 4323.76034375
transcript.pyannote[363].end 4323.86159375
transcript.pyannote[364].speaker SPEAKER_19
transcript.pyannote[364].start 4325.41409375
transcript.pyannote[364].end 4339.31909375
transcript.pyannote[365].speaker SPEAKER_19
transcript.pyannote[365].start 4339.89284375
transcript.pyannote[365].end 4342.89659375
transcript.pyannote[366].speaker SPEAKER_19
transcript.pyannote[366].start 4343.58846875
transcript.pyannote[366].end 4344.65159375
transcript.pyannote[367].speaker SPEAKER_24
transcript.pyannote[367].start 4344.65159375
transcript.pyannote[367].end 4345.71471875
transcript.pyannote[368].speaker SPEAKER_24
transcript.pyannote[368].start 4346.20409375
transcript.pyannote[368].end 4346.65971875
transcript.pyannote[369].speaker SPEAKER_24
transcript.pyannote[369].start 4347.26721875
transcript.pyannote[369].end 4353.20721875
transcript.pyannote[370].speaker SPEAKER_19
transcript.pyannote[370].start 4349.74784375
transcript.pyannote[370].end 4349.86596875
transcript.pyannote[371].speaker SPEAKER_19
transcript.pyannote[371].start 4353.44346875
transcript.pyannote[371].end 4373.77784375
transcript.pyannote[372].speaker SPEAKER_19
transcript.pyannote[372].start 4373.98034375
transcript.pyannote[372].end 4380.37596875
transcript.pyannote[373].speaker SPEAKER_24
transcript.pyannote[373].start 4377.22034375
transcript.pyannote[373].end 4378.70534375
transcript.pyannote[374].speaker SPEAKER_24
transcript.pyannote[374].start 4380.49409375
transcript.pyannote[374].end 4385.74221875
transcript.pyannote[375].speaker SPEAKER_19
transcript.pyannote[375].start 4385.03346875
transcript.pyannote[375].end 4389.52221875
transcript.pyannote[376].speaker SPEAKER_24
transcript.pyannote[376].start 4389.20159375
transcript.pyannote[376].end 4395.86721875
transcript.pyannote[377].speaker SPEAKER_19
transcript.pyannote[377].start 4395.86721875
transcript.pyannote[377].end 4404.49034375
transcript.pyannote[378].speaker SPEAKER_24
transcript.pyannote[378].start 4404.82784375
transcript.pyannote[378].end 4408.92846875
transcript.pyannote[379].speaker SPEAKER_19
transcript.pyannote[379].start 4406.16096875
transcript.pyannote[379].end 4407.03846875
transcript.pyannote[380].speaker SPEAKER_19
transcript.pyannote[380].start 4409.19846875
transcript.pyannote[380].end 4410.88596875
transcript.pyannote[381].speaker SPEAKER_24
transcript.pyannote[381].start 4410.97034375
transcript.pyannote[381].end 4413.16409375
transcript.pyannote[382].speaker SPEAKER_19
transcript.pyannote[382].start 4411.18971875
transcript.pyannote[382].end 4411.93221875
transcript.pyannote[383].speaker SPEAKER_24
transcript.pyannote[383].start 4414.00784375
transcript.pyannote[383].end 4417.23096875
transcript.pyannote[384].speaker SPEAKER_19
transcript.pyannote[384].start 4414.04159375
transcript.pyannote[384].end 4414.41284375
transcript.pyannote[385].speaker SPEAKER_19
transcript.pyannote[385].start 4416.80909375
transcript.pyannote[385].end 4422.44534375
transcript.pyannote[386].speaker SPEAKER_19
transcript.pyannote[386].start 4422.59721875
transcript.pyannote[386].end 4425.83721875
transcript.pyannote[387].speaker SPEAKER_19
transcript.pyannote[387].start 4426.83284375
transcript.pyannote[387].end 4427.25471875
transcript.pyannote[388].speaker SPEAKER_22
transcript.pyannote[388].start 4427.64284375
transcript.pyannote[388].end 4427.98034375
transcript.pyannote[389].speaker SPEAKER_19
transcript.pyannote[389].start 4428.65534375
transcript.pyannote[389].end 4428.95909375
transcript.pyannote[390].speaker SPEAKER_19
transcript.pyannote[390].start 4429.85346875
transcript.pyannote[390].end 4431.35534375
transcript.pyannote[391].speaker SPEAKER_19
transcript.pyannote[391].start 4431.92909375
transcript.pyannote[391].end 4484.52846875
transcript.pyannote[392].speaker SPEAKER_19
transcript.pyannote[392].start 4485.10221875
transcript.pyannote[392].end 4507.49534375
transcript.pyannote[393].speaker SPEAKER_19
transcript.pyannote[393].start 4508.59221875
transcript.pyannote[393].end 4513.78971875
transcript.pyannote[394].speaker SPEAKER_24
transcript.pyannote[394].start 4512.69284375
transcript.pyannote[394].end 4514.58284375
transcript.pyannote[395].speaker SPEAKER_19
transcript.pyannote[395].start 4514.51534375
transcript.pyannote[395].end 4518.91971875
transcript.pyannote[396].speaker SPEAKER_19
transcript.pyannote[396].start 4519.44284375
transcript.pyannote[396].end 4547.65784375
transcript.pyannote[397].speaker SPEAKER_19
transcript.pyannote[397].start 4548.55221875
transcript.pyannote[397].end 4579.04534375
transcript.pyannote[398].speaker SPEAKER_19
transcript.pyannote[398].start 4579.21409375
transcript.pyannote[398].end 4590.84096875
transcript.pyannote[399].speaker SPEAKER_19
transcript.pyannote[399].start 4591.88721875
transcript.pyannote[399].end 4596.39284375
transcript.pyannote[400].speaker SPEAKER_19
transcript.pyannote[400].start 4597.13534375
transcript.pyannote[400].end 4598.31659375
transcript.pyannote[401].speaker SPEAKER_24
transcript.pyannote[401].start 4598.31659375
transcript.pyannote[401].end 4600.71284375
transcript.pyannote[402].speaker SPEAKER_19
transcript.pyannote[402].start 4600.45971875
transcript.pyannote[402].end 4600.72971875
transcript.pyannote[403].speaker SPEAKER_24
transcript.pyannote[403].start 4600.72971875
transcript.pyannote[403].end 4614.63471875
transcript.pyannote[404].speaker SPEAKER_24
transcript.pyannote[404].start 4615.64721875
transcript.pyannote[404].end 4624.16909375
transcript.pyannote[405].speaker SPEAKER_20
transcript.pyannote[405].start 4624.33784375
transcript.pyannote[405].end 4625.60346875
transcript.pyannote[406].speaker SPEAKER_24
transcript.pyannote[406].start 4624.89471875
transcript.pyannote[406].end 4628.03346875
transcript.pyannote[407].speaker SPEAKER_20
transcript.pyannote[407].start 4629.53534375
transcript.pyannote[407].end 4629.95721875
transcript.pyannote[408].speaker SPEAKER_24
transcript.pyannote[408].start 4629.95721875
transcript.pyannote[408].end 4631.05409375
transcript.pyannote[409].speaker SPEAKER_20
transcript.pyannote[409].start 4629.99096875
transcript.pyannote[409].end 4630.96971875
transcript.pyannote[410].speaker SPEAKER_19
transcript.pyannote[410].start 4630.96971875
transcript.pyannote[410].end 4631.03721875
transcript.pyannote[411].speaker SPEAKER_20
transcript.pyannote[411].start 4631.03721875
transcript.pyannote[411].end 4631.17221875
transcript.pyannote[412].speaker SPEAKER_19
transcript.pyannote[412].start 4631.05409375
transcript.pyannote[412].end 4631.13846875
transcript.pyannote[413].speaker SPEAKER_19
transcript.pyannote[413].start 4631.17221875
transcript.pyannote[413].end 4669.02284375
transcript.pyannote[414].speaker SPEAKER_20
transcript.pyannote[414].start 4631.27346875
transcript.pyannote[414].end 4631.96534375
transcript.pyannote[415].speaker SPEAKER_24
transcript.pyannote[415].start 4631.96534375
transcript.pyannote[415].end 4632.03284375
transcript.pyannote[416].speaker SPEAKER_20
transcript.pyannote[416].start 4632.03284375
transcript.pyannote[416].end 4634.58096875
transcript.pyannote[417].speaker SPEAKER_08
transcript.pyannote[417].start 4654.56096875
transcript.pyannote[417].end 4654.59471875
transcript.pyannote[418].speaker SPEAKER_20
transcript.pyannote[418].start 4654.59471875
transcript.pyannote[418].end 4655.01659375
transcript.pyannote[419].speaker SPEAKER_20
transcript.pyannote[419].start 4659.16784375
transcript.pyannote[419].end 4659.70784375
transcript.pyannote[420].speaker SPEAKER_20
transcript.pyannote[420].start 4669.02284375
transcript.pyannote[420].end 4674.96284375
transcript.pyannote[421].speaker SPEAKER_19
transcript.pyannote[421].start 4674.96284375
transcript.pyannote[421].end 4675.03034375
transcript.pyannote[422].speaker SPEAKER_20
transcript.pyannote[422].start 4675.03034375
transcript.pyannote[422].end 4675.97534375
transcript.pyannote[423].speaker SPEAKER_19
transcript.pyannote[423].start 4675.97534375
transcript.pyannote[423].end 4676.02596875
transcript.pyannote[424].speaker SPEAKER_20
transcript.pyannote[424].start 4676.02596875
transcript.pyannote[424].end 4676.97096875
transcript.pyannote[425].speaker SPEAKER_19
transcript.pyannote[425].start 4676.97096875
transcript.pyannote[425].end 4677.03846875
transcript.pyannote[426].speaker SPEAKER_20
transcript.pyannote[426].start 4677.03846875
transcript.pyannote[426].end 4677.96659375
transcript.pyannote[427].speaker SPEAKER_19
transcript.pyannote[427].start 4677.96659375
transcript.pyannote[427].end 4678.03409375
transcript.pyannote[428].speaker SPEAKER_20
transcript.pyannote[428].start 4678.03409375
transcript.pyannote[428].end 4678.96221875
transcript.pyannote[429].speaker SPEAKER_19
transcript.pyannote[429].start 4678.96221875
transcript.pyannote[429].end 4679.02971875
transcript.pyannote[430].speaker SPEAKER_20
transcript.pyannote[430].start 4679.02971875
transcript.pyannote[430].end 4686.18471875
transcript.pyannote[431].speaker SPEAKER_19
transcript.pyannote[431].start 4679.14784375
transcript.pyannote[431].end 4680.17721875
transcript.pyannote[432].speaker SPEAKER_19
transcript.pyannote[432].start 4680.86909375
transcript.pyannote[432].end 4681.71284375
transcript.pyannote[433].speaker SPEAKER_19
transcript.pyannote[433].start 4682.48909375
transcript.pyannote[433].end 4682.97846875
transcript.pyannote[434].speaker SPEAKER_24
transcript.pyannote[434].start 4682.97846875
transcript.pyannote[434].end 4683.02909375
transcript.pyannote[435].speaker SPEAKER_19
transcript.pyannote[435].start 4683.02909375
transcript.pyannote[435].end 4683.72096875
transcript.pyannote[436].speaker SPEAKER_20
transcript.pyannote[436].start 4686.70784375
transcript.pyannote[436].end 4687.97346875
transcript.pyannote[437].speaker SPEAKER_19
transcript.pyannote[437].start 4687.97346875
transcript.pyannote[437].end 4694.03159375
transcript.pyannote[438].speaker SPEAKER_20
transcript.pyannote[438].start 4690.84221875
transcript.pyannote[438].end 4692.24284375
transcript.pyannote[439].speaker SPEAKER_20
transcript.pyannote[439].start 4694.03159375
transcript.pyannote[439].end 4695.97221875
transcript.pyannote[440].speaker SPEAKER_20
transcript.pyannote[440].start 4696.56284375
transcript.pyannote[440].end 4705.96221875
transcript.pyannote[441].speaker SPEAKER_24
transcript.pyannote[441].start 4699.80284375
transcript.pyannote[441].end 4704.54471875
transcript.pyannote[442].speaker SPEAKER_19
transcript.pyannote[442].start 4704.54471875
transcript.pyannote[442].end 4704.57846875
transcript.pyannote[443].speaker SPEAKER_19
transcript.pyannote[443].start 4705.96221875
transcript.pyannote[443].end 4706.02971875
transcript.pyannote[444].speaker SPEAKER_20
transcript.pyannote[444].start 4706.02971875
transcript.pyannote[444].end 4706.04659375
transcript.pyannote[445].speaker SPEAKER_19
transcript.pyannote[445].start 4706.04659375
transcript.pyannote[445].end 4726.29659375
transcript.pyannote[446].speaker SPEAKER_20
transcript.pyannote[446].start 4707.80159375
transcript.pyannote[446].end 4712.71221875
transcript.pyannote[447].speaker SPEAKER_19
transcript.pyannote[447].start 4726.88721875
transcript.pyannote[447].end 4761.14346875
transcript.pyannote[448].speaker SPEAKER_22
transcript.pyannote[448].start 4749.44909375
transcript.pyannote[448].end 4750.14096875
transcript.pyannote[449].speaker SPEAKER_24
transcript.pyannote[449].start 4761.04221875
transcript.pyannote[449].end 4772.24721875
transcript.pyannote[450].speaker SPEAKER_20
transcript.pyannote[450].start 4761.14346875
transcript.pyannote[450].end 4761.16034375
transcript.pyannote[451].speaker SPEAKER_19
transcript.pyannote[451].start 4761.16034375
transcript.pyannote[451].end 4761.17721875
transcript.pyannote[452].speaker SPEAKER_20
transcript.pyannote[452].start 4761.17721875
transcript.pyannote[452].end 4761.19409375
transcript.pyannote[453].speaker SPEAKER_20
transcript.pyannote[453].start 4769.15909375
transcript.pyannote[453].end 4769.80034375
transcript.pyannote[454].speaker SPEAKER_22
transcript.pyannote[454].start 4769.80034375
transcript.pyannote[454].end 4769.83409375
transcript.pyannote[455].speaker SPEAKER_20
transcript.pyannote[455].start 4769.83409375
transcript.pyannote[455].end 4769.85096875
transcript.pyannote[456].speaker SPEAKER_20
transcript.pyannote[456].start 4770.44159375
transcript.pyannote[456].end 4771.06596875
transcript.pyannote[457].speaker SPEAKER_20
transcript.pyannote[457].start 4771.55534375
transcript.pyannote[457].end 4772.11221875
transcript.pyannote[458].speaker SPEAKER_24
transcript.pyannote[458].start 4772.33159375
transcript.pyannote[458].end 4779.04784375
transcript.pyannote[459].speaker SPEAKER_20
transcript.pyannote[459].start 4772.39909375
transcript.pyannote[459].end 4772.51721875
transcript.pyannote[460].speaker SPEAKER_22
transcript.pyannote[460].start 4772.51721875
transcript.pyannote[460].end 4773.09096875
transcript.pyannote[461].speaker SPEAKER_24
transcript.pyannote[461].start 4779.53721875
transcript.pyannote[461].end 4815.19409375
transcript.pyannote[462].speaker SPEAKER_24
transcript.pyannote[462].start 4815.85221875
transcript.pyannote[462].end 4822.23096875
transcript.pyannote[463].speaker SPEAKER_19
transcript.pyannote[463].start 4821.89346875
transcript.pyannote[463].end 4828.54221875
transcript.pyannote[464].speaker SPEAKER_00
transcript.pyannote[464].start 4827.91784375
transcript.pyannote[464].end 4827.95159375
transcript.pyannote[465].speaker SPEAKER_19
transcript.pyannote[465].start 4828.79534375
transcript.pyannote[465].end 4889.14034375
transcript.pyannote[466].speaker SPEAKER_20
transcript.pyannote[466].start 4835.96721875
transcript.pyannote[466].end 4836.22034375
transcript.pyannote[467].speaker SPEAKER_20
transcript.pyannote[467].start 4838.29596875
transcript.pyannote[467].end 4838.68409375
transcript.pyannote[468].speaker SPEAKER_20
transcript.pyannote[468].start 4842.48096875
transcript.pyannote[468].end 4844.28659375
transcript.pyannote[469].speaker SPEAKER_29
transcript.pyannote[469].start 4876.99034375
transcript.pyannote[469].end 4877.29409375
transcript.pyannote[470].speaker SPEAKER_24
transcript.pyannote[470].start 4889.20784375
transcript.pyannote[470].end 4890.55784375
transcript.pyannote[471].speaker SPEAKER_24
transcript.pyannote[471].start 4890.84471875
transcript.pyannote[471].end 4902.21846875
transcript.pyannote[472].speaker SPEAKER_24
transcript.pyannote[472].start 4902.77534375
transcript.pyannote[472].end 4911.92159375
transcript.pyannote[473].speaker SPEAKER_19
transcript.pyannote[473].start 4910.33534375
transcript.pyannote[473].end 4913.49096875
transcript.pyannote[474].speaker SPEAKER_24
transcript.pyannote[474].start 4912.46159375
transcript.pyannote[474].end 4946.11034375
transcript.pyannote[475].speaker SPEAKER_19
transcript.pyannote[475].start 4917.03471875
transcript.pyannote[475].end 4917.37221875
transcript.pyannote[476].speaker SPEAKER_19
transcript.pyannote[476].start 4920.05534375
transcript.pyannote[476].end 4921.08471875
transcript.pyannote[477].speaker SPEAKER_22
transcript.pyannote[477].start 4921.08471875
transcript.pyannote[477].end 4921.15221875
transcript.pyannote[478].speaker SPEAKER_22
transcript.pyannote[478].start 4922.83971875
transcript.pyannote[478].end 4922.94096875
transcript.pyannote[479].speaker SPEAKER_19
transcript.pyannote[479].start 4949.08034375
transcript.pyannote[479].end 4952.84346875
transcript.pyannote[480].speaker SPEAKER_24
transcript.pyannote[480].start 4950.39659375
transcript.pyannote[480].end 4957.97346875
transcript.pyannote[481].speaker SPEAKER_19
transcript.pyannote[481].start 4954.26096875
transcript.pyannote[481].end 4962.02346875
transcript.pyannote[482].speaker SPEAKER_20
transcript.pyannote[482].start 4957.97346875
transcript.pyannote[482].end 4958.07471875
transcript.pyannote[483].speaker SPEAKER_20
transcript.pyannote[483].start 4962.02346875
transcript.pyannote[483].end 4962.96846875
transcript.pyannote[484].speaker SPEAKER_19
transcript.pyannote[484].start 4962.96846875
transcript.pyannote[484].end 4963.03596875
transcript.pyannote[485].speaker SPEAKER_20
transcript.pyannote[485].start 4963.03596875
transcript.pyannote[485].end 4968.16596875
transcript.pyannote[486].speaker SPEAKER_22
transcript.pyannote[486].start 4966.24221875
transcript.pyannote[486].end 4966.64721875
transcript.pyannote[487].speaker SPEAKER_22
transcript.pyannote[487].start 4968.16596875
transcript.pyannote[487].end 4968.52034375
transcript.pyannote[488].speaker SPEAKER_20
transcript.pyannote[488].start 4968.85784375
transcript.pyannote[488].end 4971.96284375
transcript.pyannote[489].speaker SPEAKER_19
transcript.pyannote[489].start 4971.96284375
transcript.pyannote[489].end 4973.71784375
transcript.pyannote[490].speaker SPEAKER_19
transcript.pyannote[490].start 4974.20721875
transcript.pyannote[490].end 4982.03721875
transcript.pyannote[491].speaker SPEAKER_20
transcript.pyannote[491].start 4982.03721875
transcript.pyannote[491].end 4986.50909375
transcript.pyannote[492].speaker SPEAKER_24
transcript.pyannote[492].start 4986.25596875
transcript.pyannote[492].end 4998.55784375
transcript.pyannote[493].speaker SPEAKER_20
transcript.pyannote[493].start 4989.32721875
transcript.pyannote[493].end 4991.08221875
transcript.pyannote[494].speaker SPEAKER_24
transcript.pyannote[494].start 4999.08096875
transcript.pyannote[494].end 5002.45596875
transcript.pyannote[495].speaker SPEAKER_19
transcript.pyannote[495].start 5000.59971875
transcript.pyannote[495].end 5009.03721875
transcript.pyannote[496].speaker SPEAKER_24
transcript.pyannote[496].start 5009.03721875
transcript.pyannote[496].end 5016.51284375
transcript.pyannote[497].speaker SPEAKER_19
transcript.pyannote[497].start 5009.74596875
transcript.pyannote[497].end 5011.09596875
transcript.pyannote[498].speaker SPEAKER_20
transcript.pyannote[498].start 5012.83409375
transcript.pyannote[498].end 5012.85096875
transcript.pyannote[499].speaker SPEAKER_19
transcript.pyannote[499].start 5012.85096875
transcript.pyannote[499].end 5013.96471875
transcript.pyannote[500].speaker SPEAKER_20
transcript.pyannote[500].start 5013.96471875
transcript.pyannote[500].end 5013.98159375
transcript.pyannote[501].speaker SPEAKER_19
transcript.pyannote[501].start 5013.98159375
transcript.pyannote[501].end 5014.03221875
transcript.pyannote[502].speaker SPEAKER_20
transcript.pyannote[502].start 5014.03221875
transcript.pyannote[502].end 5014.40346875
transcript.pyannote[503].speaker SPEAKER_20
transcript.pyannote[503].start 5016.42846875
transcript.pyannote[503].end 5016.98534375
transcript.pyannote[504].speaker SPEAKER_20
transcript.pyannote[504].start 5017.12034375
transcript.pyannote[504].end 5021.17034375
transcript.pyannote[505].speaker SPEAKER_24
transcript.pyannote[505].start 5019.21284375
transcript.pyannote[505].end 5019.44909375
transcript.pyannote[506].speaker SPEAKER_24
transcript.pyannote[506].start 5020.84971875
transcript.pyannote[506].end 5021.89596875
transcript.pyannote[507].speaker SPEAKER_20
transcript.pyannote[507].start 5021.92971875
transcript.pyannote[507].end 5026.97534375
transcript.pyannote[508].speaker SPEAKER_19
transcript.pyannote[508].start 5026.97534375
transcript.pyannote[508].end 5032.37534375
transcript.pyannote[509].speaker SPEAKER_19
transcript.pyannote[509].start 5032.83096875
transcript.pyannote[509].end 5034.36659375
transcript.pyannote[510].speaker SPEAKER_24
transcript.pyannote[510].start 5035.17659375
transcript.pyannote[510].end 5038.53471875
transcript.pyannote[511].speaker SPEAKER_19
transcript.pyannote[511].start 5037.60659375
transcript.pyannote[511].end 5041.75784375
transcript.pyannote[512].speaker SPEAKER_24
transcript.pyannote[512].start 5041.30221875
transcript.pyannote[512].end 5043.36096875
transcript.pyannote[513].speaker SPEAKER_19
transcript.pyannote[513].start 5043.47909375
transcript.pyannote[513].end 5053.43534375
transcript.pyannote[514].speaker SPEAKER_24
transcript.pyannote[514].start 5053.58721875
transcript.pyannote[514].end 5063.71221875
transcript.pyannote[515].speaker SPEAKER_20
transcript.pyannote[515].start 5060.62409375
transcript.pyannote[515].end 5065.99034375
transcript.pyannote[516].speaker SPEAKER_20
transcript.pyannote[516].start 5066.26034375
transcript.pyannote[516].end 5068.77471875
transcript.pyannote[517].speaker SPEAKER_24
transcript.pyannote[517].start 5068.77471875
transcript.pyannote[517].end 5071.69409375
transcript.pyannote[518].speaker SPEAKER_24
transcript.pyannote[518].start 5072.30159375
transcript.pyannote[518].end 5080.90784375
transcript.pyannote[519].speaker SPEAKER_19
transcript.pyannote[519].start 5076.50346875
transcript.pyannote[519].end 5077.95471875
transcript.pyannote[520].speaker SPEAKER_19
transcript.pyannote[520].start 5078.66346875
transcript.pyannote[520].end 5089.98659375
transcript.pyannote[521].speaker SPEAKER_20
transcript.pyannote[521].start 5088.19784375
transcript.pyannote[521].end 5089.05846875
transcript.pyannote[522].speaker SPEAKER_06
transcript.pyannote[522].start 5089.05846875
transcript.pyannote[522].end 5089.10909375
transcript.pyannote[523].speaker SPEAKER_20
transcript.pyannote[523].start 5089.10909375
transcript.pyannote[523].end 5089.49721875
transcript.pyannote[524].speaker SPEAKER_06
transcript.pyannote[524].start 5089.49721875
transcript.pyannote[524].end 5089.56471875
transcript.pyannote[525].speaker SPEAKER_06
transcript.pyannote[525].start 5091.43784375
transcript.pyannote[525].end 5095.09971875
transcript.pyannote[526].speaker SPEAKER_06
transcript.pyannote[526].start 5101.12409375
transcript.pyannote[526].end 5104.39784375
transcript.pyannote[527].speaker SPEAKER_24
transcript.pyannote[527].start 5109.56159375
transcript.pyannote[527].end 5110.20284375
transcript.pyannote[528].speaker SPEAKER_05
transcript.pyannote[528].start 5110.59096875
transcript.pyannote[528].end 5151.22596875
transcript.pyannote[529].speaker SPEAKER_24
transcript.pyannote[529].start 5151.91784375
transcript.pyannote[529].end 5156.17034375
transcript.pyannote[530].speaker SPEAKER_05
transcript.pyannote[530].start 5156.69346875
transcript.pyannote[530].end 5159.42721875
transcript.pyannote[531].speaker SPEAKER_33
transcript.pyannote[531].start 5159.64659375
transcript.pyannote[531].end 5196.36659375
transcript.pyannote[532].speaker SPEAKER_05
transcript.pyannote[532].start 5195.77596875
transcript.pyannote[532].end 5198.47596875
transcript.pyannote[533].speaker SPEAKER_33
transcript.pyannote[533].start 5197.76721875
transcript.pyannote[533].end 5219.55284375
transcript.pyannote[534].speaker SPEAKER_05
transcript.pyannote[534].start 5218.70909375
transcript.pyannote[534].end 5234.36909375
transcript.pyannote[535].speaker SPEAKER_05
transcript.pyannote[535].start 5234.68971875
transcript.pyannote[535].end 5240.73096875
transcript.pyannote[536].speaker SPEAKER_05
transcript.pyannote[536].start 5240.93346875
transcript.pyannote[536].end 5259.73221875
transcript.pyannote[537].speaker SPEAKER_05
transcript.pyannote[537].start 5260.17096875
transcript.pyannote[537].end 5261.25096875
transcript.pyannote[538].speaker SPEAKER_05
transcript.pyannote[538].start 5261.75721875
transcript.pyannote[538].end 5264.57534375
transcript.pyannote[539].speaker SPEAKER_24
transcript.pyannote[539].start 5262.41534375
transcript.pyannote[539].end 5263.17471875
transcript.pyannote[540].speaker SPEAKER_24
transcript.pyannote[540].start 5264.59221875
transcript.pyannote[540].end 5268.59159375
transcript.pyannote[541].speaker SPEAKER_24
transcript.pyannote[541].start 5268.94596875
transcript.pyannote[541].end 5276.94471875
transcript.pyannote[542].speaker SPEAKER_22
transcript.pyannote[542].start 5276.67471875
transcript.pyannote[542].end 5277.06284375
transcript.pyannote[543].speaker SPEAKER_24
transcript.pyannote[543].start 5277.06284375
transcript.pyannote[543].end 5277.07971875
transcript.pyannote[544].speaker SPEAKER_24
transcript.pyannote[544].start 5277.28221875
transcript.pyannote[544].end 5302.37534375
transcript.pyannote[545].speaker SPEAKER_24
transcript.pyannote[545].start 5302.59471875
transcript.pyannote[545].end 5306.69534375
transcript.pyannote[546].speaker SPEAKER_05
transcript.pyannote[546].start 5307.01596875
transcript.pyannote[546].end 5316.73596875
transcript.pyannote[547].speaker SPEAKER_24
transcript.pyannote[547].start 5307.21846875
transcript.pyannote[547].end 5307.57284375
transcript.pyannote[548].speaker SPEAKER_05
transcript.pyannote[548].start 5317.03971875
transcript.pyannote[548].end 5333.34096875
transcript.pyannote[549].speaker SPEAKER_05
transcript.pyannote[549].start 5333.83034375
transcript.pyannote[549].end 5336.41221875
transcript.pyannote[550].speaker SPEAKER_05
transcript.pyannote[550].start 5336.90159375
transcript.pyannote[550].end 5343.49971875
transcript.pyannote[551].speaker SPEAKER_05
transcript.pyannote[551].start 5343.97221875
transcript.pyannote[551].end 5346.36846875
transcript.pyannote[552].speaker SPEAKER_05
transcript.pyannote[552].start 5346.85784375
transcript.pyannote[552].end 5347.34721875
transcript.pyannote[553].speaker SPEAKER_24
transcript.pyannote[553].start 5346.90846875
transcript.pyannote[553].end 5346.99284375
transcript.pyannote[554].speaker SPEAKER_24
transcript.pyannote[554].start 5347.27971875
transcript.pyannote[554].end 5365.70721875
transcript.pyannote[555].speaker SPEAKER_05
transcript.pyannote[555].start 5350.38471875
transcript.pyannote[555].end 5350.70534375
transcript.pyannote[556].speaker SPEAKER_00
transcript.pyannote[556].start 5358.13034375
transcript.pyannote[556].end 5358.16409375
transcript.pyannote[557].speaker SPEAKER_29
transcript.pyannote[557].start 5358.16409375
transcript.pyannote[557].end 5358.50159375
transcript.pyannote[558].speaker SPEAKER_24
transcript.pyannote[558].start 5365.84221875
transcript.pyannote[558].end 5366.33159375
transcript.pyannote[559].speaker SPEAKER_24
transcript.pyannote[559].start 5366.63534375
transcript.pyannote[559].end 5368.77846875
transcript.pyannote[560].speaker SPEAKER_05
transcript.pyannote[560].start 5366.66909375
transcript.pyannote[560].end 5370.17909375
transcript.pyannote[561].speaker SPEAKER_24
transcript.pyannote[561].start 5370.55034375
transcript.pyannote[561].end 5372.49096875
transcript.pyannote[562].speaker SPEAKER_24
transcript.pyannote[562].start 5372.96346875
transcript.pyannote[562].end 5375.57909375
transcript.pyannote[563].speaker SPEAKER_24
transcript.pyannote[563].start 5376.10221875
transcript.pyannote[563].end 5378.22846875
transcript.pyannote[564].speaker SPEAKER_24
transcript.pyannote[564].start 5378.41409375
transcript.pyannote[564].end 5380.35471875
transcript.pyannote[565].speaker SPEAKER_05
transcript.pyannote[565].start 5380.32096875
transcript.pyannote[565].end 5383.10534375
transcript.pyannote[566].speaker SPEAKER_24
transcript.pyannote[566].start 5380.79346875
transcript.pyannote[566].end 5381.14784375
transcript.pyannote[567].speaker SPEAKER_05
transcript.pyannote[567].start 5384.16846875
transcript.pyannote[567].end 5386.48034375
transcript.pyannote[568].speaker SPEAKER_33
transcript.pyannote[568].start 5385.97409375
transcript.pyannote[568].end 5387.72909375
transcript.pyannote[569].speaker SPEAKER_05
transcript.pyannote[569].start 5386.98659375
transcript.pyannote[569].end 5388.47159375
transcript.pyannote[570].speaker SPEAKER_33
transcript.pyannote[570].start 5388.06659375
transcript.pyannote[570].end 5395.28909375
transcript.pyannote[571].speaker SPEAKER_05
transcript.pyannote[571].start 5395.42409375
transcript.pyannote[571].end 5396.58846875
transcript.pyannote[572].speaker SPEAKER_33
transcript.pyannote[572].start 5397.41534375
transcript.pyannote[572].end 5398.63034375
transcript.pyannote[573].speaker SPEAKER_05
transcript.pyannote[573].start 5398.25909375
transcript.pyannote[573].end 5400.30096875
transcript.pyannote[574].speaker SPEAKER_33
transcript.pyannote[574].start 5400.30096875
transcript.pyannote[574].end 5412.18096875
transcript.pyannote[575].speaker SPEAKER_05
transcript.pyannote[575].start 5410.52721875
transcript.pyannote[575].end 5433.57846875
transcript.pyannote[576].speaker SPEAKER_24
transcript.pyannote[576].start 5431.48596875
transcript.pyannote[576].end 5432.04284375
transcript.pyannote[577].speaker SPEAKER_24
transcript.pyannote[577].start 5433.12284375
transcript.pyannote[577].end 5440.02471875
transcript.pyannote[578].speaker SPEAKER_05
transcript.pyannote[578].start 5439.18096875
transcript.pyannote[578].end 5439.68721875
transcript.pyannote[579].speaker SPEAKER_22
transcript.pyannote[579].start 5439.68721875
transcript.pyannote[579].end 5439.75471875
transcript.pyannote[580].speaker SPEAKER_24
transcript.pyannote[580].start 5440.21034375
transcript.pyannote[580].end 5456.10659375
transcript.pyannote[581].speaker SPEAKER_00
transcript.pyannote[581].start 5445.39096875
transcript.pyannote[581].end 5445.82971875
transcript.pyannote[582].speaker SPEAKER_00
transcript.pyannote[582].start 5448.54659375
transcript.pyannote[582].end 5448.58034375
transcript.pyannote[583].speaker SPEAKER_22
transcript.pyannote[583].start 5448.58034375
transcript.pyannote[583].end 5448.91784375
transcript.pyannote[584].speaker SPEAKER_22
transcript.pyannote[584].start 5455.92096875
transcript.pyannote[584].end 5455.95471875
transcript.pyannote[585].speaker SPEAKER_05
transcript.pyannote[585].start 5455.95471875
transcript.pyannote[585].end 5456.51159375
transcript.pyannote[586].speaker SPEAKER_24
transcript.pyannote[586].start 5456.51159375
transcript.pyannote[586].end 5460.54471875
transcript.pyannote[587].speaker SPEAKER_05
transcript.pyannote[587].start 5457.99659375
transcript.pyannote[587].end 5516.41784375
transcript.pyannote[588].speaker SPEAKER_24
transcript.pyannote[588].start 5516.38409375
transcript.pyannote[588].end 5520.55221875
transcript.pyannote[589].speaker SPEAKER_05
transcript.pyannote[589].start 5516.90721875
transcript.pyannote[589].end 5516.97471875
transcript.pyannote[590].speaker SPEAKER_05
transcript.pyannote[590].start 5517.41346875
transcript.pyannote[590].end 5518.07159375
transcript.pyannote[591].speaker SPEAKER_05
transcript.pyannote[591].start 5519.13471875
transcript.pyannote[591].end 5519.72534375
transcript.pyannote[592].speaker SPEAKER_05
transcript.pyannote[592].start 5520.23159375
transcript.pyannote[592].end 5564.20784375
transcript.pyannote[593].speaker SPEAKER_24
transcript.pyannote[593].start 5564.74784375
transcript.pyannote[593].end 5565.50721875
transcript.pyannote[594].speaker SPEAKER_24
transcript.pyannote[594].start 5568.15659375
transcript.pyannote[594].end 5570.04659375
transcript.pyannote[595].speaker SPEAKER_05
transcript.pyannote[595].start 5569.99596875
transcript.pyannote[595].end 5571.44721875
transcript.pyannote[596].speaker SPEAKER_24
transcript.pyannote[596].start 5571.85221875
transcript.pyannote[596].end 5574.70409375
transcript.pyannote[597].speaker SPEAKER_05
transcript.pyannote[597].start 5572.22346875
transcript.pyannote[597].end 5576.98221875
transcript.pyannote[598].speaker SPEAKER_24
transcript.pyannote[598].start 5576.79659375
transcript.pyannote[598].end 5580.57659375
transcript.pyannote[599].speaker SPEAKER_05
transcript.pyannote[599].start 5579.64846875
transcript.pyannote[599].end 5582.68596875
transcript.pyannote[600].speaker SPEAKER_24
transcript.pyannote[600].start 5583.71534375
transcript.pyannote[600].end 5587.10721875
transcript.pyannote[601].speaker SPEAKER_05
transcript.pyannote[601].start 5588.40659375
transcript.pyannote[601].end 5589.40221875
transcript.pyannote[602].speaker SPEAKER_05
transcript.pyannote[602].start 5589.95909375
transcript.pyannote[602].end 5594.76846875
transcript.pyannote[603].speaker SPEAKER_24
transcript.pyannote[603].start 5590.04346875
transcript.pyannote[603].end 5590.16159375
transcript.pyannote[604].speaker SPEAKER_24
transcript.pyannote[604].start 5592.87846875
transcript.pyannote[604].end 5593.36784375
transcript.pyannote[605].speaker SPEAKER_24
transcript.pyannote[605].start 5595.78096875
transcript.pyannote[605].end 5597.18159375
transcript.pyannote[606].speaker SPEAKER_05
transcript.pyannote[606].start 5597.90721875
transcript.pyannote[606].end 5601.09659375
transcript.pyannote[607].speaker SPEAKER_24
transcript.pyannote[607].start 5600.01659375
transcript.pyannote[607].end 5601.02909375
transcript.pyannote[608].speaker SPEAKER_24
transcript.pyannote[608].start 5601.09659375
transcript.pyannote[608].end 5601.87284375
transcript.pyannote[609].speaker SPEAKER_05
transcript.pyannote[609].start 5602.22721875
transcript.pyannote[609].end 5603.49284375
transcript.pyannote[610].speaker SPEAKER_05
transcript.pyannote[610].start 5603.86409375
transcript.pyannote[610].end 5620.48596875
transcript.pyannote[611].speaker SPEAKER_05
transcript.pyannote[611].start 5621.95409375
transcript.pyannote[611].end 5622.30846875
transcript.pyannote[612].speaker SPEAKER_24
transcript.pyannote[612].start 5622.00471875
transcript.pyannote[612].end 5625.63284375
transcript.pyannote[613].speaker SPEAKER_05
transcript.pyannote[613].start 5626.42596875
transcript.pyannote[613].end 5626.79721875
transcript.pyannote[614].speaker SPEAKER_05
transcript.pyannote[614].start 5628.06284375
transcript.pyannote[614].end 5632.46721875
transcript.pyannote[615].speaker SPEAKER_05
transcript.pyannote[615].start 5632.93971875
transcript.pyannote[615].end 5638.67721875
transcript.pyannote[616].speaker SPEAKER_05
transcript.pyannote[616].start 5638.93034375
transcript.pyannote[616].end 5683.96971875
transcript.pyannote[617].speaker SPEAKER_24
transcript.pyannote[617].start 5683.96971875
transcript.pyannote[617].end 5692.08659375
transcript.pyannote[618].speaker SPEAKER_05
transcript.pyannote[618].start 5686.06221875
transcript.pyannote[618].end 5686.45034375
transcript.pyannote[619].speaker SPEAKER_05
transcript.pyannote[619].start 5691.68159375
transcript.pyannote[619].end 5692.94721875
transcript.pyannote[620].speaker SPEAKER_24
transcript.pyannote[620].start 5693.20034375
transcript.pyannote[620].end 5699.37659375
transcript.pyannote[621].speaker SPEAKER_05
transcript.pyannote[621].start 5699.84909375
transcript.pyannote[621].end 5701.36784375
transcript.pyannote[622].speaker SPEAKER_24
transcript.pyannote[622].start 5702.04284375
transcript.pyannote[622].end 5740.61909375
transcript.pyannote[623].speaker SPEAKER_22
transcript.pyannote[623].start 5714.44596875
transcript.pyannote[623].end 5714.73284375
transcript.pyannote[624].speaker SPEAKER_22
transcript.pyannote[624].start 5723.15346875
transcript.pyannote[624].end 5723.32221875
transcript.pyannote[625].speaker SPEAKER_24
transcript.pyannote[625].start 5741.10846875
transcript.pyannote[625].end 5749.17471875
transcript.pyannote[626].speaker SPEAKER_05
transcript.pyannote[626].start 5749.17471875
transcript.pyannote[626].end 5755.58721875
transcript.pyannote[627].speaker SPEAKER_24
transcript.pyannote[627].start 5751.25034375
transcript.pyannote[627].end 5751.75659375
transcript.pyannote[628].speaker SPEAKER_24
transcript.pyannote[628].start 5751.77346875
transcript.pyannote[628].end 5751.80721875
transcript.pyannote[629].speaker SPEAKER_24
transcript.pyannote[629].start 5755.06409375
transcript.pyannote[629].end 5805.45284375
transcript.pyannote[630].speaker SPEAKER_05
transcript.pyannote[630].start 5805.79034375
transcript.pyannote[630].end 5809.87409375
transcript.pyannote[631].speaker SPEAKER_05
transcript.pyannote[631].start 5809.97534375
transcript.pyannote[631].end 5836.78971875
transcript.pyannote[632].speaker SPEAKER_29
transcript.pyannote[632].start 5826.85034375
transcript.pyannote[632].end 5826.96846875
transcript.pyannote[633].speaker SPEAKER_00
transcript.pyannote[633].start 5826.96846875
transcript.pyannote[633].end 5827.71096875
transcript.pyannote[634].speaker SPEAKER_06
transcript.pyannote[634].start 5835.47346875
transcript.pyannote[634].end 5836.18221875
transcript.pyannote[635].speaker SPEAKER_05
transcript.pyannote[635].start 5838.98346875
transcript.pyannote[635].end 5839.00034375
transcript.pyannote[636].speaker SPEAKER_06
transcript.pyannote[636].start 5839.00034375
transcript.pyannote[636].end 5843.69159375
transcript.pyannote[637].speaker SPEAKER_25
transcript.pyannote[637].start 5852.88846875
transcript.pyannote[637].end 5853.64784375
transcript.pyannote[638].speaker SPEAKER_25
transcript.pyannote[638].start 5853.83346875
transcript.pyannote[638].end 5854.67721875
transcript.pyannote[639].speaker SPEAKER_06
transcript.pyannote[639].start 5855.23409375
transcript.pyannote[639].end 5856.21284375
transcript.pyannote[640].speaker SPEAKER_25
transcript.pyannote[640].start 5861.19096875
transcript.pyannote[640].end 5863.48596875
transcript.pyannote[641].speaker SPEAKER_25
transcript.pyannote[641].start 5864.11034375
transcript.pyannote[641].end 5904.91409375
transcript.pyannote[642].speaker SPEAKER_24
transcript.pyannote[642].start 5904.91409375
transcript.pyannote[642].end 5917.73909375
transcript.pyannote[643].speaker SPEAKER_25
transcript.pyannote[643].start 5917.73909375
transcript.pyannote[643].end 5924.13471875
transcript.pyannote[644].speaker SPEAKER_24
transcript.pyannote[644].start 5924.20221875
transcript.pyannote[644].end 5929.48409375
transcript.pyannote[645].speaker SPEAKER_25
transcript.pyannote[645].start 5929.48409375
transcript.pyannote[645].end 5937.92159375
transcript.pyannote[646].speaker SPEAKER_24
transcript.pyannote[646].start 5937.38159375
transcript.pyannote[646].end 5937.80346875
transcript.pyannote[647].speaker SPEAKER_24
transcript.pyannote[647].start 5937.92159375
transcript.pyannote[647].end 5938.49534375
transcript.pyannote[648].speaker SPEAKER_24
transcript.pyannote[648].start 5938.61346875
transcript.pyannote[648].end 5945.68409375
transcript.pyannote[649].speaker SPEAKER_24
transcript.pyannote[649].start 5946.05534375
transcript.pyannote[649].end 5947.33784375
transcript.pyannote[650].speaker SPEAKER_25
transcript.pyannote[650].start 5946.51096875
transcript.pyannote[650].end 5947.96221875
transcript.pyannote[651].speaker SPEAKER_24
transcript.pyannote[651].start 5947.43909375
transcript.pyannote[651].end 5950.72971875
transcript.pyannote[652].speaker SPEAKER_25
transcript.pyannote[652].start 5950.81409375
transcript.pyannote[652].end 5951.96159375
transcript.pyannote[653].speaker SPEAKER_25
transcript.pyannote[653].start 5953.09221875
transcript.pyannote[653].end 5970.08534375
transcript.pyannote[654].speaker SPEAKER_24
transcript.pyannote[654].start 5970.60846875
transcript.pyannote[654].end 5970.91221875
transcript.pyannote[655].speaker SPEAKER_24
transcript.pyannote[655].start 5971.48596875
transcript.pyannote[655].end 5976.64971875
transcript.pyannote[656].speaker SPEAKER_25
transcript.pyannote[656].start 5974.00034375
transcript.pyannote[656].end 5974.72596875
transcript.pyannote[657].speaker SPEAKER_25
transcript.pyannote[657].start 5976.64971875
transcript.pyannote[657].end 5977.94909375
transcript.pyannote[658].speaker SPEAKER_24
transcript.pyannote[658].start 5976.66659375
transcript.pyannote[658].end 5976.97034375
transcript.pyannote[659].speaker SPEAKER_25
transcript.pyannote[659].start 5978.32034375
transcript.pyannote[659].end 6003.16034375
transcript.pyannote[660].speaker SPEAKER_24
transcript.pyannote[660].start 6004.34159375
transcript.pyannote[660].end 6006.94034375
transcript.pyannote[661].speaker SPEAKER_25
transcript.pyannote[661].start 6006.48471875
transcript.pyannote[661].end 6008.32409375
transcript.pyannote[662].speaker SPEAKER_24
transcript.pyannote[662].start 6009.23534375
transcript.pyannote[662].end 6009.25221875
transcript.pyannote[663].speaker SPEAKER_25
transcript.pyannote[663].start 6009.25221875
transcript.pyannote[663].end 6010.73721875
transcript.pyannote[664].speaker SPEAKER_24
transcript.pyannote[664].start 6010.19721875
transcript.pyannote[664].end 6010.65284375
transcript.pyannote[665].speaker SPEAKER_24
transcript.pyannote[665].start 6010.73721875
transcript.pyannote[665].end 6010.75409375
transcript.pyannote[666].speaker SPEAKER_25
transcript.pyannote[666].start 6010.75409375
transcript.pyannote[666].end 6012.35721875
transcript.pyannote[667].speaker SPEAKER_24
transcript.pyannote[667].start 6011.81721875
transcript.pyannote[667].end 6029.78909375
transcript.pyannote[668].speaker SPEAKER_00
transcript.pyannote[668].start 6019.15784375
transcript.pyannote[668].end 6019.46159375
transcript.pyannote[669].speaker SPEAKER_25
transcript.pyannote[669].start 6022.38096875
transcript.pyannote[669].end 6022.81971875
transcript.pyannote[670].speaker SPEAKER_25
transcript.pyannote[670].start 6029.45159375
transcript.pyannote[670].end 6029.73846875
transcript.pyannote[671].speaker SPEAKER_25
transcript.pyannote[671].start 6029.78909375
transcript.pyannote[671].end 6029.95784375
transcript.pyannote[672].speaker SPEAKER_24
transcript.pyannote[672].start 6029.95784375
transcript.pyannote[672].end 6030.02534375
transcript.pyannote[673].speaker SPEAKER_25
transcript.pyannote[673].start 6030.02534375
transcript.pyannote[673].end 6030.10971875
transcript.pyannote[674].speaker SPEAKER_24
transcript.pyannote[674].start 6030.10971875
transcript.pyannote[674].end 6030.31221875
transcript.pyannote[675].speaker SPEAKER_25
transcript.pyannote[675].start 6030.31221875
transcript.pyannote[675].end 6030.51471875
transcript.pyannote[676].speaker SPEAKER_24
transcript.pyannote[676].start 6030.51471875
transcript.pyannote[676].end 6037.45034375
transcript.pyannote[677].speaker SPEAKER_25
transcript.pyannote[677].start 6030.59909375
transcript.pyannote[677].end 6032.18534375
transcript.pyannote[678].speaker SPEAKER_25
transcript.pyannote[678].start 6034.59846875
transcript.pyannote[678].end 6035.00346875
transcript.pyannote[679].speaker SPEAKER_25
transcript.pyannote[679].start 6037.45034375
transcript.pyannote[679].end 6037.50096875
transcript.pyannote[680].speaker SPEAKER_24
transcript.pyannote[680].start 6037.50096875
transcript.pyannote[680].end 6037.61909375
transcript.pyannote[681].speaker SPEAKER_25
transcript.pyannote[681].start 6037.61909375
transcript.pyannote[681].end 6037.65284375
transcript.pyannote[682].speaker SPEAKER_24
transcript.pyannote[682].start 6037.65284375
transcript.pyannote[682].end 6037.99034375
transcript.pyannote[683].speaker SPEAKER_25
transcript.pyannote[683].start 6037.99034375
transcript.pyannote[683].end 6042.34409375
transcript.pyannote[684].speaker SPEAKER_24
transcript.pyannote[684].start 6041.34846875
transcript.pyannote[684].end 6042.96846875
transcript.pyannote[685].speaker SPEAKER_25
transcript.pyannote[685].start 6042.96846875
transcript.pyannote[685].end 6050.00534375
transcript.pyannote[686].speaker SPEAKER_24
transcript.pyannote[686].start 6049.87034375
transcript.pyannote[686].end 6050.46096875
transcript.pyannote[687].speaker SPEAKER_25
transcript.pyannote[687].start 6050.03909375
transcript.pyannote[687].end 6051.55784375
transcript.pyannote[688].speaker SPEAKER_24
transcript.pyannote[688].start 6051.13596875
transcript.pyannote[688].end 6053.68409375
transcript.pyannote[689].speaker SPEAKER_25
transcript.pyannote[689].start 6052.38471875
transcript.pyannote[689].end 6095.02784375
transcript.pyannote[690].speaker SPEAKER_24
transcript.pyannote[690].start 6055.67534375
transcript.pyannote[690].end 6055.91159375
transcript.pyannote[691].speaker SPEAKER_24
transcript.pyannote[691].start 6095.02784375
transcript.pyannote[691].end 6105.35534375
transcript.pyannote[692].speaker SPEAKER_24
transcript.pyannote[692].start 6105.64221875
transcript.pyannote[692].end 6118.51784375
transcript.pyannote[693].speaker SPEAKER_25
transcript.pyannote[693].start 6115.39596875
transcript.pyannote[693].end 6116.23971875
transcript.pyannote[694].speaker SPEAKER_24
transcript.pyannote[694].start 6118.58534375
transcript.pyannote[694].end 6118.65284375
transcript.pyannote[695].speaker SPEAKER_25
transcript.pyannote[695].start 6118.65284375
transcript.pyannote[695].end 6119.73284375
transcript.pyannote[696].speaker SPEAKER_24
transcript.pyannote[696].start 6119.31096875
transcript.pyannote[696].end 6119.59784375
transcript.pyannote[697].speaker SPEAKER_24
transcript.pyannote[697].start 6119.73284375
transcript.pyannote[697].end 6119.74971875
transcript.pyannote[698].speaker SPEAKER_25
transcript.pyannote[698].start 6119.74971875
transcript.pyannote[698].end 6119.83409375
transcript.pyannote[699].speaker SPEAKER_24
transcript.pyannote[699].start 6119.83409375
transcript.pyannote[699].end 6132.16971875
transcript.pyannote[700].speaker SPEAKER_25
transcript.pyannote[700].start 6120.12096875
transcript.pyannote[700].end 6120.62721875
transcript.pyannote[701].speaker SPEAKER_24
transcript.pyannote[701].start 6132.49034375
transcript.pyannote[701].end 6136.43909375
transcript.pyannote[702].speaker SPEAKER_25
transcript.pyannote[702].start 6136.99596875
transcript.pyannote[702].end 6138.97034375
transcript.pyannote[703].speaker SPEAKER_25
transcript.pyannote[703].start 6139.76346875
transcript.pyannote[703].end 6181.30971875
transcript.pyannote[704].speaker SPEAKER_24
transcript.pyannote[704].start 6166.18971875
transcript.pyannote[704].end 6167.52284375
transcript.pyannote[705].speaker SPEAKER_24
transcript.pyannote[705].start 6180.80346875
transcript.pyannote[705].end 6199.77096875
transcript.pyannote[706].speaker SPEAKER_25
transcript.pyannote[706].start 6194.33721875
transcript.pyannote[706].end 6194.92784375
transcript.pyannote[707].speaker SPEAKER_25
transcript.pyannote[707].start 6199.77096875
transcript.pyannote[707].end 6202.16721875
transcript.pyannote[708].speaker SPEAKER_24
transcript.pyannote[708].start 6202.16721875
transcript.pyannote[708].end 6203.14596875
transcript.pyannote[709].speaker SPEAKER_25
transcript.pyannote[709].start 6202.43721875
transcript.pyannote[709].end 6207.98909375
transcript.pyannote[710].speaker SPEAKER_24
transcript.pyannote[710].start 6205.47471875
transcript.pyannote[710].end 6205.60971875
transcript.pyannote[711].speaker SPEAKER_25
transcript.pyannote[711].start 6208.25909375
transcript.pyannote[711].end 6219.73409375
transcript.pyannote[712].speaker SPEAKER_25
transcript.pyannote[712].start 6219.90284375
transcript.pyannote[712].end 6239.88284375
transcript.pyannote[713].speaker SPEAKER_25
transcript.pyannote[713].start 6240.25409375
transcript.pyannote[713].end 6315.87096875
transcript.pyannote[714].speaker SPEAKER_24
transcript.pyannote[714].start 6317.23784375
transcript.pyannote[714].end 6347.66346875
transcript.pyannote[715].speaker SPEAKER_00
transcript.pyannote[715].start 6344.08596875
transcript.pyannote[715].end 6344.64284375
transcript.pyannote[716].speaker SPEAKER_00
transcript.pyannote[716].start 6347.02221875
transcript.pyannote[716].end 6347.14034375
transcript.pyannote[717].speaker SPEAKER_25
transcript.pyannote[717].start 6347.14034375
transcript.pyannote[717].end 6347.44409375
transcript.pyannote[718].speaker SPEAKER_00
transcript.pyannote[718].start 6347.44409375
transcript.pyannote[718].end 6347.46096875
transcript.pyannote[719].speaker SPEAKER_24
transcript.pyannote[719].start 6347.76471875
transcript.pyannote[719].end 6350.83596875
transcript.pyannote[720].speaker SPEAKER_24
transcript.pyannote[720].start 6351.25784375
transcript.pyannote[720].end 6360.35346875
transcript.pyannote[721].speaker SPEAKER_25
transcript.pyannote[721].start 6360.35346875
transcript.pyannote[721].end 6397.96784375
transcript.pyannote[722].speaker SPEAKER_24
transcript.pyannote[722].start 6360.37034375
transcript.pyannote[722].end 6362.39534375
transcript.pyannote[723].speaker SPEAKER_24
transcript.pyannote[723].start 6363.27284375
transcript.pyannote[723].end 6363.34034375
transcript.pyannote[724].speaker SPEAKER_29
transcript.pyannote[724].start 6373.46534375
transcript.pyannote[724].end 6373.88721875
transcript.pyannote[725].speaker SPEAKER_24
transcript.pyannote[725].start 6395.06534375
transcript.pyannote[725].end 6395.31846875
transcript.pyannote[726].speaker SPEAKER_24
transcript.pyannote[726].start 6396.26346875
transcript.pyannote[726].end 6398.49096875
transcript.pyannote[727].speaker SPEAKER_25
transcript.pyannote[727].start 6398.08596875
transcript.pyannote[727].end 6467.89784375
transcript.pyannote[728].speaker SPEAKER_25
transcript.pyannote[728].start 6468.58971875
transcript.pyannote[728].end 6469.68659375
transcript.pyannote[729].speaker SPEAKER_25
transcript.pyannote[729].start 6469.97346875
transcript.pyannote[729].end 6474.76596875
transcript.pyannote[730].speaker SPEAKER_25
transcript.pyannote[730].start 6474.91784375
transcript.pyannote[730].end 6474.96846875
transcript.pyannote[731].speaker SPEAKER_24
transcript.pyannote[731].start 6474.96846875
transcript.pyannote[731].end 6501.59721875
transcript.pyannote[732].speaker SPEAKER_25
transcript.pyannote[732].start 6475.03596875
transcript.pyannote[732].end 6475.32284375
transcript.pyannote[733].speaker SPEAKER_25
transcript.pyannote[733].start 6483.45659375
transcript.pyannote[733].end 6484.23284375
transcript.pyannote[734].speaker SPEAKER_25
transcript.pyannote[734].start 6501.59721875
transcript.pyannote[734].end 6540.79784375
transcript.pyannote[735].speaker SPEAKER_24
transcript.pyannote[735].start 6501.64784375
transcript.pyannote[735].end 6502.84596875
transcript.pyannote[736].speaker SPEAKER_29
transcript.pyannote[736].start 6507.53721875
transcript.pyannote[736].end 6507.55409375
transcript.pyannote[737].speaker SPEAKER_24
transcript.pyannote[737].start 6507.55409375
transcript.pyannote[737].end 6508.33034375
transcript.pyannote[738].speaker SPEAKER_24
transcript.pyannote[738].start 6512.78534375
transcript.pyannote[738].end 6512.80221875
transcript.pyannote[739].speaker SPEAKER_29
transcript.pyannote[739].start 6512.80221875
transcript.pyannote[739].end 6514.03409375
transcript.pyannote[740].speaker SPEAKER_24
transcript.pyannote[740].start 6514.03409375
transcript.pyannote[740].end 6514.96221875
transcript.pyannote[741].speaker SPEAKER_29
transcript.pyannote[741].start 6514.96221875
transcript.pyannote[741].end 6515.13096875
transcript.pyannote[742].speaker SPEAKER_24
transcript.pyannote[742].start 6515.13096875
transcript.pyannote[742].end 6515.26596875
transcript.pyannote[743].speaker SPEAKER_24
transcript.pyannote[743].start 6541.32096875
transcript.pyannote[743].end 6541.60784375
transcript.pyannote[744].speaker SPEAKER_25
transcript.pyannote[744].start 6541.60784375
transcript.pyannote[744].end 6542.23221875
transcript.pyannote[745].speaker SPEAKER_24
transcript.pyannote[745].start 6541.72596875
transcript.pyannote[745].end 6555.04034375
transcript.pyannote[746].speaker SPEAKER_24
transcript.pyannote[746].start 6555.51284375
transcript.pyannote[746].end 6564.15284375
transcript.pyannote[747].speaker SPEAKER_24
transcript.pyannote[747].start 6565.01346875
transcript.pyannote[747].end 6586.96784375
transcript.pyannote[748].speaker SPEAKER_25
transcript.pyannote[748].start 6570.63284375
transcript.pyannote[748].end 6571.12221875
transcript.pyannote[749].speaker SPEAKER_25
transcript.pyannote[749].start 6572.30346875
transcript.pyannote[749].end 6574.49721875
transcript.pyannote[750].speaker SPEAKER_25
transcript.pyannote[750].start 6586.96784375
transcript.pyannote[750].end 6592.97534375
transcript.pyannote[751].speaker SPEAKER_24
transcript.pyannote[751].start 6589.09409375
transcript.pyannote[751].end 6589.97159375
transcript.pyannote[752].speaker SPEAKER_25
transcript.pyannote[752].start 6593.68409375
transcript.pyannote[752].end 6607.21784375
transcript.pyannote[753].speaker SPEAKER_24
transcript.pyannote[753].start 6606.15471875
transcript.pyannote[753].end 6609.41159375
transcript.pyannote[754].speaker SPEAKER_25
transcript.pyannote[754].start 6608.88846875
transcript.pyannote[754].end 6612.90471875
transcript.pyannote[755].speaker SPEAKER_24
transcript.pyannote[755].start 6612.76971875
transcript.pyannote[755].end 6612.80346875
transcript.pyannote[756].speaker SPEAKER_29
transcript.pyannote[756].start 6612.80346875
transcript.pyannote[756].end 6613.12409375
transcript.pyannote[757].speaker SPEAKER_25
transcript.pyannote[757].start 6613.00596875
transcript.pyannote[757].end 6621.44346875
transcript.pyannote[758].speaker SPEAKER_25
transcript.pyannote[758].start 6622.59096875
transcript.pyannote[758].end 6632.88471875
transcript.pyannote[759].speaker SPEAKER_24
transcript.pyannote[759].start 6632.88471875
transcript.pyannote[759].end 6645.82784375
transcript.pyannote[760].speaker SPEAKER_25
transcript.pyannote[760].start 6636.19221875
transcript.pyannote[760].end 6636.42846875
transcript.pyannote[761].speaker SPEAKER_29
transcript.pyannote[761].start 6636.42846875
transcript.pyannote[761].end 6636.44534375
transcript.pyannote[762].speaker SPEAKER_24
transcript.pyannote[762].start 6645.84471875
transcript.pyannote[762].end 6645.86159375
transcript.pyannote[763].speaker SPEAKER_25
transcript.pyannote[763].start 6645.86159375
transcript.pyannote[763].end 6663.73221875
transcript.pyannote[764].speaker SPEAKER_25
transcript.pyannote[764].start 6664.06971875
transcript.pyannote[764].end 6673.46909375
transcript.pyannote[765].speaker SPEAKER_25
transcript.pyannote[765].start 6674.04284375
transcript.pyannote[765].end 6677.58659375
transcript.pyannote[766].speaker SPEAKER_25
transcript.pyannote[766].start 6677.87346875
transcript.pyannote[766].end 6680.08409375
transcript.pyannote[767].speaker SPEAKER_24
transcript.pyannote[767].start 6680.18534375
transcript.pyannote[767].end 6681.68721875
transcript.pyannote[768].speaker SPEAKER_25
transcript.pyannote[768].start 6681.04596875
transcript.pyannote[768].end 6684.53909375
transcript.pyannote[769].speaker SPEAKER_24
transcript.pyannote[769].start 6684.53909375
transcript.pyannote[769].end 6684.79221875
transcript.pyannote[770].speaker SPEAKER_25
transcript.pyannote[770].start 6684.79221875
transcript.pyannote[770].end 6684.89346875
transcript.pyannote[771].speaker SPEAKER_24
transcript.pyannote[771].start 6684.89346875
transcript.pyannote[771].end 6685.12971875
transcript.pyannote[772].speaker SPEAKER_25
transcript.pyannote[772].start 6685.12971875
transcript.pyannote[772].end 6685.19721875
transcript.pyannote[773].speaker SPEAKER_24
transcript.pyannote[773].start 6685.46721875
transcript.pyannote[773].end 6710.10471875
transcript.pyannote[774].speaker SPEAKER_00
transcript.pyannote[774].start 6700.33409375
transcript.pyannote[774].end 6700.46909375
transcript.pyannote[775].speaker SPEAKER_24
transcript.pyannote[775].start 6710.64471875
transcript.pyannote[775].end 6718.57596875
transcript.pyannote[776].speaker SPEAKER_24
transcript.pyannote[776].start 6718.91346875
transcript.pyannote[776].end 6720.38159375
transcript.pyannote[777].speaker SPEAKER_24
transcript.pyannote[777].start 6720.71909375
transcript.pyannote[777].end 6726.57471875
transcript.pyannote[778].speaker SPEAKER_24
transcript.pyannote[778].start 6727.58721875
transcript.pyannote[778].end 6736.71659375
transcript.pyannote[779].speaker SPEAKER_24
transcript.pyannote[779].start 6737.17221875
transcript.pyannote[779].end 6742.16721875
transcript.pyannote[780].speaker SPEAKER_24
transcript.pyannote[780].start 6742.92659375
transcript.pyannote[780].end 6761.11784375
transcript.pyannote[781].speaker SPEAKER_25
transcript.pyannote[781].start 6761.11784375
transcript.pyannote[781].end 6761.13471875
transcript.pyannote[782].speaker SPEAKER_25
transcript.pyannote[782].start 6761.30346875
transcript.pyannote[782].end 6788.96159375
transcript.pyannote[783].speaker SPEAKER_24
transcript.pyannote[783].start 6777.79034375
transcript.pyannote[783].end 6782.36346875
transcript.pyannote[784].speaker SPEAKER_29
transcript.pyannote[784].start 6782.36346875
transcript.pyannote[784].end 6782.38034375
transcript.pyannote[785].speaker SPEAKER_25
transcript.pyannote[785].start 6789.14721875
transcript.pyannote[785].end 6800.31846875
transcript.pyannote[786].speaker SPEAKER_24
transcript.pyannote[786].start 6800.31846875
transcript.pyannote[786].end 6800.33534375
transcript.pyannote[787].speaker SPEAKER_25
transcript.pyannote[787].start 6800.85846875
transcript.pyannote[787].end 6801.02721875
transcript.pyannote[788].speaker SPEAKER_24
transcript.pyannote[788].start 6801.02721875
transcript.pyannote[788].end 6811.86096875
transcript.pyannote[789].speaker SPEAKER_24
transcript.pyannote[789].start 6812.68784375
transcript.pyannote[789].end 6828.04409375
transcript.pyannote[790].speaker SPEAKER_24
transcript.pyannote[790].start 6828.19596875
transcript.pyannote[790].end 6830.47409375
transcript.pyannote[791].speaker SPEAKER_24
transcript.pyannote[791].start 6831.04784375
transcript.pyannote[791].end 6831.46971875
transcript.pyannote[792].speaker SPEAKER_24
transcript.pyannote[792].start 6831.90846875
transcript.pyannote[792].end 6832.41471875
transcript.pyannote[793].speaker SPEAKER_24
transcript.pyannote[793].start 6832.81971875
transcript.pyannote[793].end 6848.96909375
transcript.pyannote[794].speaker SPEAKER_25
transcript.pyannote[794].start 6848.96909375
transcript.pyannote[794].end 6877.40346875
transcript.pyannote[795].speaker SPEAKER_24
transcript.pyannote[795].start 6875.74971875
transcript.pyannote[795].end 6876.15471875
transcript.pyannote[796].speaker SPEAKER_24
transcript.pyannote[796].start 6877.55534375
transcript.pyannote[796].end 6883.12409375
transcript.pyannote[797].speaker SPEAKER_25
transcript.pyannote[797].start 6883.12409375
transcript.pyannote[797].end 6883.88346875
transcript.pyannote[798].speaker SPEAKER_06
transcript.pyannote[798].start 6884.99721875
transcript.pyannote[798].end 6887.03909375
transcript.pyannote[799].speaker SPEAKER_06
transcript.pyannote[799].start 6887.12346875
transcript.pyannote[799].end 6889.89096875
transcript.pyannote[800].speaker SPEAKER_06
transcript.pyannote[800].start 6890.16096875
transcript.pyannote[800].end 6894.22784375
transcript.pyannote[801].speaker SPEAKER_02
transcript.pyannote[801].start 6902.63159375
transcript.pyannote[801].end 6903.62721875
transcript.pyannote[802].speaker SPEAKER_02
transcript.pyannote[802].start 6906.34409375
transcript.pyannote[802].end 6909.97221875
transcript.pyannote[803].speaker SPEAKER_06
transcript.pyannote[803].start 6909.38159375
transcript.pyannote[803].end 6910.56284375
transcript.pyannote[804].speaker SPEAKER_02
transcript.pyannote[804].start 6916.99221875
transcript.pyannote[804].end 6923.84346875
transcript.pyannote[805].speaker SPEAKER_02
transcript.pyannote[805].start 6924.83909375
transcript.pyannote[805].end 6925.41284375
transcript.pyannote[806].speaker SPEAKER_24
transcript.pyannote[806].start 6926.03721875
transcript.pyannote[806].end 6926.83034375
transcript.pyannote[807].speaker SPEAKER_24
transcript.pyannote[807].start 6928.68659375
transcript.pyannote[807].end 6929.15909375
transcript.pyannote[808].speaker SPEAKER_02
transcript.pyannote[808].start 6929.51346875
transcript.pyannote[808].end 6930.01971875
transcript.pyannote[809].speaker SPEAKER_24
transcript.pyannote[809].start 6929.80034375
transcript.pyannote[809].end 6930.27284375
transcript.pyannote[810].speaker SPEAKER_02
transcript.pyannote[810].start 6930.27284375
transcript.pyannote[810].end 6930.30659375
transcript.pyannote[811].speaker SPEAKER_02
transcript.pyannote[811].start 6930.45846875
transcript.pyannote[811].end 6931.06596875
transcript.pyannote[812].speaker SPEAKER_02
transcript.pyannote[812].start 6931.62284375
transcript.pyannote[812].end 6934.64346875
transcript.pyannote[813].speaker SPEAKER_02
transcript.pyannote[813].start 6935.04846875
transcript.pyannote[813].end 6936.17909375
transcript.pyannote[814].speaker SPEAKER_24
transcript.pyannote[814].start 6937.27596875
transcript.pyannote[814].end 6943.33409375
transcript.pyannote[815].speaker SPEAKER_24
transcript.pyannote[815].start 6943.97534375
transcript.pyannote[815].end 6945.05534375
transcript.pyannote[816].speaker SPEAKER_02
transcript.pyannote[816].start 6945.61221875
transcript.pyannote[816].end 6946.55721875
transcript.pyannote[817].speaker SPEAKER_24
transcript.pyannote[817].start 6946.52346875
transcript.pyannote[817].end 6947.97471875
transcript.pyannote[818].speaker SPEAKER_02
transcript.pyannote[818].start 6946.82721875
transcript.pyannote[818].end 6949.89846875
transcript.pyannote[819].speaker SPEAKER_02
transcript.pyannote[819].start 6950.33721875
transcript.pyannote[819].end 6954.35346875
transcript.pyannote[820].speaker SPEAKER_02
transcript.pyannote[820].start 6954.47159375
transcript.pyannote[820].end 6955.33221875
transcript.pyannote[821].speaker SPEAKER_24
transcript.pyannote[821].start 6955.75409375
transcript.pyannote[821].end 6963.16221875
transcript.pyannote[822].speaker SPEAKER_24
transcript.pyannote[822].start 6963.71909375
transcript.pyannote[822].end 6967.76909375
transcript.pyannote[823].speaker SPEAKER_02
transcript.pyannote[823].start 6964.51221875
transcript.pyannote[823].end 6966.28409375
transcript.pyannote[824].speaker SPEAKER_02
transcript.pyannote[824].start 6967.90409375
transcript.pyannote[824].end 6969.54096875
transcript.pyannote[825].speaker SPEAKER_02
transcript.pyannote[825].start 6970.08096875
transcript.pyannote[825].end 6972.07221875
transcript.pyannote[826].speaker SPEAKER_24
transcript.pyannote[826].start 6971.68409375
transcript.pyannote[826].end 6974.63721875
transcript.pyannote[827].speaker SPEAKER_24
transcript.pyannote[827].start 6975.16034375
transcript.pyannote[827].end 6977.25284375
transcript.pyannote[828].speaker SPEAKER_02
transcript.pyannote[828].start 6977.25284375
transcript.pyannote[828].end 6977.60721875
transcript.pyannote[829].speaker SPEAKER_24
transcript.pyannote[829].start 6977.60721875
transcript.pyannote[829].end 6982.48409375
transcript.pyannote[830].speaker SPEAKER_02
transcript.pyannote[830].start 6978.06284375
transcript.pyannote[830].end 6978.26534375
transcript.pyannote[831].speaker SPEAKER_02
transcript.pyannote[831].start 6980.99909375
transcript.pyannote[831].end 7000.92846875
transcript.pyannote[832].speaker SPEAKER_24
transcript.pyannote[832].start 6983.24346875
transcript.pyannote[832].end 6985.03221875
transcript.pyannote[833].speaker SPEAKER_24
transcript.pyannote[833].start 6999.44346875
transcript.pyannote[833].end 7003.49346875
transcript.pyannote[834].speaker SPEAKER_24
transcript.pyannote[834].start 7003.59471875
transcript.pyannote[834].end 7005.80534375
transcript.pyannote[835].speaker SPEAKER_24
transcript.pyannote[835].start 7006.27784375
transcript.pyannote[835].end 7011.37409375
transcript.pyannote[836].speaker SPEAKER_02
transcript.pyannote[836].start 7010.88471875
transcript.pyannote[836].end 7012.15034375
transcript.pyannote[837].speaker SPEAKER_24
transcript.pyannote[837].start 7012.62284375
transcript.pyannote[837].end 7013.09534375
transcript.pyannote[838].speaker SPEAKER_24
transcript.pyannote[838].start 7013.70284375
transcript.pyannote[838].end 7015.30596875
transcript.pyannote[839].speaker SPEAKER_24
transcript.pyannote[839].start 7016.13284375
transcript.pyannote[839].end 7022.41034375
transcript.pyannote[840].speaker SPEAKER_02
transcript.pyannote[840].start 7016.68971875
transcript.pyannote[840].end 7018.73159375
transcript.pyannote[841].speaker SPEAKER_24
transcript.pyannote[841].start 7022.59596875
transcript.pyannote[841].end 7026.07221875
transcript.pyannote[842].speaker SPEAKER_02
transcript.pyannote[842].start 7024.68846875
transcript.pyannote[842].end 7045.61346875
transcript.pyannote[843].speaker SPEAKER_24
transcript.pyannote[843].start 7047.19971875
transcript.pyannote[843].end 7048.65096875
transcript.pyannote[844].speaker SPEAKER_02
transcript.pyannote[844].start 7048.48221875
transcript.pyannote[844].end 7063.66971875
transcript.pyannote[845].speaker SPEAKER_02
transcript.pyannote[845].start 7069.96409375
transcript.pyannote[845].end 7070.95971875
transcript.pyannote[846].speaker SPEAKER_13
transcript.pyannote[846].start 7073.15346875
transcript.pyannote[846].end 7079.73471875
transcript.pyannote[847].speaker SPEAKER_13
transcript.pyannote[847].start 7079.97096875
transcript.pyannote[847].end 7083.34596875
transcript.pyannote[848].speaker SPEAKER_13
transcript.pyannote[848].start 7083.83534375
transcript.pyannote[848].end 7086.78846875
transcript.pyannote[849].speaker SPEAKER_13
transcript.pyannote[849].start 7087.14284375
transcript.pyannote[849].end 7088.27346875
transcript.pyannote[850].speaker SPEAKER_13
transcript.pyannote[850].start 7088.72909375
transcript.pyannote[850].end 7095.58034375
transcript.pyannote[851].speaker SPEAKER_02
transcript.pyannote[851].start 7094.80409375
transcript.pyannote[851].end 7095.98534375
transcript.pyannote[852].speaker SPEAKER_13
transcript.pyannote[852].start 7096.69409375
transcript.pyannote[852].end 7100.57534375
transcript.pyannote[853].speaker SPEAKER_02
transcript.pyannote[853].start 7100.98034375
transcript.pyannote[853].end 7103.51159375
transcript.pyannote[854].speaker SPEAKER_24
transcript.pyannote[854].start 7102.48221875
transcript.pyannote[854].end 7125.02721875
transcript.pyannote[855].speaker SPEAKER_02
transcript.pyannote[855].start 7104.08534375
transcript.pyannote[855].end 7104.64221875
transcript.pyannote[856].speaker SPEAKER_24
transcript.pyannote[856].start 7125.82034375
transcript.pyannote[856].end 7128.72284375
transcript.pyannote[857].speaker SPEAKER_02
transcript.pyannote[857].start 7127.77784375
transcript.pyannote[857].end 7131.96284375
transcript.pyannote[858].speaker SPEAKER_24
transcript.pyannote[858].start 7131.96284375
transcript.pyannote[858].end 7144.02846875
transcript.pyannote[859].speaker SPEAKER_02
transcript.pyannote[859].start 7144.02846875
transcript.pyannote[859].end 7165.79721875
transcript.pyannote[860].speaker SPEAKER_24
transcript.pyannote[860].start 7148.23034375
transcript.pyannote[860].end 7149.29346875
transcript.pyannote[861].speaker SPEAKER_24
transcript.pyannote[861].start 7165.79721875
transcript.pyannote[861].end 7166.60721875
transcript.pyannote[862].speaker SPEAKER_02
transcript.pyannote[862].start 7166.74221875
transcript.pyannote[862].end 7170.06659375
transcript.pyannote[863].speaker SPEAKER_02
transcript.pyannote[863].start 7170.40409375
transcript.pyannote[863].end 7173.79596875
transcript.pyannote[864].speaker SPEAKER_24
transcript.pyannote[864].start 7170.97784375
transcript.pyannote[864].end 7171.82159375
transcript.pyannote[865].speaker SPEAKER_24
transcript.pyannote[865].start 7173.79596875
transcript.pyannote[865].end 7175.14596875
transcript.pyannote[866].speaker SPEAKER_02
transcript.pyannote[866].start 7174.33596875
transcript.pyannote[866].end 7190.31659375
transcript.pyannote[867].speaker SPEAKER_24
transcript.pyannote[867].start 7177.71096875
transcript.pyannote[867].end 7178.90909375
transcript.pyannote[868].speaker SPEAKER_24
transcript.pyannote[868].start 7185.47346875
transcript.pyannote[868].end 7186.95846875
transcript.pyannote[869].speaker SPEAKER_24
transcript.pyannote[869].start 7189.47284375
transcript.pyannote[869].end 7193.11784375
transcript.pyannote[870].speaker SPEAKER_02
transcript.pyannote[870].start 7192.64534375
transcript.pyannote[870].end 7203.24284375
transcript.pyannote[871].speaker SPEAKER_24
transcript.pyannote[871].start 7193.91096875
transcript.pyannote[871].end 7194.46784375
transcript.pyannote[872].speaker SPEAKER_24
transcript.pyannote[872].start 7195.22721875
transcript.pyannote[872].end 7196.15534375
transcript.pyannote[873].speaker SPEAKER_02
transcript.pyannote[873].start 7203.96846875
transcript.pyannote[873].end 7212.94596875
transcript.pyannote[874].speaker SPEAKER_24
transcript.pyannote[874].start 7214.36346875
transcript.pyannote[874].end 7225.04534375
transcript.pyannote[875].speaker SPEAKER_02
transcript.pyannote[875].start 7225.04534375
transcript.pyannote[875].end 7225.33221875
transcript.pyannote[876].speaker SPEAKER_02
transcript.pyannote[876].start 7225.55159375
transcript.pyannote[876].end 7238.24159375
transcript.pyannote[877].speaker SPEAKER_24
transcript.pyannote[877].start 7238.86596875
transcript.pyannote[877].end 7244.94096875
transcript.pyannote[878].speaker SPEAKER_24
transcript.pyannote[878].start 7245.53159375
transcript.pyannote[878].end 7251.10034375
transcript.pyannote[879].speaker SPEAKER_02
transcript.pyannote[879].start 7250.50971875
transcript.pyannote[879].end 7252.83846875
transcript.pyannote[880].speaker SPEAKER_24
transcript.pyannote[880].start 7252.34909375
transcript.pyannote[880].end 7252.82159375
transcript.pyannote[881].speaker SPEAKER_24
transcript.pyannote[881].start 7252.83846875
transcript.pyannote[881].end 7260.87096875
transcript.pyannote[882].speaker SPEAKER_02
transcript.pyannote[882].start 7253.04096875
transcript.pyannote[882].end 7253.53034375
transcript.pyannote[883].speaker SPEAKER_02
transcript.pyannote[883].start 7260.87096875
transcript.pyannote[883].end 7264.26284375
transcript.pyannote[884].speaker SPEAKER_02
transcript.pyannote[884].start 7264.51596875
transcript.pyannote[884].end 7265.47784375
transcript.pyannote[885].speaker SPEAKER_24
transcript.pyannote[885].start 7264.83659375
transcript.pyannote[885].end 7269.07221875
transcript.pyannote[886].speaker SPEAKER_02
transcript.pyannote[886].start 7268.16096875
transcript.pyannote[886].end 7281.25596875
transcript.pyannote[887].speaker SPEAKER_29
transcript.pyannote[887].start 7278.82596875
transcript.pyannote[887].end 7279.12971875
transcript.pyannote[888].speaker SPEAKER_02
transcript.pyannote[888].start 7281.71159375
transcript.pyannote[888].end 7282.79159375
transcript.pyannote[889].speaker SPEAKER_29
transcript.pyannote[889].start 7282.36971875
transcript.pyannote[889].end 7282.84221875
transcript.pyannote[890].speaker SPEAKER_02
transcript.pyannote[890].start 7282.84221875
transcript.pyannote[890].end 7289.00159375
transcript.pyannote[891].speaker SPEAKER_24
transcript.pyannote[891].start 7288.52909375
transcript.pyannote[891].end 7292.44409375
transcript.pyannote[892].speaker SPEAKER_24
transcript.pyannote[892].start 7292.54534375
transcript.pyannote[892].end 7292.56221875
transcript.pyannote[893].speaker SPEAKER_02
transcript.pyannote[893].start 7292.56221875
transcript.pyannote[893].end 7292.91659375
transcript.pyannote[894].speaker SPEAKER_24
transcript.pyannote[894].start 7292.91659375
transcript.pyannote[894].end 7295.68409375
transcript.pyannote[895].speaker SPEAKER_02
transcript.pyannote[895].start 7294.90784375
transcript.pyannote[895].end 7297.00034375
transcript.pyannote[896].speaker SPEAKER_24
transcript.pyannote[896].start 7296.19034375
transcript.pyannote[896].end 7299.97034375
transcript.pyannote[897].speaker SPEAKER_24
transcript.pyannote[897].start 7300.34159375
transcript.pyannote[897].end 7304.66159375
transcript.pyannote[898].speaker SPEAKER_24
transcript.pyannote[898].start 7305.64034375
transcript.pyannote[898].end 7315.54596875
transcript.pyannote[899].speaker SPEAKER_02
transcript.pyannote[899].start 7314.31409375
transcript.pyannote[899].end 7325.55284375
transcript.pyannote[900].speaker SPEAKER_24
transcript.pyannote[900].start 7326.64971875
transcript.pyannote[900].end 7335.15471875
transcript.pyannote[901].speaker SPEAKER_02
transcript.pyannote[901].start 7326.95346875
transcript.pyannote[901].end 7328.84346875
transcript.pyannote[902].speaker SPEAKER_24
transcript.pyannote[902].start 7335.74534375
transcript.pyannote[902].end 7339.67721875
transcript.pyannote[903].speaker SPEAKER_02
transcript.pyannote[903].start 7338.25971875
transcript.pyannote[903].end 7346.66346875
transcript.pyannote[904].speaker SPEAKER_24
transcript.pyannote[904].start 7346.69721875
transcript.pyannote[904].end 7348.19909375
transcript.pyannote[905].speaker SPEAKER_02
transcript.pyannote[905].start 7347.05159375
transcript.pyannote[905].end 7347.52409375
transcript.pyannote[906].speaker SPEAKER_02
transcript.pyannote[906].start 7348.19909375
transcript.pyannote[906].end 7348.21596875
transcript.pyannote[907].speaker SPEAKER_24
transcript.pyannote[907].start 7348.21596875
transcript.pyannote[907].end 7348.28346875
transcript.pyannote[908].speaker SPEAKER_02
transcript.pyannote[908].start 7348.28346875
transcript.pyannote[908].end 7348.77284375
transcript.pyannote[909].speaker SPEAKER_24
transcript.pyannote[909].start 7348.77284375
transcript.pyannote[909].end 7348.80659375
transcript.pyannote[910].speaker SPEAKER_02
transcript.pyannote[910].start 7348.80659375
transcript.pyannote[910].end 7348.97534375
transcript.pyannote[911].speaker SPEAKER_24
transcript.pyannote[911].start 7348.97534375
transcript.pyannote[911].end 7355.03346875
transcript.pyannote[912].speaker SPEAKER_02
transcript.pyannote[912].start 7349.29596875
transcript.pyannote[912].end 7349.59971875
transcript.pyannote[913].speaker SPEAKER_02
transcript.pyannote[913].start 7355.03346875
transcript.pyannote[913].end 7355.70846875
transcript.pyannote[914].speaker SPEAKER_02
transcript.pyannote[914].start 7356.18096875
transcript.pyannote[914].end 7362.98159375
transcript.pyannote[915].speaker SPEAKER_02
transcript.pyannote[915].start 7363.31909375
transcript.pyannote[915].end 7367.20034375
transcript.pyannote[916].speaker SPEAKER_02
transcript.pyannote[916].start 7367.35221875
transcript.pyannote[916].end 7370.96346875
transcript.pyannote[917].speaker SPEAKER_24
transcript.pyannote[917].start 7369.19159375
transcript.pyannote[917].end 7369.68096875
transcript.pyannote[918].speaker SPEAKER_24
transcript.pyannote[918].start 7370.96346875
transcript.pyannote[918].end 7377.44346875
transcript.pyannote[919].speaker SPEAKER_02
transcript.pyannote[919].start 7373.81534375
transcript.pyannote[919].end 7374.42284375
transcript.pyannote[920].speaker SPEAKER_02
transcript.pyannote[920].start 7377.44346875
transcript.pyannote[920].end 7377.49409375
transcript.pyannote[921].speaker SPEAKER_02
transcript.pyannote[921].start 7377.71346875
transcript.pyannote[921].end 7386.15096875
transcript.pyannote[922].speaker SPEAKER_24
transcript.pyannote[922].start 7386.06659375
transcript.pyannote[922].end 7388.47971875
transcript.pyannote[923].speaker SPEAKER_02
transcript.pyannote[923].start 7387.23096875
transcript.pyannote[923].end 7392.04034375
transcript.pyannote[924].speaker SPEAKER_24
transcript.pyannote[924].start 7393.47471875
transcript.pyannote[924].end 7393.50846875
transcript.pyannote[925].speaker SPEAKER_02
transcript.pyannote[925].start 7393.50846875
transcript.pyannote[925].end 7393.57596875
transcript.pyannote[926].speaker SPEAKER_24
transcript.pyannote[926].start 7393.57596875
transcript.pyannote[926].end 7393.82909375
transcript.pyannote[927].speaker SPEAKER_02
transcript.pyannote[927].start 7393.82909375
transcript.pyannote[927].end 7393.96409375
transcript.pyannote[928].speaker SPEAKER_24
transcript.pyannote[928].start 7393.96409375
transcript.pyannote[928].end 7397.01846875
transcript.pyannote[929].speaker SPEAKER_24
transcript.pyannote[929].start 7397.35596875
transcript.pyannote[929].end 7406.94096875
transcript.pyannote[930].speaker SPEAKER_02
transcript.pyannote[930].start 7398.35159375
transcript.pyannote[930].end 7398.73971875
transcript.pyannote[931].speaker SPEAKER_02
transcript.pyannote[931].start 7406.01284375
transcript.pyannote[931].end 7418.65221875
transcript.pyannote[932].speaker SPEAKER_24
transcript.pyannote[932].start 7407.66659375
transcript.pyannote[932].end 7408.52721875
transcript.pyannote[933].speaker SPEAKER_02
transcript.pyannote[933].start 7419.04034375
transcript.pyannote[933].end 7422.31409375
transcript.pyannote[934].speaker SPEAKER_00
transcript.pyannote[934].start 7419.07409375
transcript.pyannote[934].end 7419.09096875
transcript.pyannote[935].speaker SPEAKER_24
transcript.pyannote[935].start 7419.09096875
transcript.pyannote[935].end 7419.83346875
transcript.pyannote[936].speaker SPEAKER_02
transcript.pyannote[936].start 7422.41534375
transcript.pyannote[936].end 7427.39346875
transcript.pyannote[937].speaker SPEAKER_24
transcript.pyannote[937].start 7427.56221875
transcript.pyannote[937].end 7438.39596875
transcript.pyannote[938].speaker SPEAKER_02
transcript.pyannote[938].start 7435.98284375
transcript.pyannote[938].end 7444.77471875
transcript.pyannote[939].speaker SPEAKER_24
transcript.pyannote[939].start 7445.23034375
transcript.pyannote[939].end 7446.15846875
transcript.pyannote[940].speaker SPEAKER_02
transcript.pyannote[940].start 7446.15846875
transcript.pyannote[940].end 7450.34346875
transcript.pyannote[941].speaker SPEAKER_24
transcript.pyannote[941].start 7450.34346875
transcript.pyannote[941].end 7451.32221875
transcript.pyannote[942].speaker SPEAKER_02
transcript.pyannote[942].start 7450.90034375
transcript.pyannote[942].end 7451.33909375
transcript.pyannote[943].speaker SPEAKER_24
transcript.pyannote[943].start 7451.33909375
transcript.pyannote[943].end 7451.40659375
transcript.pyannote[944].speaker SPEAKER_02
transcript.pyannote[944].start 7451.40659375
transcript.pyannote[944].end 7457.63346875
transcript.pyannote[945].speaker SPEAKER_24
transcript.pyannote[945].start 7452.95909375
transcript.pyannote[945].end 7453.83659375
transcript.pyannote[946].speaker SPEAKER_24
transcript.pyannote[946].start 7456.01346875
transcript.pyannote[946].end 7458.64596875
transcript.pyannote[947].speaker SPEAKER_24
transcript.pyannote[947].start 7459.92846875
transcript.pyannote[947].end 7465.78409375
transcript.pyannote[948].speaker SPEAKER_02
transcript.pyannote[948].start 7465.78409375
transcript.pyannote[948].end 7478.52471875
transcript.pyannote[949].speaker SPEAKER_24
transcript.pyannote[949].start 7477.74846875
transcript.pyannote[949].end 7488.02534375
transcript.pyannote[950].speaker SPEAKER_02
transcript.pyannote[950].start 7481.39346875
transcript.pyannote[950].end 7481.89971875
transcript.pyannote[951].speaker SPEAKER_02
transcript.pyannote[951].start 7486.91159375
transcript.pyannote[951].end 7487.46846875
transcript.pyannote[952].speaker SPEAKER_02
transcript.pyannote[952].start 7488.02534375
transcript.pyannote[952].end 7488.04221875
transcript.pyannote[953].speaker SPEAKER_24
transcript.pyannote[953].start 7488.04221875
transcript.pyannote[953].end 7489.93221875
transcript.pyannote[954].speaker SPEAKER_02
transcript.pyannote[954].start 7488.83534375
transcript.pyannote[954].end 7489.66221875
transcript.pyannote[955].speaker SPEAKER_24
transcript.pyannote[955].start 7490.30346875
transcript.pyannote[955].end 7492.66596875
transcript.pyannote[956].speaker SPEAKER_02
transcript.pyannote[956].start 7491.95721875
transcript.pyannote[956].end 7493.42534375
transcript.pyannote[957].speaker SPEAKER_24
transcript.pyannote[957].start 7493.42534375
transcript.pyannote[957].end 7495.72034375
transcript.pyannote[958].speaker SPEAKER_02
transcript.pyannote[958].start 7495.33221875
transcript.pyannote[958].end 7495.73721875
transcript.pyannote[959].speaker SPEAKER_24
transcript.pyannote[959].start 7495.73721875
transcript.pyannote[959].end 7496.88471875
transcript.pyannote[960].speaker SPEAKER_02
transcript.pyannote[960].start 7496.88471875
transcript.pyannote[960].end 7497.77909375
transcript.pyannote[961].speaker SPEAKER_24
transcript.pyannote[961].start 7497.05346875
transcript.pyannote[961].end 7497.39096875
transcript.pyannote[962].speaker SPEAKER_24
transcript.pyannote[962].start 7497.77909375
transcript.pyannote[962].end 7497.82971875
transcript.pyannote[963].speaker SPEAKER_24
transcript.pyannote[963].start 7497.84659375
transcript.pyannote[963].end 7505.98034375
transcript.pyannote[964].speaker SPEAKER_02
transcript.pyannote[964].start 7505.38971875
transcript.pyannote[964].end 7509.49034375
transcript.pyannote[965].speaker SPEAKER_24
transcript.pyannote[965].start 7509.49034375
transcript.pyannote[965].end 7518.31596875
transcript.pyannote[966].speaker SPEAKER_02
transcript.pyannote[966].start 7518.31596875
transcript.pyannote[966].end 7526.85471875
transcript.pyannote[967].speaker SPEAKER_24
transcript.pyannote[967].start 7522.38284375
transcript.pyannote[967].end 7523.80034375
transcript.pyannote[968].speaker SPEAKER_24
transcript.pyannote[968].start 7524.96471875
transcript.pyannote[968].end 7525.96034375
transcript.pyannote[969].speaker SPEAKER_24
transcript.pyannote[969].start 7526.70284375
transcript.pyannote[969].end 7528.82909375
transcript.pyannote[970].speaker SPEAKER_02
transcript.pyannote[970].start 7528.82909375
transcript.pyannote[970].end 7529.57159375
transcript.pyannote[971].speaker SPEAKER_24
transcript.pyannote[971].start 7529.57159375
transcript.pyannote[971].end 7529.63909375
transcript.pyannote[972].speaker SPEAKER_24
transcript.pyannote[972].start 7530.07784375
transcript.pyannote[972].end 7532.59221875
transcript.pyannote[973].speaker SPEAKER_02
transcript.pyannote[973].start 7533.18284375
transcript.pyannote[973].end 7533.84096875
transcript.pyannote[974].speaker SPEAKER_24
transcript.pyannote[974].start 7535.42721875
transcript.pyannote[974].end 7537.43534375
transcript.pyannote[975].speaker SPEAKER_02
transcript.pyannote[975].start 7538.26221875
transcript.pyannote[975].end 7540.74284375
transcript.pyannote[976].speaker SPEAKER_02
transcript.pyannote[976].start 7541.92409375
transcript.pyannote[976].end 7542.49784375
transcript.pyannote[977].speaker SPEAKER_02
transcript.pyannote[977].start 7543.71284375
transcript.pyannote[977].end 7543.78034375
transcript.pyannote[978].speaker SPEAKER_24
transcript.pyannote[978].start 7543.78034375
transcript.pyannote[978].end 7545.34971875
transcript.pyannote[979].speaker SPEAKER_02
transcript.pyannote[979].start 7545.60284375
transcript.pyannote[979].end 7550.68221875
transcript.pyannote[980].speaker SPEAKER_03
transcript.pyannote[980].start 7549.56846875
transcript.pyannote[980].end 7549.82159375
transcript.pyannote[981].speaker SPEAKER_03
transcript.pyannote[981].start 7552.67346875
transcript.pyannote[981].end 7557.19596875
transcript.pyannote[982].speaker SPEAKER_03
transcript.pyannote[982].start 8312.99346875
transcript.pyannote[982].end 8315.18721875
transcript.pyannote[983].speaker SPEAKER_03
transcript.pyannote[983].start 8316.33471875
transcript.pyannote[983].end 8317.71846875
transcript.pyannote[984].speaker SPEAKER_03
transcript.pyannote[984].start 8319.77721875
transcript.pyannote[984].end 8321.07659375
transcript.pyannote[985].speaker SPEAKER_03
transcript.pyannote[985].start 8321.97096875
transcript.pyannote[985].end 8330.93159375
transcript.pyannote[986].speaker SPEAKER_03
transcript.pyannote[986].start 8331.13409375
transcript.pyannote[986].end 8337.86721875
transcript.pyannote[987].speaker SPEAKER_03
transcript.pyannote[987].start 8338.20471875
transcript.pyannote[987].end 8340.68534375
transcript.pyannote[988].speaker SPEAKER_03
transcript.pyannote[988].start 8340.98909375
transcript.pyannote[988].end 8357.99909375
transcript.pyannote[989].speaker SPEAKER_03
transcript.pyannote[989].start 8422.36034375
transcript.pyannote[989].end 8426.19096875
transcript.pyannote[990].speaker SPEAKER_03
transcript.pyannote[990].start 8426.57909375
transcript.pyannote[990].end 8429.16096875
transcript.pyannote[991].speaker SPEAKER_03
transcript.pyannote[991].start 8429.88659375
transcript.pyannote[991].end 8432.50221875
transcript.pyannote[992].speaker SPEAKER_30
transcript.pyannote[992].start 8443.60596875
transcript.pyannote[992].end 8449.63034375
transcript.pyannote[993].speaker SPEAKER_03
transcript.pyannote[993].start 8447.38596875
transcript.pyannote[993].end 8448.02721875
transcript.pyannote[994].speaker SPEAKER_03
transcript.pyannote[994].start 8449.84971875
transcript.pyannote[994].end 8450.91284375
transcript.pyannote[995].speaker SPEAKER_30
transcript.pyannote[995].start 8458.65846875
transcript.pyannote[995].end 8461.07159375
transcript.pyannote[996].speaker SPEAKER_30
transcript.pyannote[996].start 8461.59471875
transcript.pyannote[996].end 8465.86409375
transcript.pyannote[997].speaker SPEAKER_30
transcript.pyannote[997].start 8466.21846875
transcript.pyannote[997].end 8472.69846875
transcript.pyannote[998].speaker SPEAKER_30
transcript.pyannote[998].start 8473.17096875
transcript.pyannote[998].end 8474.23409375
transcript.pyannote[999].speaker SPEAKER_30
transcript.pyannote[999].start 8474.65596875
transcript.pyannote[999].end 8478.52034375
transcript.pyannote[1000].speaker SPEAKER_30
transcript.pyannote[1000].start 8479.07721875
transcript.pyannote[1000].end 8480.08971875
transcript.pyannote[1001].speaker SPEAKER_30
transcript.pyannote[1001].start 8480.57909375
transcript.pyannote[1001].end 8481.72659375
transcript.pyannote[1002].speaker SPEAKER_30
transcript.pyannote[1002].start 8482.36784375
transcript.pyannote[1002].end 8483.26221875
transcript.pyannote[1003].speaker SPEAKER_30
transcript.pyannote[1003].start 8483.71784375
transcript.pyannote[1003].end 8484.79784375
transcript.pyannote[1004].speaker SPEAKER_30
transcript.pyannote[1004].start 8485.05096875
transcript.pyannote[1004].end 8485.77659375
transcript.pyannote[1005].speaker SPEAKER_30
transcript.pyannote[1005].start 8485.87784375
transcript.pyannote[1005].end 8493.60659375
transcript.pyannote[1006].speaker SPEAKER_30
transcript.pyannote[1006].start 8494.02846875
transcript.pyannote[1006].end 8496.27284375
transcript.pyannote[1007].speaker SPEAKER_30
transcript.pyannote[1007].start 8496.50909375
transcript.pyannote[1007].end 8497.53846875
transcript.pyannote[1008].speaker SPEAKER_30
transcript.pyannote[1008].start 8497.94346875
transcript.pyannote[1008].end 8500.82909375
transcript.pyannote[1009].speaker SPEAKER_30
transcript.pyannote[1009].start 8501.80784375
transcript.pyannote[1009].end 8504.84534375
transcript.pyannote[1010].speaker SPEAKER_30
transcript.pyannote[1010].start 8505.14909375
transcript.pyannote[1010].end 8506.73534375
transcript.pyannote[1011].speaker SPEAKER_30
transcript.pyannote[1011].start 8507.12346875
transcript.pyannote[1011].end 8507.73096875
transcript.pyannote[1012].speaker SPEAKER_30
transcript.pyannote[1012].start 8508.10221875
transcript.pyannote[1012].end 8508.77721875
transcript.pyannote[1013].speaker SPEAKER_30
transcript.pyannote[1013].start 8508.91221875
transcript.pyannote[1013].end 8510.66721875
transcript.pyannote[1014].speaker SPEAKER_30
transcript.pyannote[1014].start 8510.83596875
transcript.pyannote[1014].end 8512.64159375
transcript.pyannote[1015].speaker SPEAKER_30
transcript.pyannote[1015].start 8512.82721875
transcript.pyannote[1015].end 8515.51034375
transcript.pyannote[1016].speaker SPEAKER_30
transcript.pyannote[1016].start 8515.94909375
transcript.pyannote[1016].end 8521.66971875
transcript.pyannote[1017].speaker SPEAKER_30
transcript.pyannote[1017].start 8521.95659375
transcript.pyannote[1017].end 8525.73659375
transcript.pyannote[1018].speaker SPEAKER_30
transcript.pyannote[1018].start 8525.83784375
transcript.pyannote[1018].end 8527.20471875
transcript.pyannote[1019].speaker SPEAKER_30
transcript.pyannote[1019].start 8527.76159375
transcript.pyannote[1019].end 8530.22534375
transcript.pyannote[1020].speaker SPEAKER_30
transcript.pyannote[1020].start 8530.44471875
transcript.pyannote[1020].end 8531.17034375
transcript.pyannote[1021].speaker SPEAKER_30
transcript.pyannote[1021].start 8531.42346875
transcript.pyannote[1021].end 8531.91284375
transcript.pyannote[1022].speaker SPEAKER_30
transcript.pyannote[1022].start 8532.11534375
transcript.pyannote[1022].end 8534.66346875
transcript.pyannote[1023].speaker SPEAKER_30
transcript.pyannote[1023].start 8535.20346875
transcript.pyannote[1023].end 8535.84471875
transcript.pyannote[1024].speaker SPEAKER_30
transcript.pyannote[1024].start 8537.46471875
transcript.pyannote[1024].end 8539.27034375
transcript.pyannote[1025].speaker SPEAKER_30
transcript.pyannote[1025].start 8539.87784375
transcript.pyannote[1025].end 8544.65346875
transcript.pyannote[1026].speaker SPEAKER_30
transcript.pyannote[1026].start 8544.92346875
transcript.pyannote[1026].end 8547.69096875
transcript.pyannote[1027].speaker SPEAKER_30
transcript.pyannote[1027].start 8548.41659375
transcript.pyannote[1027].end 8551.43721875
transcript.pyannote[1028].speaker SPEAKER_30
transcript.pyannote[1028].start 8552.19659375
transcript.pyannote[1028].end 8558.65971875
transcript.pyannote[1029].speaker SPEAKER_30
transcript.pyannote[1029].start 8558.81159375
transcript.pyannote[1029].end 8561.71409375
transcript.pyannote[1030].speaker SPEAKER_30
transcript.pyannote[1030].start 8561.89971875
transcript.pyannote[1030].end 8565.67971875
transcript.pyannote[1031].speaker SPEAKER_30
transcript.pyannote[1031].start 8566.75971875
transcript.pyannote[1031].end 8569.02096875
transcript.pyannote[1032].speaker SPEAKER_30
transcript.pyannote[1032].start 8569.17284375
transcript.pyannote[1032].end 8571.04596875
transcript.pyannote[1033].speaker SPEAKER_30
transcript.pyannote[1033].start 8571.26534375
transcript.pyannote[1033].end 8573.00346875
transcript.pyannote[1034].speaker SPEAKER_30
transcript.pyannote[1034].start 8573.86409375
transcript.pyannote[1034].end 8575.24784375
transcript.pyannote[1035].speaker SPEAKER_30
transcript.pyannote[1035].start 8576.69909375
transcript.pyannote[1035].end 8578.23471875
transcript.pyannote[1036].speaker SPEAKER_30
transcript.pyannote[1036].start 8578.43721875
transcript.pyannote[1036].end 8579.31471875
transcript.pyannote[1037].speaker SPEAKER_30
transcript.pyannote[1037].start 8580.25971875
transcript.pyannote[1037].end 8595.43034375
transcript.pyannote[1038].speaker SPEAKER_30
transcript.pyannote[1038].start 8596.08846875
transcript.pyannote[1038].end 8597.59034375
transcript.pyannote[1039].speaker SPEAKER_30
transcript.pyannote[1039].start 8597.97846875
transcript.pyannote[1039].end 8600.18909375
transcript.pyannote[1040].speaker SPEAKER_30
transcript.pyannote[1040].start 8600.81346875
transcript.pyannote[1040].end 8603.74971875
transcript.pyannote[1041].speaker SPEAKER_30
transcript.pyannote[1041].start 8604.69471875
transcript.pyannote[1041].end 8605.35284375
transcript.pyannote[1042].speaker SPEAKER_30
transcript.pyannote[1042].start 8605.60596875
transcript.pyannote[1042].end 8606.71971875
transcript.pyannote[1043].speaker SPEAKER_30
transcript.pyannote[1043].start 8607.12471875
transcript.pyannote[1043].end 8608.55909375
transcript.pyannote[1044].speaker SPEAKER_30
transcript.pyannote[1044].start 8609.92596875
transcript.pyannote[1044].end 8611.41096875
transcript.pyannote[1045].speaker SPEAKER_04
transcript.pyannote[1045].start 8614.38096875
transcript.pyannote[1045].end 8617.31721875
transcript.pyannote[1046].speaker SPEAKER_04
transcript.pyannote[1046].start 8617.45221875
transcript.pyannote[1046].end 8622.31221875
transcript.pyannote[1047].speaker SPEAKER_30
transcript.pyannote[1047].start 8622.31221875
transcript.pyannote[1047].end 8624.47221875
transcript.pyannote[1048].speaker SPEAKER_04
transcript.pyannote[1048].start 8623.27409375
transcript.pyannote[1048].end 8623.76346875
transcript.pyannote[1049].speaker SPEAKER_04
transcript.pyannote[1049].start 8625.14721875
transcript.pyannote[1049].end 8628.79221875
transcript.pyannote[1050].speaker SPEAKER_04
transcript.pyannote[1050].start 8630.44596875
transcript.pyannote[1050].end 8639.71034375
transcript.pyannote[1051].speaker SPEAKER_04
transcript.pyannote[1051].start 8640.21659375
transcript.pyannote[1051].end 8643.87846875
transcript.pyannote[1052].speaker SPEAKER_04
transcript.pyannote[1052].start 8643.91221875
transcript.pyannote[1052].end 8651.74221875
transcript.pyannote[1053].speaker SPEAKER_30
transcript.pyannote[1053].start 8652.34971875
transcript.pyannote[1053].end 8658.39096875
transcript.pyannote[1054].speaker SPEAKER_04
transcript.pyannote[1054].start 8656.45034375
transcript.pyannote[1054].end 8656.82159375
transcript.pyannote[1055].speaker SPEAKER_04
transcript.pyannote[1055].start 8657.26034375
transcript.pyannote[1055].end 8658.96471875
transcript.pyannote[1056].speaker SPEAKER_30
transcript.pyannote[1056].start 8658.69471875
transcript.pyannote[1056].end 8666.17034375
transcript.pyannote[1057].speaker SPEAKER_30
transcript.pyannote[1057].start 8666.38971875
transcript.pyannote[1057].end 8667.73971875
transcript.pyannote[1058].speaker SPEAKER_04
transcript.pyannote[1058].start 8668.36409375
transcript.pyannote[1058].end 8668.38096875
transcript.pyannote[1059].speaker SPEAKER_30
transcript.pyannote[1059].start 8668.38096875
transcript.pyannote[1059].end 8672.17784375
transcript.pyannote[1060].speaker SPEAKER_04
transcript.pyannote[1060].start 8668.39784375
transcript.pyannote[1060].end 8669.05596875
transcript.pyannote[1061].speaker SPEAKER_04
transcript.pyannote[1061].start 8670.00096875
transcript.pyannote[1061].end 8671.48596875
transcript.pyannote[1062].speaker SPEAKER_04
transcript.pyannote[1062].start 8672.31284375
transcript.pyannote[1062].end 8676.85221875
transcript.pyannote[1063].speaker SPEAKER_04
transcript.pyannote[1063].start 8676.98721875
transcript.pyannote[1063].end 8683.56846875
transcript.pyannote[1064].speaker SPEAKER_30
transcript.pyannote[1064].start 8682.28596875
transcript.pyannote[1064].end 8685.25596875
transcript.pyannote[1065].speaker SPEAKER_04
transcript.pyannote[1065].start 8684.59784375
transcript.pyannote[1065].end 8685.62721875
transcript.pyannote[1066].speaker SPEAKER_30
transcript.pyannote[1066].start 8685.40784375
transcript.pyannote[1066].end 8687.07846875
transcript.pyannote[1067].speaker SPEAKER_30
transcript.pyannote[1067].start 8687.33159375
transcript.pyannote[1067].end 8690.14971875
transcript.pyannote[1068].speaker SPEAKER_04
transcript.pyannote[1068].start 8688.59721875
transcript.pyannote[1068].end 8688.85034375
transcript.pyannote[1069].speaker SPEAKER_30
transcript.pyannote[1069].start 8690.92596875
transcript.pyannote[1069].end 8691.92159375
transcript.pyannote[1070].speaker SPEAKER_30
transcript.pyannote[1070].start 8692.32659375
transcript.pyannote[1070].end 8695.63409375
transcript.pyannote[1071].speaker SPEAKER_04
transcript.pyannote[1071].start 8694.19971875
transcript.pyannote[1071].end 8704.98284375
transcript.pyannote[1072].speaker SPEAKER_30
transcript.pyannote[1072].start 8705.20221875
transcript.pyannote[1072].end 8710.72034375
transcript.pyannote[1073].speaker SPEAKER_30
transcript.pyannote[1073].start 8711.31096875
transcript.pyannote[1073].end 8711.78346875
transcript.pyannote[1074].speaker SPEAKER_04
transcript.pyannote[1074].start 8711.76659375
transcript.pyannote[1074].end 8718.02721875
transcript.pyannote[1075].speaker SPEAKER_30
transcript.pyannote[1075].start 8711.80034375
transcript.pyannote[1075].end 8711.88471875
transcript.pyannote[1076].speaker SPEAKER_30
transcript.pyannote[1076].start 8711.98596875
transcript.pyannote[1076].end 8713.01534375
transcript.pyannote[1077].speaker SPEAKER_30
transcript.pyannote[1077].start 8718.41534375
transcript.pyannote[1077].end 8719.05659375
transcript.pyannote[1078].speaker SPEAKER_04
transcript.pyannote[1078].start 8718.44909375
transcript.pyannote[1078].end 8719.15784375
transcript.pyannote[1079].speaker SPEAKER_04
transcript.pyannote[1079].start 8719.22534375
transcript.pyannote[1079].end 8721.77346875
transcript.pyannote[1080].speaker SPEAKER_04
transcript.pyannote[1080].start 8722.00971875
transcript.pyannote[1080].end 8727.29159375
transcript.pyannote[1081].speaker SPEAKER_30
transcript.pyannote[1081].start 8727.73034375
transcript.pyannote[1081].end 8729.60346875
transcript.pyannote[1082].speaker SPEAKER_30
transcript.pyannote[1082].start 8729.92409375
transcript.pyannote[1082].end 8733.63659375
transcript.pyannote[1083].speaker SPEAKER_30
transcript.pyannote[1083].start 8734.32846875
transcript.pyannote[1083].end 8740.42034375
transcript.pyannote[1084].speaker SPEAKER_30
transcript.pyannote[1084].start 8740.79159375
transcript.pyannote[1084].end 8743.66034375
transcript.pyannote[1085].speaker SPEAKER_30
transcript.pyannote[1085].start 8744.20034375
transcript.pyannote[1085].end 8751.13596875
transcript.pyannote[1086].speaker SPEAKER_30
transcript.pyannote[1086].start 8751.55784375
transcript.pyannote[1086].end 8756.56971875
transcript.pyannote[1087].speaker SPEAKER_30
transcript.pyannote[1087].start 8757.22784375
transcript.pyannote[1087].end 8772.82034375
transcript.pyannote[1088].speaker SPEAKER_30
transcript.pyannote[1088].start 8773.09034375
transcript.pyannote[1088].end 8778.27096875
transcript.pyannote[1089].speaker SPEAKER_04
transcript.pyannote[1089].start 8773.10721875
transcript.pyannote[1089].end 8773.76534375
transcript.pyannote[1090].speaker SPEAKER_04
transcript.pyannote[1090].start 8778.97971875
transcript.pyannote[1090].end 8782.00034375
transcript.pyannote[1091].speaker SPEAKER_04
transcript.pyannote[1091].start 8782.62471875
transcript.pyannote[1091].end 8788.88534375
transcript.pyannote[1092].speaker SPEAKER_04
transcript.pyannote[1092].start 8789.13846875
transcript.pyannote[1092].end 8792.76659375
transcript.pyannote[1093].speaker SPEAKER_04
transcript.pyannote[1093].start 8793.08721875
transcript.pyannote[1093].end 8795.53409375
transcript.pyannote[1094].speaker SPEAKER_04
transcript.pyannote[1094].start 8795.88846875
transcript.pyannote[1094].end 8806.72221875
transcript.pyannote[1095].speaker SPEAKER_30
transcript.pyannote[1095].start 8807.81909375
transcript.pyannote[1095].end 8809.69221875
transcript.pyannote[1096].speaker SPEAKER_04
transcript.pyannote[1096].start 8807.85284375
transcript.pyannote[1096].end 8808.57846875
transcript.pyannote[1097].speaker SPEAKER_30
transcript.pyannote[1097].start 8810.40096875
transcript.pyannote[1097].end 8829.97596875
transcript.pyannote[1098].speaker SPEAKER_22
transcript.pyannote[1098].start 8824.99784375
transcript.pyannote[1098].end 8825.01471875
transcript.pyannote[1099].speaker SPEAKER_10
transcript.pyannote[1099].start 8825.01471875
transcript.pyannote[1099].end 8825.06534375
transcript.pyannote[1100].speaker SPEAKER_29
transcript.pyannote[1100].start 8825.06534375
transcript.pyannote[1100].end 8825.09909375
transcript.pyannote[1101].speaker SPEAKER_10
transcript.pyannote[1101].start 8825.09909375
transcript.pyannote[1101].end 8825.30159375
transcript.pyannote[1102].speaker SPEAKER_10
transcript.pyannote[1102].start 8829.87471875
transcript.pyannote[1102].end 8831.10659375
transcript.pyannote[1103].speaker SPEAKER_30
transcript.pyannote[1103].start 8830.00971875
transcript.pyannote[1103].end 8830.07721875
transcript.pyannote[1104].speaker SPEAKER_30
transcript.pyannote[1104].start 8830.17846875
transcript.pyannote[1104].end 8838.90284375
transcript.pyannote[1105].speaker SPEAKER_04
transcript.pyannote[1105].start 8834.17784375
transcript.pyannote[1105].end 8834.36346875
transcript.pyannote[1106].speaker SPEAKER_04
transcript.pyannote[1106].start 8838.76784375
transcript.pyannote[1106].end 8840.25284375
transcript.pyannote[1107].speaker SPEAKER_30
transcript.pyannote[1107].start 8840.06721875
transcript.pyannote[1107].end 8845.99034375
transcript.pyannote[1108].speaker SPEAKER_29
transcript.pyannote[1108].start 8846.46284375
transcript.pyannote[1108].end 8846.86784375
transcript.pyannote[1109].speaker SPEAKER_30
transcript.pyannote[1109].start 8847.12096875
transcript.pyannote[1109].end 8850.81659375
transcript.pyannote[1110].speaker SPEAKER_30
transcript.pyannote[1110].start 8851.37346875
transcript.pyannote[1110].end 8853.92159375
transcript.pyannote[1111].speaker SPEAKER_30
transcript.pyannote[1111].start 8855.06909375
transcript.pyannote[1111].end 8858.83221875
transcript.pyannote[1112].speaker SPEAKER_30
transcript.pyannote[1112].start 8859.27096875
transcript.pyannote[1112].end 8859.69284375
transcript.pyannote[1113].speaker SPEAKER_30
transcript.pyannote[1113].start 8860.94159375
transcript.pyannote[1113].end 8864.43471875
transcript.pyannote[1114].speaker SPEAKER_30
transcript.pyannote[1114].start 8865.12659375
transcript.pyannote[1114].end 8868.78846875
transcript.pyannote[1115].speaker SPEAKER_30
transcript.pyannote[1115].start 8869.46346875
transcript.pyannote[1115].end 8885.57909375
transcript.pyannote[1116].speaker SPEAKER_30
transcript.pyannote[1116].start 8886.77721875
transcript.pyannote[1116].end 8889.89909375
transcript.pyannote[1117].speaker SPEAKER_30
transcript.pyannote[1117].start 8890.30409375
transcript.pyannote[1117].end 8891.36721875
transcript.pyannote[1118].speaker SPEAKER_30
transcript.pyannote[1118].start 8891.41784375
transcript.pyannote[1118].end 8892.63284375
transcript.pyannote[1119].speaker SPEAKER_30
transcript.pyannote[1119].start 8893.03784375
transcript.pyannote[1119].end 8959.42409375
transcript.pyannote[1120].speaker SPEAKER_30
transcript.pyannote[1120].start 8959.99784375
transcript.pyannote[1120].end 8960.80784375
transcript.pyannote[1121].speaker SPEAKER_30
transcript.pyannote[1121].start 8961.04409375
transcript.pyannote[1121].end 8970.15659375
transcript.pyannote[1122].speaker SPEAKER_30
transcript.pyannote[1122].start 8970.57846875
transcript.pyannote[1122].end 8971.77659375
transcript.pyannote[1123].speaker SPEAKER_30
transcript.pyannote[1123].start 8971.84409375
transcript.pyannote[1123].end 8972.35034375
transcript.pyannote[1124].speaker SPEAKER_30
transcript.pyannote[1124].start 8972.65409375
transcript.pyannote[1124].end 8973.56534375
transcript.pyannote[1125].speaker SPEAKER_30
transcript.pyannote[1125].start 8974.79721875
transcript.pyannote[1125].end 8977.14284375
transcript.pyannote[1126].speaker SPEAKER_30
transcript.pyannote[1126].start 8978.12159375
transcript.pyannote[1126].end 8982.94784375
transcript.pyannote[1127].speaker SPEAKER_30
transcript.pyannote[1127].start 8983.48784375
transcript.pyannote[1127].end 8984.16284375
transcript.pyannote[1128].speaker SPEAKER_30
transcript.pyannote[1128].start 8984.43284375
transcript.pyannote[1128].end 8990.59221875
transcript.pyannote[1129].speaker SPEAKER_30
transcript.pyannote[1129].start 8991.09846875
transcript.pyannote[1129].end 9001.30784375
transcript.pyannote[1130].speaker SPEAKER_30
transcript.pyannote[1130].start 9001.79721875
transcript.pyannote[1130].end 9006.60659375
transcript.pyannote[1131].speaker SPEAKER_30
transcript.pyannote[1131].start 9006.80909375
transcript.pyannote[1131].end 9006.82596875
transcript.pyannote[1132].speaker SPEAKER_24
transcript.pyannote[1132].start 9006.82596875
transcript.pyannote[1132].end 9016.44471875
transcript.pyannote[1133].speaker SPEAKER_30
transcript.pyannote[1133].start 9006.99471875
transcript.pyannote[1133].end 9007.39971875
transcript.pyannote[1134].speaker SPEAKER_24
transcript.pyannote[1134].start 9016.61346875
transcript.pyannote[1134].end 9056.75909375
transcript.pyannote[1135].speaker SPEAKER_24
transcript.pyannote[1135].start 9057.77159375
transcript.pyannote[1135].end 9059.69534375
transcript.pyannote[1136].speaker SPEAKER_30
transcript.pyannote[1136].start 9059.74596875
transcript.pyannote[1136].end 9062.69909375
transcript.pyannote[1137].speaker SPEAKER_30
transcript.pyannote[1137].start 9063.32346875
transcript.pyannote[1137].end 9065.14596875
transcript.pyannote[1138].speaker SPEAKER_30
transcript.pyannote[1138].start 9065.58471875
transcript.pyannote[1138].end 9070.22534375
transcript.pyannote[1139].speaker SPEAKER_24
transcript.pyannote[1139].start 9070.05659375
transcript.pyannote[1139].end 9075.28784375
transcript.pyannote[1140].speaker SPEAKER_24
transcript.pyannote[1140].start 9075.70971875
transcript.pyannote[1140].end 9079.81034375
transcript.pyannote[1141].speaker SPEAKER_24
transcript.pyannote[1141].start 9080.43471875
transcript.pyannote[1141].end 9111.60284375
transcript.pyannote[1142].speaker SPEAKER_30
transcript.pyannote[1142].start 9111.60284375
transcript.pyannote[1142].end 9115.99034375
transcript.pyannote[1143].speaker SPEAKER_30
transcript.pyannote[1143].start 9116.59784375
transcript.pyannote[1143].end 9120.63096875
transcript.pyannote[1144].speaker SPEAKER_24
transcript.pyannote[1144].start 9120.19221875
transcript.pyannote[1144].end 9123.21284375
transcript.pyannote[1145].speaker SPEAKER_30
transcript.pyannote[1145].start 9122.23409375
transcript.pyannote[1145].end 9131.54909375
transcript.pyannote[1146].speaker SPEAKER_24
transcript.pyannote[1146].start 9130.46909375
transcript.pyannote[1146].end 9137.74221875
transcript.pyannote[1147].speaker SPEAKER_30
transcript.pyannote[1147].start 9135.46409375
transcript.pyannote[1147].end 9136.25721875
transcript.pyannote[1148].speaker SPEAKER_24
transcript.pyannote[1148].start 9138.07971875
transcript.pyannote[1148].end 9140.20596875
transcript.pyannote[1149].speaker SPEAKER_30
transcript.pyannote[1149].start 9140.20596875
transcript.pyannote[1149].end 9140.22284375
transcript.pyannote[1150].speaker SPEAKER_30
transcript.pyannote[1150].start 9140.23971875
transcript.pyannote[1150].end 9144.30659375
transcript.pyannote[1151].speaker SPEAKER_24
transcript.pyannote[1151].start 9144.30659375
transcript.pyannote[1151].end 9148.40721875
transcript.pyannote[1152].speaker SPEAKER_30
transcript.pyannote[1152].start 9148.01909375
transcript.pyannote[1152].end 9150.34784375
transcript.pyannote[1153].speaker SPEAKER_24
transcript.pyannote[1153].start 9150.34784375
transcript.pyannote[1153].end 9155.02221875
transcript.pyannote[1154].speaker SPEAKER_30
transcript.pyannote[1154].start 9153.97596875
transcript.pyannote[1154].end 9198.34034375
transcript.pyannote[1155].speaker SPEAKER_30
transcript.pyannote[1155].start 9198.37409375
transcript.pyannote[1155].end 9199.35284375
transcript.pyannote[1156].speaker SPEAKER_30
transcript.pyannote[1156].start 9199.57221875
transcript.pyannote[1156].end 9200.71971875
transcript.pyannote[1157].speaker SPEAKER_30
transcript.pyannote[1157].start 9200.88846875
transcript.pyannote[1157].end 9203.47034375
transcript.pyannote[1158].speaker SPEAKER_24
transcript.pyannote[1158].start 9203.47034375
transcript.pyannote[1158].end 9215.78909375
transcript.pyannote[1159].speaker SPEAKER_24
transcript.pyannote[1159].start 9216.29534375
transcript.pyannote[1159].end 9219.13034375
transcript.pyannote[1160].speaker SPEAKER_30
transcript.pyannote[1160].start 9220.05846875
transcript.pyannote[1160].end 9222.48846875
transcript.pyannote[1161].speaker SPEAKER_30
transcript.pyannote[1161].start 9223.01159375
transcript.pyannote[1161].end 9223.95659375
transcript.pyannote[1162].speaker SPEAKER_30
transcript.pyannote[1162].start 9224.96909375
transcript.pyannote[1162].end 9229.74471875
transcript.pyannote[1163].speaker SPEAKER_24
transcript.pyannote[1163].start 9229.74471875
transcript.pyannote[1163].end 9232.24221875
transcript.pyannote[1164].speaker SPEAKER_30
transcript.pyannote[1164].start 9229.81221875
transcript.pyannote[1164].end 9230.03159375
transcript.pyannote[1165].speaker SPEAKER_24
transcript.pyannote[1165].start 9232.76534375
transcript.pyannote[1165].end 9236.00534375
transcript.pyannote[1166].speaker SPEAKER_24
transcript.pyannote[1166].start 9236.83221875
transcript.pyannote[1166].end 9239.02596875
transcript.pyannote[1167].speaker SPEAKER_30
transcript.pyannote[1167].start 9239.02596875
transcript.pyannote[1167].end 9239.27909375
transcript.pyannote[1168].speaker SPEAKER_24
transcript.pyannote[1168].start 9239.24534375
transcript.pyannote[1168].end 9239.97096875
transcript.pyannote[1169].speaker SPEAKER_35
transcript.pyannote[1169].start 9239.27909375
transcript.pyannote[1169].end 9240.49409375
transcript.pyannote[1170].speaker SPEAKER_30
transcript.pyannote[1170].start 9239.97096875
transcript.pyannote[1170].end 9276.20159375
transcript.pyannote[1171].speaker SPEAKER_30
transcript.pyannote[1171].start 9276.96096875
transcript.pyannote[1171].end 9279.79596875
transcript.pyannote[1172].speaker SPEAKER_24
transcript.pyannote[1172].start 9279.79596875
transcript.pyannote[1172].end 9287.84534375
transcript.pyannote[1173].speaker SPEAKER_30
transcript.pyannote[1173].start 9288.94221875
transcript.pyannote[1173].end 9293.65034375
transcript.pyannote[1174].speaker SPEAKER_24
transcript.pyannote[1174].start 9293.16096875
transcript.pyannote[1174].end 9297.37971875
transcript.pyannote[1175].speaker SPEAKER_30
transcript.pyannote[1175].start 9295.13534375
transcript.pyannote[1175].end 9296.73846875
transcript.pyannote[1176].speaker SPEAKER_30
transcript.pyannote[1176].start 9297.00846875
transcript.pyannote[1176].end 9305.76659375
transcript.pyannote[1177].speaker SPEAKER_24
transcript.pyannote[1177].start 9301.02471875
transcript.pyannote[1177].end 9302.47596875
transcript.pyannote[1178].speaker SPEAKER_24
transcript.pyannote[1178].start 9304.85534375
transcript.pyannote[1178].end 9313.73159375
transcript.pyannote[1179].speaker SPEAKER_30
transcript.pyannote[1179].start 9307.11659375
transcript.pyannote[1179].end 9307.63971875
transcript.pyannote[1180].speaker SPEAKER_30
transcript.pyannote[1180].start 9312.16221875
transcript.pyannote[1180].end 9320.44784375
transcript.pyannote[1181].speaker SPEAKER_24
transcript.pyannote[1181].start 9316.51596875
transcript.pyannote[1181].end 9316.83659375
transcript.pyannote[1182].speaker SPEAKER_03
transcript.pyannote[1182].start 9316.83659375
transcript.pyannote[1182].end 9316.95471875
transcript.pyannote[1183].speaker SPEAKER_03
transcript.pyannote[1183].start 9318.70971875
transcript.pyannote[1183].end 9319.36784375
transcript.pyannote[1184].speaker SPEAKER_03
transcript.pyannote[1184].start 9319.41846875
transcript.pyannote[1184].end 9320.27909375
transcript.pyannote[1185].speaker SPEAKER_03
transcript.pyannote[1185].start 9321.69659375
transcript.pyannote[1185].end 9322.38846875
transcript.pyannote[1186].speaker SPEAKER_03
transcript.pyannote[1186].start 9326.37096875
transcript.pyannote[1186].end 9327.90659375
transcript.pyannote[1187].speaker SPEAKER_21
transcript.pyannote[1187].start 9335.36534375
transcript.pyannote[1187].end 9337.27221875
transcript.pyannote[1188].speaker SPEAKER_03
transcript.pyannote[1188].start 9337.35659375
transcript.pyannote[1188].end 9338.09909375
transcript.pyannote[1189].speaker SPEAKER_03
transcript.pyannote[1189].start 9343.14471875
transcript.pyannote[1189].end 9343.16159375
transcript.pyannote[1190].speaker SPEAKER_24
transcript.pyannote[1190].start 9343.16159375
transcript.pyannote[1190].end 9343.88721875
transcript.pyannote[1191].speaker SPEAKER_21
transcript.pyannote[1191].start 9343.92096875
transcript.pyannote[1191].end 9350.51909375
transcript.pyannote[1192].speaker SPEAKER_21
transcript.pyannote[1192].start 9351.04221875
transcript.pyannote[1192].end 9353.57346875
transcript.pyannote[1193].speaker SPEAKER_21
transcript.pyannote[1193].start 9354.01221875
transcript.pyannote[1193].end 9356.76284375
transcript.pyannote[1194].speaker SPEAKER_21
transcript.pyannote[1194].start 9357.53909375
transcript.pyannote[1194].end 9362.38221875
transcript.pyannote[1195].speaker SPEAKER_21
transcript.pyannote[1195].start 9362.73659375
transcript.pyannote[1195].end 9367.86659375
transcript.pyannote[1196].speaker SPEAKER_21
transcript.pyannote[1196].start 9368.05221875
transcript.pyannote[1196].end 9369.57096875
transcript.pyannote[1197].speaker SPEAKER_21
transcript.pyannote[1197].start 9370.44846875
transcript.pyannote[1197].end 9376.32096875
transcript.pyannote[1198].speaker SPEAKER_21
transcript.pyannote[1198].start 9376.81034375
transcript.pyannote[1198].end 9381.21471875
transcript.pyannote[1199].speaker SPEAKER_21
transcript.pyannote[1199].start 9381.72096875
transcript.pyannote[1199].end 9386.51346875
transcript.pyannote[1200].speaker SPEAKER_21
transcript.pyannote[1200].start 9387.57659375
transcript.pyannote[1200].end 9389.95596875
transcript.pyannote[1201].speaker SPEAKER_21
transcript.pyannote[1201].start 9390.73221875
transcript.pyannote[1201].end 9403.01721875
transcript.pyannote[1202].speaker SPEAKER_21
transcript.pyannote[1202].start 9404.11409375
transcript.pyannote[1202].end 9411.33659375
transcript.pyannote[1203].speaker SPEAKER_21
transcript.pyannote[1203].start 9411.60659375
transcript.pyannote[1203].end 9418.66034375
transcript.pyannote[1204].speaker SPEAKER_24
transcript.pyannote[1204].start 9420.16221875
transcript.pyannote[1204].end 9431.18159375
transcript.pyannote[1205].speaker SPEAKER_21
transcript.pyannote[1205].start 9423.73971875
transcript.pyannote[1205].end 9425.83221875
transcript.pyannote[1206].speaker SPEAKER_21
transcript.pyannote[1206].start 9427.16534375
transcript.pyannote[1206].end 9427.46909375
transcript.pyannote[1207].speaker SPEAKER_21
transcript.pyannote[1207].start 9431.41784375
transcript.pyannote[1207].end 9433.84784375
transcript.pyannote[1208].speaker SPEAKER_24
transcript.pyannote[1208].start 9434.94471875
transcript.pyannote[1208].end 9449.11971875
transcript.pyannote[1209].speaker SPEAKER_21
transcript.pyannote[1209].start 9437.88096875
transcript.pyannote[1209].end 9439.31534375
transcript.pyannote[1210].speaker SPEAKER_21
transcript.pyannote[1210].start 9447.55034375
transcript.pyannote[1210].end 9450.55409375
transcript.pyannote[1211].speaker SPEAKER_24
transcript.pyannote[1211].start 9451.11096875
transcript.pyannote[1211].end 9452.61284375
transcript.pyannote[1212].speaker SPEAKER_24
transcript.pyannote[1212].start 9452.83221875
transcript.pyannote[1212].end 9452.86596875
transcript.pyannote[1213].speaker SPEAKER_21
transcript.pyannote[1213].start 9452.86596875
transcript.pyannote[1213].end 9455.38034375
transcript.pyannote[1214].speaker SPEAKER_24
transcript.pyannote[1214].start 9453.20346875
transcript.pyannote[1214].end 9453.57471875
transcript.pyannote[1215].speaker SPEAKER_24
transcript.pyannote[1215].start 9454.43534375
transcript.pyannote[1215].end 9459.41346875
transcript.pyannote[1216].speaker SPEAKER_21
transcript.pyannote[1216].start 9456.35909375
transcript.pyannote[1216].end 9456.78096875
transcript.pyannote[1217].speaker SPEAKER_24
transcript.pyannote[1217].start 9459.53159375
transcript.pyannote[1217].end 9462.46784375
transcript.pyannote[1218].speaker SPEAKER_21
transcript.pyannote[1218].start 9464.08784375
transcript.pyannote[1218].end 9466.31534375
transcript.pyannote[1219].speaker SPEAKER_21
transcript.pyannote[1219].start 9466.97346875
transcript.pyannote[1219].end 9471.04034375
transcript.pyannote[1220].speaker SPEAKER_21
transcript.pyannote[1220].start 9471.71534375
transcript.pyannote[1220].end 9482.49846875
transcript.pyannote[1221].speaker SPEAKER_21
transcript.pyannote[1221].start 9482.86971875
transcript.pyannote[1221].end 9486.83534375
transcript.pyannote[1222].speaker SPEAKER_21
transcript.pyannote[1222].start 9487.57784375
transcript.pyannote[1222].end 9490.81784375
transcript.pyannote[1223].speaker SPEAKER_21
transcript.pyannote[1223].start 9491.44221875
transcript.pyannote[1223].end 9496.58909375
transcript.pyannote[1224].speaker SPEAKER_21
transcript.pyannote[1224].start 9496.99409375
transcript.pyannote[1224].end 9499.03596875
transcript.pyannote[1225].speaker SPEAKER_21
transcript.pyannote[1225].start 9499.49159375
transcript.pyannote[1225].end 9501.51659375
transcript.pyannote[1226].speaker SPEAKER_21
transcript.pyannote[1226].start 9502.14096875
transcript.pyannote[1226].end 9524.31471875
transcript.pyannote[1227].speaker SPEAKER_21
transcript.pyannote[1227].start 9524.50034375
transcript.pyannote[1227].end 9530.94659375
transcript.pyannote[1228].speaker SPEAKER_24
transcript.pyannote[1228].start 9532.14471875
transcript.pyannote[1228].end 9535.19909375
transcript.pyannote[1229].speaker SPEAKER_21
transcript.pyannote[1229].start 9534.13596875
transcript.pyannote[1229].end 9537.86534375
transcript.pyannote[1230].speaker SPEAKER_24
transcript.pyannote[1230].start 9535.24971875
transcript.pyannote[1230].end 9535.26659375
transcript.pyannote[1231].speaker SPEAKER_24
transcript.pyannote[1231].start 9535.65471875
transcript.pyannote[1231].end 9537.84846875
transcript.pyannote[1232].speaker SPEAKER_24
transcript.pyannote[1232].start 9537.86534375
transcript.pyannote[1232].end 9559.31346875
transcript.pyannote[1233].speaker SPEAKER_21
transcript.pyannote[1233].start 9560.12346875
transcript.pyannote[1233].end 9567.66659375
transcript.pyannote[1234].speaker SPEAKER_29
transcript.pyannote[1234].start 9564.67971875
transcript.pyannote[1234].end 9564.73034375
transcript.pyannote[1235].speaker SPEAKER_24
transcript.pyannote[1235].start 9564.73034375
transcript.pyannote[1235].end 9564.81471875
transcript.pyannote[1236].speaker SPEAKER_29
transcript.pyannote[1236].start 9564.81471875
transcript.pyannote[1236].end 9564.84846875
transcript.pyannote[1237].speaker SPEAKER_24
transcript.pyannote[1237].start 9564.84846875
transcript.pyannote[1237].end 9564.86534375
transcript.pyannote[1238].speaker SPEAKER_21
transcript.pyannote[1238].start 9568.03784375
transcript.pyannote[1238].end 9572.74596875
transcript.pyannote[1239].speaker SPEAKER_21
transcript.pyannote[1239].start 9573.11721875
transcript.pyannote[1239].end 9577.92659375
transcript.pyannote[1240].speaker SPEAKER_21
transcript.pyannote[1240].start 9578.78721875
transcript.pyannote[1240].end 9580.03596875
transcript.pyannote[1241].speaker SPEAKER_24
transcript.pyannote[1241].start 9580.03596875
transcript.pyannote[1241].end 9601.70346875
transcript.pyannote[1242].speaker SPEAKER_21
transcript.pyannote[1242].start 9587.39346875
transcript.pyannote[1242].end 9590.76846875
transcript.pyannote[1243].speaker SPEAKER_21
transcript.pyannote[1243].start 9591.42659375
transcript.pyannote[1243].end 9602.56409375
transcript.pyannote[1244].speaker SPEAKER_21
transcript.pyannote[1244].start 9603.07034375
transcript.pyannote[1244].end 9605.33159375
transcript.pyannote[1245].speaker SPEAKER_21
transcript.pyannote[1245].start 9605.61846875
transcript.pyannote[1245].end 9607.12034375
transcript.pyannote[1246].speaker SPEAKER_21
transcript.pyannote[1246].start 9608.03159375
transcript.pyannote[1246].end 9609.92159375
transcript.pyannote[1247].speaker SPEAKER_21
transcript.pyannote[1247].start 9610.46159375
transcript.pyannote[1247].end 9611.60909375
transcript.pyannote[1248].speaker SPEAKER_21
transcript.pyannote[1248].start 9612.09846875
transcript.pyannote[1248].end 9615.30471875
transcript.pyannote[1249].speaker SPEAKER_21
transcript.pyannote[1249].start 9617.98784375
transcript.pyannote[1249].end 9619.45596875
transcript.pyannote[1250].speaker SPEAKER_21
transcript.pyannote[1250].start 9619.65846875
transcript.pyannote[1250].end 9622.51034375
transcript.pyannote[1251].speaker SPEAKER_21
transcript.pyannote[1251].start 9623.03346875
transcript.pyannote[1251].end 9627.87659375
transcript.pyannote[1252].speaker SPEAKER_21
transcript.pyannote[1252].start 9628.34909375
transcript.pyannote[1252].end 9634.81221875
transcript.pyannote[1253].speaker SPEAKER_21
transcript.pyannote[1253].start 9635.35221875
transcript.pyannote[1253].end 9641.56221875
transcript.pyannote[1254].speaker SPEAKER_21
transcript.pyannote[1254].start 9641.95034375
transcript.pyannote[1254].end 9648.93659375
transcript.pyannote[1255].speaker SPEAKER_21
transcript.pyannote[1255].start 9649.76346875
transcript.pyannote[1255].end 9652.26096875
transcript.pyannote[1256].speaker SPEAKER_21
transcript.pyannote[1256].start 9652.93596875
transcript.pyannote[1256].end 9655.55159375
transcript.pyannote[1257].speaker SPEAKER_21
transcript.pyannote[1257].start 9656.05784375
transcript.pyannote[1257].end 9657.34034375
transcript.pyannote[1258].speaker SPEAKER_21
transcript.pyannote[1258].start 9657.86346875
transcript.pyannote[1258].end 9660.25971875
transcript.pyannote[1259].speaker SPEAKER_21
transcript.pyannote[1259].start 9661.03596875
transcript.pyannote[1259].end 9662.58846875
transcript.pyannote[1260].speaker SPEAKER_21
transcript.pyannote[1260].start 9662.92596875
transcript.pyannote[1260].end 9669.84471875
transcript.pyannote[1261].speaker SPEAKER_21
transcript.pyannote[1261].start 9670.35096875
transcript.pyannote[1261].end 9674.85659375
transcript.pyannote[1262].speaker SPEAKER_21
transcript.pyannote[1262].start 9675.14346875
transcript.pyannote[1262].end 9677.97846875
transcript.pyannote[1263].speaker SPEAKER_21
transcript.pyannote[1263].start 9678.09659375
transcript.pyannote[1263].end 9680.10471875
transcript.pyannote[1264].speaker SPEAKER_21
transcript.pyannote[1264].start 9680.61096875
transcript.pyannote[1264].end 9693.33471875
transcript.pyannote[1265].speaker SPEAKER_24
transcript.pyannote[1265].start 9694.33034375
transcript.pyannote[1265].end 9703.89846875
transcript.pyannote[1266].speaker SPEAKER_21
transcript.pyannote[1266].start 9698.21159375
transcript.pyannote[1266].end 9698.43096875
transcript.pyannote[1267].speaker SPEAKER_21
transcript.pyannote[1267].start 9703.89846875
transcript.pyannote[1267].end 9712.69034375
transcript.pyannote[1268].speaker SPEAKER_24
transcript.pyannote[1268].start 9704.99534375
transcript.pyannote[1268].end 9709.53471875
transcript.pyannote[1269].speaker SPEAKER_24
transcript.pyannote[1269].start 9710.51346875
transcript.pyannote[1269].end 9711.91409375
transcript.pyannote[1270].speaker SPEAKER_21
transcript.pyannote[1270].start 9712.87596875
transcript.pyannote[1270].end 9717.90471875
transcript.pyannote[1271].speaker SPEAKER_24
transcript.pyannote[1271].start 9717.90471875
transcript.pyannote[1271].end 9718.30971875
transcript.pyannote[1272].speaker SPEAKER_21
transcript.pyannote[1272].start 9718.30971875
transcript.pyannote[1272].end 9722.47784375
transcript.pyannote[1273].speaker SPEAKER_24
transcript.pyannote[1273].start 9718.44471875
transcript.pyannote[1273].end 9723.89534375
transcript.pyannote[1274].speaker SPEAKER_21
transcript.pyannote[1274].start 9722.76471875
transcript.pyannote[1274].end 9731.21909375
transcript.pyannote[1275].speaker SPEAKER_21
transcript.pyannote[1275].start 9733.53096875
transcript.pyannote[1275].end 9738.62721875
transcript.pyannote[1276].speaker SPEAKER_21
transcript.pyannote[1276].start 9739.36971875
transcript.pyannote[1276].end 9743.75721875
transcript.pyannote[1277].speaker SPEAKER_21
transcript.pyannote[1277].start 9745.17471875
transcript.pyannote[1277].end 9746.84534375
transcript.pyannote[1278].speaker SPEAKER_21
transcript.pyannote[1278].start 9747.25034375
transcript.pyannote[1278].end 9748.17846875
transcript.pyannote[1279].speaker SPEAKER_21
transcript.pyannote[1279].start 9748.76909375
transcript.pyannote[1279].end 9750.40596875
transcript.pyannote[1280].speaker SPEAKER_21
transcript.pyannote[1280].start 9750.96284375
transcript.pyannote[1280].end 9753.84846875
transcript.pyannote[1281].speaker SPEAKER_21
transcript.pyannote[1281].start 9754.27034375
transcript.pyannote[1281].end 9785.40471875
transcript.pyannote[1282].speaker SPEAKER_09
transcript.pyannote[1282].start 9786.33284375
transcript.pyannote[1282].end 9806.51534375
transcript.pyannote[1283].speaker SPEAKER_21
transcript.pyannote[1283].start 9804.50721875
transcript.pyannote[1283].end 9821.14596875
transcript.pyannote[1284].speaker SPEAKER_09
transcript.pyannote[1284].start 9807.15659375
transcript.pyannote[1284].end 9809.50221875
transcript.pyannote[1285].speaker SPEAKER_09
transcript.pyannote[1285].start 9821.26409375
transcript.pyannote[1285].end 9834.42659375
transcript.pyannote[1286].speaker SPEAKER_21
transcript.pyannote[1286].start 9833.81909375
transcript.pyannote[1286].end 9835.48971875
transcript.pyannote[1287].speaker SPEAKER_09
transcript.pyannote[1287].start 9835.32096875
transcript.pyannote[1287].end 9836.04659375
transcript.pyannote[1288].speaker SPEAKER_21
transcript.pyannote[1288].start 9835.94534375
transcript.pyannote[1288].end 9840.34971875
transcript.pyannote[1289].speaker SPEAKER_09
transcript.pyannote[1289].start 9841.34534375
transcript.pyannote[1289].end 9847.20096875
transcript.pyannote[1290].speaker SPEAKER_21
transcript.pyannote[1290].start 9845.54721875
transcript.pyannote[1290].end 9846.72846875
transcript.pyannote[1291].speaker SPEAKER_21
transcript.pyannote[1291].start 9847.62284375
transcript.pyannote[1291].end 9849.91784375
transcript.pyannote[1292].speaker SPEAKER_21
transcript.pyannote[1292].start 9850.91346875
transcript.pyannote[1292].end 9855.84096875
transcript.pyannote[1293].speaker SPEAKER_28
transcript.pyannote[1293].start 9856.58346875
transcript.pyannote[1293].end 9871.02846875
transcript.pyannote[1294].speaker SPEAKER_28
transcript.pyannote[1294].start 9871.21409375
transcript.pyannote[1294].end 9875.95596875
transcript.pyannote[1295].speaker SPEAKER_21
transcript.pyannote[1295].start 9873.05346875
transcript.pyannote[1295].end 9886.58721875
transcript.pyannote[1296].speaker SPEAKER_28
transcript.pyannote[1296].start 9882.50346875
transcript.pyannote[1296].end 9883.70159375
transcript.pyannote[1297].speaker SPEAKER_28
transcript.pyannote[1297].start 9887.16096875
transcript.pyannote[1297].end 9892.39221875
transcript.pyannote[1298].speaker SPEAKER_21
transcript.pyannote[1298].start 9892.99971875
transcript.pyannote[1298].end 9893.33721875
transcript.pyannote[1299].speaker SPEAKER_21
transcript.pyannote[1299].start 9893.82659375
transcript.pyannote[1299].end 9895.07534375
transcript.pyannote[1300].speaker SPEAKER_24
transcript.pyannote[1300].start 9895.44659375
transcript.pyannote[1300].end 9896.67846875
transcript.pyannote[1301].speaker SPEAKER_21
transcript.pyannote[1301].start 9896.37471875
transcript.pyannote[1301].end 9897.23534375
transcript.pyannote[1302].speaker SPEAKER_21
transcript.pyannote[1302].start 9897.45471875
transcript.pyannote[1302].end 9898.61909375
transcript.pyannote[1303].speaker SPEAKER_21
transcript.pyannote[1303].start 9899.36159375
transcript.pyannote[1303].end 9900.72846875
transcript.pyannote[1304].speaker SPEAKER_21
transcript.pyannote[1304].start 9901.33596875
transcript.pyannote[1304].end 9902.56784375
transcript.pyannote[1305].speaker SPEAKER_21
transcript.pyannote[1305].start 9903.86721875
transcript.pyannote[1305].end 9908.35596875
transcript.pyannote[1306].speaker SPEAKER_21
transcript.pyannote[1306].start 9909.09846875
transcript.pyannote[1306].end 9931.64346875
transcript.pyannote[1307].speaker SPEAKER_21
transcript.pyannote[1307].start 9931.72784375
transcript.pyannote[1307].end 9943.96221875
transcript.pyannote[1308].speaker SPEAKER_21
transcript.pyannote[1308].start 9945.02534375
transcript.pyannote[1308].end 9945.53159375
transcript.pyannote[1309].speaker SPEAKER_24
transcript.pyannote[1309].start 9945.07596875
transcript.pyannote[1309].end 9945.44721875
transcript.pyannote[1310].speaker SPEAKER_24
transcript.pyannote[1310].start 9945.53159375
transcript.pyannote[1310].end 9945.56534375
transcript.pyannote[1311].speaker SPEAKER_24
transcript.pyannote[1311].start 9945.85221875
transcript.pyannote[1311].end 9952.28159375
transcript.pyannote[1312].speaker SPEAKER_21
transcript.pyannote[1312].start 9950.74596875
transcript.pyannote[1312].end 9951.97784375
transcript.pyannote[1313].speaker SPEAKER_21
transcript.pyannote[1313].start 9952.28159375
transcript.pyannote[1313].end 9952.50096875
transcript.pyannote[1314].speaker SPEAKER_24
transcript.pyannote[1314].start 9952.50096875
transcript.pyannote[1314].end 9953.96909375
transcript.pyannote[1315].speaker SPEAKER_21
transcript.pyannote[1315].start 9952.56846875
transcript.pyannote[1315].end 9954.39096875
transcript.pyannote[1316].speaker SPEAKER_22
transcript.pyannote[1316].start 9953.96909375
transcript.pyannote[1316].end 9954.03659375
transcript.pyannote[1317].speaker SPEAKER_24
transcript.pyannote[1317].start 9954.03659375
transcript.pyannote[1317].end 9954.05346875
transcript.pyannote[1318].speaker SPEAKER_22
transcript.pyannote[1318].start 9954.79596875
transcript.pyannote[1318].end 9954.89721875
transcript.pyannote[1319].speaker SPEAKER_24
transcript.pyannote[1319].start 9954.89721875
transcript.pyannote[1319].end 9954.93096875
transcript.pyannote[1320].speaker SPEAKER_22
transcript.pyannote[1320].start 9954.93096875
transcript.pyannote[1320].end 9955.01534375
transcript.pyannote[1321].speaker SPEAKER_21
transcript.pyannote[1321].start 9955.01534375
transcript.pyannote[1321].end 9956.48346875
transcript.pyannote[1322].speaker SPEAKER_21
transcript.pyannote[1322].start 9957.15846875
transcript.pyannote[1322].end 9962.76096875
transcript.pyannote[1323].speaker SPEAKER_21
transcript.pyannote[1323].start 9963.19971875
transcript.pyannote[1323].end 9966.81096875
transcript.pyannote[1324].speaker SPEAKER_21
transcript.pyannote[1324].start 9967.26659375
transcript.pyannote[1324].end 9971.31659375
transcript.pyannote[1325].speaker SPEAKER_21
transcript.pyannote[1325].start 9971.68784375
transcript.pyannote[1325].end 9983.53409375
transcript.pyannote[1326].speaker SPEAKER_24
transcript.pyannote[1326].start 9982.79159375
transcript.pyannote[1326].end 9982.90971875
transcript.pyannote[1327].speaker SPEAKER_24
transcript.pyannote[1327].start 9984.14159375
transcript.pyannote[1327].end 9986.45346875
transcript.pyannote[1328].speaker SPEAKER_21
transcript.pyannote[1328].start 9986.23409375
transcript.pyannote[1328].end 9987.98909375
transcript.pyannote[1329].speaker SPEAKER_21
transcript.pyannote[1329].start 9988.32659375
transcript.pyannote[1329].end 9989.69346875
transcript.pyannote[1330].speaker SPEAKER_21
transcript.pyannote[1330].start 9990.36846875
transcript.pyannote[1330].end 9992.61284375
transcript.pyannote[1331].speaker SPEAKER_21
transcript.pyannote[1331].start 9993.30471875
transcript.pyannote[1331].end 9994.68846875
transcript.pyannote[1332].speaker SPEAKER_21
transcript.pyannote[1332].start 9994.87409375
transcript.pyannote[1332].end 9996.46034375
transcript.pyannote[1333].speaker SPEAKER_21
transcript.pyannote[1333].start 9997.57409375
transcript.pyannote[1333].end 9999.41346875
transcript.pyannote[1334].speaker SPEAKER_21
transcript.pyannote[1334].start 10000.44284375
transcript.pyannote[1334].end 10010.02784375
transcript.pyannote[1335].speaker SPEAKER_24
transcript.pyannote[1335].start 10010.02784375
transcript.pyannote[1335].end 10019.05596875
transcript.pyannote[1336].speaker SPEAKER_29
transcript.pyannote[1336].start 10019.37659375
transcript.pyannote[1336].end 10019.52846875
transcript.pyannote[1337].speaker SPEAKER_24
transcript.pyannote[1337].start 10019.52846875
transcript.pyannote[1337].end 10023.44346875
transcript.pyannote[1338].speaker SPEAKER_24
transcript.pyannote[1338].start 10023.52784375
transcript.pyannote[1338].end 10023.94971875
transcript.pyannote[1339].speaker SPEAKER_21
transcript.pyannote[1339].start 10023.94971875
transcript.pyannote[1339].end 10023.96659375
transcript.pyannote[1340].speaker SPEAKER_24
transcript.pyannote[1340].start 10025.40096875
transcript.pyannote[1340].end 10025.41784375
transcript.pyannote[1341].speaker SPEAKER_21
transcript.pyannote[1341].start 10025.41784375
transcript.pyannote[1341].end 10026.75096875
transcript.pyannote[1342].speaker SPEAKER_21
transcript.pyannote[1342].start 10027.74659375
transcript.pyannote[1342].end 10031.03721875
transcript.pyannote[1343].speaker SPEAKER_24
transcript.pyannote[1343].start 10031.49284375
transcript.pyannote[1343].end 10041.07784375
transcript.pyannote[1344].speaker SPEAKER_03
transcript.pyannote[1344].start 10043.33909375
transcript.pyannote[1344].end 10046.68034375
transcript.pyannote[1345].speaker SPEAKER_31
transcript.pyannote[1345].start 10060.04534375
transcript.pyannote[1345].end 10063.28534375
transcript.pyannote[1346].speaker SPEAKER_03
transcript.pyannote[1346].start 10060.50096875
transcript.pyannote[1346].end 10060.63596875
transcript.pyannote[1347].speaker SPEAKER_03
transcript.pyannote[1347].start 10063.65659375
transcript.pyannote[1347].end 10064.19659375
transcript.pyannote[1348].speaker SPEAKER_31
transcript.pyannote[1348].start 10068.16221875
transcript.pyannote[1348].end 10068.17909375
transcript.pyannote[1349].speaker SPEAKER_03
transcript.pyannote[1349].start 10068.17909375
transcript.pyannote[1349].end 10068.41534375
transcript.pyannote[1350].speaker SPEAKER_03
transcript.pyannote[1350].start 10068.60096875
transcript.pyannote[1350].end 10068.61784375
transcript.pyannote[1351].speaker SPEAKER_31
transcript.pyannote[1351].start 10068.61784375
transcript.pyannote[1351].end 10132.79346875
transcript.pyannote[1352].speaker SPEAKER_03
transcript.pyannote[1352].start 10068.70221875
transcript.pyannote[1352].end 10069.32659375
transcript.pyannote[1353].speaker SPEAKER_31
transcript.pyannote[1353].start 10133.46846875
transcript.pyannote[1353].end 10157.75159375
transcript.pyannote[1354].speaker SPEAKER_31
transcript.pyannote[1354].start 10158.17346875
transcript.pyannote[1354].end 10239.89909375
transcript.pyannote[1355].speaker SPEAKER_24
transcript.pyannote[1355].start 10240.69221875
transcript.pyannote[1355].end 10257.02721875
transcript.pyannote[1356].speaker SPEAKER_31
transcript.pyannote[1356].start 10257.68534375
transcript.pyannote[1356].end 10275.62346875
transcript.pyannote[1357].speaker SPEAKER_31
transcript.pyannote[1357].start 10275.75846875
transcript.pyannote[1357].end 10285.93409375
transcript.pyannote[1358].speaker SPEAKER_00
transcript.pyannote[1358].start 10279.38659375
transcript.pyannote[1358].end 10279.75784375
transcript.pyannote[1359].speaker SPEAKER_31
transcript.pyannote[1359].start 10286.08596875
transcript.pyannote[1359].end 10415.21346875
transcript.pyannote[1360].speaker SPEAKER_31
transcript.pyannote[1360].start 10415.83784375
transcript.pyannote[1360].end 10503.41909375
transcript.pyannote[1361].speaker SPEAKER_24
transcript.pyannote[1361].start 10503.50346875
transcript.pyannote[1361].end 10503.63846875
transcript.pyannote[1362].speaker SPEAKER_24
transcript.pyannote[1362].start 10504.02659375
transcript.pyannote[1362].end 10553.25096875
transcript.pyannote[1363].speaker SPEAKER_24
transcript.pyannote[1363].start 10553.67284375
transcript.pyannote[1363].end 10573.85534375
transcript.pyannote[1364].speaker SPEAKER_24
transcript.pyannote[1364].start 10574.12534375
transcript.pyannote[1364].end 10602.25596875
transcript.pyannote[1365].speaker SPEAKER_24
transcript.pyannote[1365].start 10603.18409375
transcript.pyannote[1365].end 10613.30909375
transcript.pyannote[1366].speaker SPEAKER_24
transcript.pyannote[1366].start 10613.47784375
transcript.pyannote[1366].end 10653.08346875
transcript.pyannote[1367].speaker SPEAKER_24
transcript.pyannote[1367].start 10653.15096875
transcript.pyannote[1367].end 10653.57284375
transcript.pyannote[1368].speaker SPEAKER_31
transcript.pyannote[1368].start 10653.65721875
transcript.pyannote[1368].end 10727.87346875
transcript.pyannote[1369].speaker SPEAKER_29
transcript.pyannote[1369].start 10681.80471875
transcript.pyannote[1369].end 10682.15909375
transcript.pyannote[1370].speaker SPEAKER_24
transcript.pyannote[1370].start 10727.95784375
transcript.pyannote[1370].end 10741.03596875
transcript.pyannote[1371].speaker SPEAKER_24
transcript.pyannote[1371].start 10741.35659375
transcript.pyannote[1371].end 10747.36409375
transcript.pyannote[1372].speaker SPEAKER_31
transcript.pyannote[1372].start 10747.36409375
transcript.pyannote[1372].end 10816.09596875
transcript.pyannote[1373].speaker SPEAKER_24
transcript.pyannote[1373].start 10816.55159375
transcript.pyannote[1373].end 10862.11409375
transcript.pyannote[1374].speaker SPEAKER_31
transcript.pyannote[1374].start 10862.26596875
transcript.pyannote[1374].end 10878.28034375
transcript.pyannote[1375].speaker SPEAKER_24
transcript.pyannote[1375].start 10878.17909375
transcript.pyannote[1375].end 10898.58096875
transcript.pyannote[1376].speaker SPEAKER_31
transcript.pyannote[1376].start 10898.74971875
transcript.pyannote[1376].end 10900.67346875
transcript.pyannote[1377].speaker SPEAKER_03
transcript.pyannote[1377].start 10900.67346875
transcript.pyannote[1377].end 10910.27534375
transcript.pyannote[1378].speaker SPEAKER_03
transcript.pyannote[1378].start 10911.49034375
transcript.pyannote[1378].end 10914.44346875
transcript.pyannote[1379].speaker SPEAKER_03
transcript.pyannote[1379].start 10914.86534375
transcript.pyannote[1379].end 10917.80159375
transcript.pyannote[1380].speaker SPEAKER_29
transcript.pyannote[1380].start 10917.98721875
transcript.pyannote[1380].end 10918.03784375
transcript.pyannote[1381].speaker SPEAKER_03
transcript.pyannote[1381].start 10919.37096875
transcript.pyannote[1381].end 10921.51409375
transcript.pyannote[1382].speaker SPEAKER_03
transcript.pyannote[1382].start 10921.69971875
transcript.pyannote[1382].end 10921.75034375
transcript.pyannote[1383].speaker SPEAKER_03
transcript.pyannote[1383].start 10921.95284375
transcript.pyannote[1383].end 10922.32409375
transcript.pyannote[1384].speaker SPEAKER_03
transcript.pyannote[1384].start 10924.24784375
transcript.pyannote[1384].end 10926.52596875
transcript.pyannote[1385].speaker SPEAKER_18
transcript.pyannote[1385].start 10927.20096875
transcript.pyannote[1385].end 10953.25596875
transcript.pyannote[1386].speaker SPEAKER_18
transcript.pyannote[1386].start 10953.59346875
transcript.pyannote[1386].end 10959.02721875
transcript.pyannote[1387].speaker SPEAKER_18
transcript.pyannote[1387].start 10959.16221875
transcript.pyannote[1387].end 10961.98034375
transcript.pyannote[1388].speaker SPEAKER_18
transcript.pyannote[1388].start 10962.28409375
transcript.pyannote[1388].end 10971.61596875
transcript.pyannote[1389].speaker SPEAKER_03
transcript.pyannote[1389].start 10972.67909375
transcript.pyannote[1389].end 10974.63659375
transcript.pyannote[1390].speaker SPEAKER_03
transcript.pyannote[1390].start 10976.10471875
transcript.pyannote[1390].end 10977.20159375
transcript.pyannote[1391].speaker SPEAKER_14
transcript.pyannote[1391].start 11006.58096875
transcript.pyannote[1391].end 11027.75909375
transcript.pyannote[1392].speaker SPEAKER_14
transcript.pyannote[1392].start 11027.80971875
transcript.pyannote[1392].end 11034.66096875
transcript.pyannote[1393].speaker SPEAKER_14
transcript.pyannote[1393].start 11034.81284375
transcript.pyannote[1393].end 11040.19596875
transcript.pyannote[1394].speaker SPEAKER_14
transcript.pyannote[1394].start 11040.33096875
transcript.pyannote[1394].end 11046.18659375
transcript.pyannote[1395].speaker SPEAKER_14
transcript.pyannote[1395].start 11046.43971875
transcript.pyannote[1395].end 11051.06346875
transcript.pyannote[1396].speaker SPEAKER_14
transcript.pyannote[1396].start 11051.36721875
transcript.pyannote[1396].end 11052.53159375
transcript.pyannote[1397].speaker SPEAKER_14
transcript.pyannote[1397].start 11052.73409375
transcript.pyannote[1397].end 11055.23159375
transcript.pyannote[1398].speaker SPEAKER_14
transcript.pyannote[1398].start 11055.41721875
transcript.pyannote[1398].end 11059.51784375
transcript.pyannote[1399].speaker SPEAKER_14
transcript.pyannote[1399].start 11059.75409375
transcript.pyannote[1399].end 11062.13346875
transcript.pyannote[1400].speaker SPEAKER_14
transcript.pyannote[1400].start 11063.21346875
transcript.pyannote[1400].end 11065.98096875
transcript.pyannote[1401].speaker SPEAKER_14
transcript.pyannote[1401].start 11066.28471875
transcript.pyannote[1401].end 11066.79096875
transcript.pyannote[1402].speaker SPEAKER_14
transcript.pyannote[1402].start 11066.84159375
transcript.pyannote[1402].end 11073.49034375
transcript.pyannote[1403].speaker SPEAKER_03
transcript.pyannote[1403].start 11074.72221875
transcript.pyannote[1403].end 11079.34596875
transcript.pyannote[1404].speaker SPEAKER_24
transcript.pyannote[1404].start 11077.55721875
transcript.pyannote[1404].end 11079.21096875
transcript.pyannote[1405].speaker SPEAKER_03
transcript.pyannote[1405].start 11079.66659375
transcript.pyannote[1405].end 11081.03346875
transcript.pyannote[1406].speaker SPEAKER_24
transcript.pyannote[1406].start 11080.66221875
transcript.pyannote[1406].end 11086.75409375
transcript.pyannote[1407].speaker SPEAKER_24
transcript.pyannote[1407].start 11087.34471875
transcript.pyannote[1407].end 11089.28534375
transcript.pyannote[1408].speaker SPEAKER_24
transcript.pyannote[1408].start 11089.43721875
transcript.pyannote[1408].end 11092.62659375
transcript.pyannote[1409].speaker SPEAKER_24
transcript.pyannote[1409].start 11093.01471875
transcript.pyannote[1409].end 11097.70596875
transcript.pyannote[1410].speaker SPEAKER_24
transcript.pyannote[1410].start 11098.09409375
transcript.pyannote[1410].end 11099.56221875
transcript.pyannote[1411].speaker SPEAKER_24
transcript.pyannote[1411].start 11100.05159375
transcript.pyannote[1411].end 11101.40159375
transcript.pyannote[1412].speaker SPEAKER_24
transcript.pyannote[1412].start 11101.73909375
transcript.pyannote[1412].end 11142.71159375
transcript.pyannote[1413].speaker SPEAKER_24
transcript.pyannote[1413].start 11143.16721875
transcript.pyannote[1413].end 11148.38159375
transcript.pyannote[1414].speaker SPEAKER_24
transcript.pyannote[1414].start 11148.53346875
transcript.pyannote[1414].end 11148.92159375
transcript.pyannote[1415].speaker SPEAKER_24
transcript.pyannote[1415].start 11149.52909375
transcript.pyannote[1415].end 11156.61659375
transcript.pyannote[1416].speaker SPEAKER_19
transcript.pyannote[1416].start 11157.40971875
transcript.pyannote[1416].end 11157.56159375
transcript.pyannote[1417].speaker SPEAKER_19
transcript.pyannote[1417].start 11157.76409375
transcript.pyannote[1417].end 11159.62034375
transcript.pyannote[1418].speaker SPEAKER_24
transcript.pyannote[1418].start 11157.91596875
transcript.pyannote[1418].end 11158.27034375
transcript.pyannote[1419].speaker SPEAKER_24
transcript.pyannote[1419].start 11159.75534375
transcript.pyannote[1419].end 11159.78909375
transcript.pyannote[1420].speaker SPEAKER_03
transcript.pyannote[1420].start 11159.78909375
transcript.pyannote[1420].end 11160.51471875
transcript.pyannote[1421].speaker SPEAKER_19
transcript.pyannote[1421].start 11160.17721875
transcript.pyannote[1421].end 11162.91096875
transcript.pyannote[1422].speaker SPEAKER_24
transcript.pyannote[1422].start 11160.51471875
transcript.pyannote[1422].end 11160.68346875
transcript.pyannote[1423].speaker SPEAKER_03
transcript.pyannote[1423].start 11160.68346875
transcript.pyannote[1423].end 11160.71721875
transcript.pyannote[1424].speaker SPEAKER_24
transcript.pyannote[1424].start 11160.71721875
transcript.pyannote[1424].end 11160.86909375
transcript.pyannote[1425].speaker SPEAKER_03
transcript.pyannote[1425].start 11160.86909375
transcript.pyannote[1425].end 11160.91971875
transcript.pyannote[1426].speaker SPEAKER_19
transcript.pyannote[1426].start 11163.23159375
transcript.pyannote[1426].end 11166.87659375
transcript.pyannote[1427].speaker SPEAKER_03
transcript.pyannote[1427].start 11167.19721875
transcript.pyannote[1427].end 11171.44971875
transcript.pyannote[1428].speaker SPEAKER_03
transcript.pyannote[1428].start 11171.68596875
transcript.pyannote[1428].end 11171.87159375
transcript.pyannote[1429].speaker SPEAKER_24
transcript.pyannote[1429].start 11173.52534375
transcript.pyannote[1429].end 11173.54221875
transcript.pyannote[1430].speaker SPEAKER_03
transcript.pyannote[1430].start 11174.63909375
transcript.pyannote[1430].end 11175.28034375
transcript.pyannote[1431].speaker SPEAKER_24
transcript.pyannote[1431].start 11174.79096875
transcript.pyannote[1431].end 11179.22909375
transcript.pyannote[1432].speaker SPEAKER_03
transcript.pyannote[1432].start 11178.36846875
transcript.pyannote[1432].end 11178.80721875
transcript.pyannote[1433].speaker SPEAKER_03
transcript.pyannote[1433].start 11181.35534375
transcript.pyannote[1433].end 11181.69284375
transcript.pyannote[1434].speaker SPEAKER_03
transcript.pyannote[1434].start 11181.94596875
transcript.pyannote[1434].end 11183.85284375
transcript.pyannote[1435].speaker SPEAKER_03
transcript.pyannote[1435].start 11184.71346875
transcript.pyannote[1435].end 11185.59096875
transcript.pyannote[1436].speaker SPEAKER_03
transcript.pyannote[1436].start 11186.80596875
transcript.pyannote[1436].end 11188.30784375
transcript.pyannote[1437].speaker SPEAKER_29
transcript.pyannote[1437].start 11190.50159375
transcript.pyannote[1437].end 11190.60284375
transcript.pyannote[1438].speaker SPEAKER_03
transcript.pyannote[1438].start 11194.95659375
transcript.pyannote[1438].end 11195.74971875
transcript.pyannote[1439].speaker SPEAKER_18
transcript.pyannote[1439].start 11199.17534375
transcript.pyannote[1439].end 11201.65596875
transcript.pyannote[1440].speaker SPEAKER_18
transcript.pyannote[1440].start 11203.09034375
transcript.pyannote[1440].end 11204.67659375
transcript.pyannote[1441].speaker SPEAKER_18
transcript.pyannote[1441].start 11205.16596875
transcript.pyannote[1441].end 11210.09346875
transcript.pyannote[1442].speaker SPEAKER_18
transcript.pyannote[1442].start 11210.46471875
transcript.pyannote[1442].end 11215.81409375
transcript.pyannote[1443].speaker SPEAKER_18
transcript.pyannote[1443].start 11216.89409375
transcript.pyannote[1443].end 11217.70409375
transcript.pyannote[1444].speaker SPEAKER_18
transcript.pyannote[1444].start 11217.92346875
transcript.pyannote[1444].end 11219.17221875
transcript.pyannote[1445].speaker SPEAKER_18
transcript.pyannote[1445].start 11220.20159375
transcript.pyannote[1445].end 11223.35721875
transcript.pyannote[1446].speaker SPEAKER_18
transcript.pyannote[1446].start 11223.99846875
transcript.pyannote[1446].end 11225.19659375
transcript.pyannote[1447].speaker SPEAKER_18
transcript.pyannote[1447].start 11225.95596875
transcript.pyannote[1447].end 11228.95971875
transcript.pyannote[1448].speaker SPEAKER_18
transcript.pyannote[1448].start 11229.26346875
transcript.pyannote[1448].end 11231.37284375
transcript.pyannote[1449].speaker SPEAKER_18
transcript.pyannote[1449].start 11233.49909375
transcript.pyannote[1449].end 11236.78971875
transcript.pyannote[1450].speaker SPEAKER_24
transcript.pyannote[1450].start 11236.78971875
transcript.pyannote[1450].end 11240.46846875
transcript.pyannote[1451].speaker SPEAKER_18
transcript.pyannote[1451].start 11237.76846875
transcript.pyannote[1451].end 11238.25784375
transcript.pyannote[1452].speaker SPEAKER_18
transcript.pyannote[1452].start 11240.06346875
transcript.pyannote[1452].end 11242.45971875
transcript.pyannote[1453].speaker SPEAKER_18
transcript.pyannote[1453].start 11243.21909375
transcript.pyannote[1453].end 11246.79659375
transcript.pyannote[1454].speaker SPEAKER_18
transcript.pyannote[1454].start 11247.04971875
transcript.pyannote[1454].end 11253.27659375
transcript.pyannote[1455].speaker SPEAKER_03
transcript.pyannote[1455].start 11255.99346875
transcript.pyannote[1455].end 11257.83284375
transcript.pyannote[1456].speaker SPEAKER_19
transcript.pyannote[1456].start 11258.57534375
transcript.pyannote[1456].end 11260.19534375
transcript.pyannote[1457].speaker SPEAKER_03
transcript.pyannote[1457].start 11260.39784375
transcript.pyannote[1457].end 11260.93784375
transcript.pyannote[1458].speaker SPEAKER_19
transcript.pyannote[1458].start 11260.56659375
transcript.pyannote[1458].end 11260.95471875
transcript.pyannote[1459].speaker SPEAKER_03
transcript.pyannote[1459].start 11260.95471875
transcript.pyannote[1459].end 11260.97159375
transcript.pyannote[1460].speaker SPEAKER_19
transcript.pyannote[1460].start 11260.97159375
transcript.pyannote[1460].end 11260.98846875
transcript.pyannote[1461].speaker SPEAKER_03
transcript.pyannote[1461].start 11260.98846875
transcript.pyannote[1461].end 11261.05596875
transcript.pyannote[1462].speaker SPEAKER_03
transcript.pyannote[1462].start 11261.24159375
transcript.pyannote[1462].end 11264.04284375
transcript.pyannote[1463].speaker SPEAKER_03
transcript.pyannote[1463].start 11264.63346875
transcript.pyannote[1463].end 11269.44284375
transcript.pyannote[1464].speaker SPEAKER_03
transcript.pyannote[1464].start 11272.31159375
transcript.pyannote[1464].end 11274.85971875
transcript.pyannote[1465].speaker SPEAKER_03
transcript.pyannote[1465].start 11274.97784375
transcript.pyannote[1465].end 11275.02846875
transcript.pyannote[1466].speaker SPEAKER_03
transcript.pyannote[1466].start 11275.07909375
transcript.pyannote[1466].end 11276.90159375
transcript.pyannote[1467].speaker SPEAKER_32
transcript.pyannote[1467].start 11278.35284375
transcript.pyannote[1467].end 11282.65596875
transcript.pyannote[1468].speaker SPEAKER_03
transcript.pyannote[1468].start 11281.74471875
transcript.pyannote[1468].end 11282.63909375
transcript.pyannote[1469].speaker SPEAKER_03
transcript.pyannote[1469].start 11282.65596875
transcript.pyannote[1469].end 11282.70659375
transcript.pyannote[1470].speaker SPEAKER_03
transcript.pyannote[1470].start 11282.97659375
transcript.pyannote[1470].end 11283.01034375
transcript.pyannote[1471].speaker SPEAKER_32
transcript.pyannote[1471].start 11283.01034375
transcript.pyannote[1471].end 11283.24659375
transcript.pyannote[1472].speaker SPEAKER_03
transcript.pyannote[1472].start 11283.24659375
transcript.pyannote[1472].end 11285.11971875
transcript.pyannote[1473].speaker SPEAKER_32
transcript.pyannote[1473].start 11285.11971875
transcript.pyannote[1473].end 11287.19534375
transcript.pyannote[1474].speaker SPEAKER_03
transcript.pyannote[1474].start 11285.13659375
transcript.pyannote[1474].end 11285.37284375
transcript.pyannote[1475].speaker SPEAKER_03
transcript.pyannote[1475].start 11287.33034375
transcript.pyannote[1475].end 11288.08971875
transcript.pyannote[1476].speaker SPEAKER_32
transcript.pyannote[1476].start 11290.51971875
transcript.pyannote[1476].end 11291.17784375
transcript.pyannote[1477].speaker SPEAKER_32
transcript.pyannote[1477].start 11294.21534375
transcript.pyannote[1477].end 11299.31159375
transcript.pyannote[1478].speaker SPEAKER_32
transcript.pyannote[1478].start 11299.83471875
transcript.pyannote[1478].end 11303.73284375
transcript.pyannote[1479].speaker SPEAKER_32
transcript.pyannote[1479].start 11305.38659375
transcript.pyannote[1479].end 11307.85034375
transcript.pyannote[1480].speaker SPEAKER_24
transcript.pyannote[1480].start 11305.40346875
transcript.pyannote[1480].end 11305.79159375
transcript.pyannote[1481].speaker SPEAKER_24
transcript.pyannote[1481].start 11306.78721875
transcript.pyannote[1481].end 11307.15846875
transcript.pyannote[1482].speaker SPEAKER_32
transcript.pyannote[1482].start 11309.03159375
transcript.pyannote[1482].end 11310.61784375
transcript.pyannote[1483].speaker SPEAKER_32
transcript.pyannote[1483].start 11311.12409375
transcript.pyannote[1483].end 11314.90409375
transcript.pyannote[1484].speaker SPEAKER_32
transcript.pyannote[1484].start 11318.53221875
transcript.pyannote[1484].end 11318.97096875
transcript.pyannote[1485].speaker SPEAKER_24
transcript.pyannote[1485].start 11318.97096875
transcript.pyannote[1485].end 11320.40534375
transcript.pyannote[1486].speaker SPEAKER_24
transcript.pyannote[1486].start 11322.36284375
transcript.pyannote[1486].end 11324.75909375
transcript.pyannote[1487].speaker SPEAKER_24
transcript.pyannote[1487].start 11325.31596875
transcript.pyannote[1487].end 11327.88096875
transcript.pyannote[1488].speaker SPEAKER_32
transcript.pyannote[1488].start 11328.47159375
transcript.pyannote[1488].end 11339.22096875
transcript.pyannote[1489].speaker SPEAKER_32
transcript.pyannote[1489].start 11339.67659375
transcript.pyannote[1489].end 11342.15721875
transcript.pyannote[1490].speaker SPEAKER_32
transcript.pyannote[1490].start 11343.05159375
transcript.pyannote[1490].end 11343.30471875
transcript.pyannote[1491].speaker SPEAKER_32
transcript.pyannote[1491].start 11344.09784375
transcript.pyannote[1491].end 11345.11034375
transcript.pyannote[1492].speaker SPEAKER_32
transcript.pyannote[1492].start 11346.13971875
transcript.pyannote[1492].end 11349.70034375
transcript.pyannote[1493].speaker SPEAKER_32
transcript.pyannote[1493].start 11350.17284375
transcript.pyannote[1493].end 11353.26096875
transcript.pyannote[1494].speaker SPEAKER_32
transcript.pyannote[1494].start 11353.66596875
transcript.pyannote[1494].end 11362.50846875
transcript.pyannote[1495].speaker SPEAKER_32
transcript.pyannote[1495].start 11363.55471875
transcript.pyannote[1495].end 11373.13971875
transcript.pyannote[1496].speaker SPEAKER_32
transcript.pyannote[1496].start 11373.76409375
transcript.pyannote[1496].end 11377.84784375
transcript.pyannote[1497].speaker SPEAKER_32
transcript.pyannote[1497].start 11378.92784375
transcript.pyannote[1497].end 11394.65534375
transcript.pyannote[1498].speaker SPEAKER_32
transcript.pyannote[1498].start 11396.44409375
transcript.pyannote[1498].end 11406.87284375
transcript.pyannote[1499].speaker SPEAKER_24
transcript.pyannote[1499].start 11408.84721875
transcript.pyannote[1499].end 11413.47096875
transcript.pyannote[1500].speaker SPEAKER_24
transcript.pyannote[1500].start 11413.55534375
transcript.pyannote[1500].end 11413.85909375
transcript.pyannote[1501].speaker SPEAKER_32
transcript.pyannote[1501].start 11414.17971875
transcript.pyannote[1501].end 11422.09409375
transcript.pyannote[1502].speaker SPEAKER_24
transcript.pyannote[1502].start 11422.48221875
transcript.pyannote[1502].end 11425.50284375
transcript.pyannote[1503].speaker SPEAKER_32
transcript.pyannote[1503].start 11422.49909375
transcript.pyannote[1503].end 11422.61721875
transcript.pyannote[1504].speaker SPEAKER_24
transcript.pyannote[1504].start 11427.34221875
transcript.pyannote[1504].end 11427.35909375
transcript.pyannote[1505].speaker SPEAKER_32
transcript.pyannote[1505].start 11427.35909375
transcript.pyannote[1505].end 11443.03596875
transcript.pyannote[1506].speaker SPEAKER_32
transcript.pyannote[1506].start 11443.94721875
transcript.pyannote[1506].end 11446.07346875
transcript.pyannote[1507].speaker SPEAKER_32
transcript.pyannote[1507].start 11446.79909375
transcript.pyannote[1507].end 11447.40659375
transcript.pyannote[1508].speaker SPEAKER_32
transcript.pyannote[1508].start 11448.40221875
transcript.pyannote[1508].end 11450.98409375
transcript.pyannote[1509].speaker SPEAKER_32
transcript.pyannote[1509].start 11451.70971875
transcript.pyannote[1509].end 11473.12409375
transcript.pyannote[1510].speaker SPEAKER_32
transcript.pyannote[1510].start 11474.05221875
transcript.pyannote[1510].end 11475.80721875
transcript.pyannote[1511].speaker SPEAKER_32
transcript.pyannote[1511].start 11477.64659375
transcript.pyannote[1511].end 11485.32471875
transcript.pyannote[1512].speaker SPEAKER_32
transcript.pyannote[1512].start 11485.49346875
transcript.pyannote[1512].end 11490.43784375
transcript.pyannote[1513].speaker SPEAKER_32
transcript.pyannote[1513].start 11491.14659375
transcript.pyannote[1513].end 11491.65284375
transcript.pyannote[1514].speaker SPEAKER_32
transcript.pyannote[1514].start 11493.03659375
transcript.pyannote[1514].end 11500.78221875
transcript.pyannote[1515].speaker SPEAKER_32
transcript.pyannote[1515].start 11501.25471875
transcript.pyannote[1515].end 11503.00971875
transcript.pyannote[1516].speaker SPEAKER_32
transcript.pyannote[1516].start 11504.34284375
transcript.pyannote[1516].end 11506.28346875
transcript.pyannote[1517].speaker SPEAKER_24
transcript.pyannote[1517].start 11506.82346875
transcript.pyannote[1517].end 11510.26596875
transcript.pyannote[1518].speaker SPEAKER_32
transcript.pyannote[1518].start 11506.84034375
transcript.pyannote[1518].end 11507.27909375
transcript.pyannote[1519].speaker SPEAKER_32
transcript.pyannote[1519].start 11511.31221875
transcript.pyannote[1519].end 11511.97034375
transcript.pyannote[1520].speaker SPEAKER_24
transcript.pyannote[1520].start 11511.97034375
transcript.pyannote[1520].end 11512.03784375
transcript.pyannote[1521].speaker SPEAKER_32
transcript.pyannote[1521].start 11512.03784375
transcript.pyannote[1521].end 11512.10534375
transcript.pyannote[1522].speaker SPEAKER_24
transcript.pyannote[1522].start 11512.10534375
transcript.pyannote[1522].end 11515.02471875
transcript.pyannote[1523].speaker SPEAKER_32
transcript.pyannote[1523].start 11515.02471875
transcript.pyannote[1523].end 11515.73346875
transcript.pyannote[1524].speaker SPEAKER_24
transcript.pyannote[1524].start 11516.39159375
transcript.pyannote[1524].end 11516.42534375
transcript.pyannote[1525].speaker SPEAKER_32
transcript.pyannote[1525].start 11516.42534375
transcript.pyannote[1525].end 11518.51784375
transcript.pyannote[1526].speaker SPEAKER_32
transcript.pyannote[1526].start 11518.75409375
transcript.pyannote[1526].end 11519.58096875
transcript.pyannote[1527].speaker SPEAKER_32
transcript.pyannote[1527].start 11519.73284375
transcript.pyannote[1527].end 11522.11221875
transcript.pyannote[1528].speaker SPEAKER_32
transcript.pyannote[1528].start 11522.82096875
transcript.pyannote[1528].end 11525.55471875
transcript.pyannote[1529].speaker SPEAKER_32
transcript.pyannote[1529].start 11525.97659375
transcript.pyannote[1529].end 11526.41534375
transcript.pyannote[1530].speaker SPEAKER_32
transcript.pyannote[1530].start 11527.25909375
transcript.pyannote[1530].end 11528.00159375
transcript.pyannote[1531].speaker SPEAKER_32
transcript.pyannote[1531].start 11528.89596875
transcript.pyannote[1531].end 11531.29221875
transcript.pyannote[1532].speaker SPEAKER_32
transcript.pyannote[1532].start 11532.20346875
transcript.pyannote[1532].end 11537.41784375
transcript.pyannote[1533].speaker SPEAKER_32
transcript.pyannote[1533].start 11538.66659375
transcript.pyannote[1533].end 11539.84784375
transcript.pyannote[1534].speaker SPEAKER_24
transcript.pyannote[1534].start 11539.13909375
transcript.pyannote[1534].end 11587.60409375
transcript.pyannote[1535].speaker SPEAKER_32
transcript.pyannote[1535].start 11587.24971875
transcript.pyannote[1535].end 11600.26034375
transcript.pyannote[1536].speaker SPEAKER_24
transcript.pyannote[1536].start 11599.19721875
transcript.pyannote[1536].end 11612.78159375
transcript.pyannote[1537].speaker SPEAKER_29
transcript.pyannote[1537].start 11603.48346875
transcript.pyannote[1537].end 11603.97284375
transcript.pyannote[1538].speaker SPEAKER_24
transcript.pyannote[1538].start 11613.47346875
transcript.pyannote[1538].end 11615.75159375
transcript.pyannote[1539].speaker SPEAKER_24
transcript.pyannote[1539].start 11616.27471875
transcript.pyannote[1539].end 11625.79221875
transcript.pyannote[1540].speaker SPEAKER_32
transcript.pyannote[1540].start 11627.63159375
transcript.pyannote[1540].end 11635.00596875
transcript.pyannote[1541].speaker SPEAKER_32
transcript.pyannote[1541].start 11635.86659375
transcript.pyannote[1541].end 11639.35971875
transcript.pyannote[1542].speaker SPEAKER_32
transcript.pyannote[1542].start 11639.52846875
transcript.pyannote[1542].end 11651.35784375
transcript.pyannote[1543].speaker SPEAKER_24
transcript.pyannote[1543].start 11652.26909375
transcript.pyannote[1543].end 11652.28596875
transcript.pyannote[1544].speaker SPEAKER_32
transcript.pyannote[1544].start 11652.28596875
transcript.pyannote[1544].end 11652.30284375
transcript.pyannote[1545].speaker SPEAKER_24
transcript.pyannote[1545].start 11652.30284375
transcript.pyannote[1545].end 11652.79221875
transcript.pyannote[1546].speaker SPEAKER_32
transcript.pyannote[1546].start 11652.33659375
transcript.pyannote[1546].end 11654.00721875
transcript.pyannote[1547].speaker SPEAKER_24
transcript.pyannote[1547].start 11654.00721875
transcript.pyannote[1547].end 11659.84596875
transcript.pyannote[1548].speaker SPEAKER_32
transcript.pyannote[1548].start 11659.42409375
transcript.pyannote[1548].end 11662.25909375
transcript.pyannote[1549].speaker SPEAKER_24
transcript.pyannote[1549].start 11661.22971875
transcript.pyannote[1549].end 11661.53346875
transcript.pyannote[1550].speaker SPEAKER_24
transcript.pyannote[1550].start 11662.25909375
transcript.pyannote[1550].end 11666.42721875
transcript.pyannote[1551].speaker SPEAKER_32
transcript.pyannote[1551].start 11662.34346875
transcript.pyannote[1551].end 11664.38534375
transcript.pyannote[1552].speaker SPEAKER_24
transcript.pyannote[1552].start 11667.13596875
transcript.pyannote[1552].end 11667.20346875
transcript.pyannote[1553].speaker SPEAKER_32
transcript.pyannote[1553].start 11667.20346875
transcript.pyannote[1553].end 11667.54096875
transcript.pyannote[1554].speaker SPEAKER_24
transcript.pyannote[1554].start 11667.54096875
transcript.pyannote[1554].end 11667.57471875
transcript.pyannote[1555].speaker SPEAKER_32
transcript.pyannote[1555].start 11667.57471875
transcript.pyannote[1555].end 11667.60846875
transcript.pyannote[1556].speaker SPEAKER_32
transcript.pyannote[1556].start 11667.84471875
transcript.pyannote[1556].end 11669.12721875
transcript.pyannote[1557].speaker SPEAKER_32
transcript.pyannote[1557].start 11669.19471875
transcript.pyannote[1557].end 11669.49846875
transcript.pyannote[1558].speaker SPEAKER_32
transcript.pyannote[1558].start 11670.10596875
transcript.pyannote[1558].end 11674.45971875
transcript.pyannote[1559].speaker SPEAKER_24
transcript.pyannote[1559].start 11671.60784375
transcript.pyannote[1559].end 11671.91159375
transcript.pyannote[1560].speaker SPEAKER_32
transcript.pyannote[1560].start 11674.71284375
transcript.pyannote[1560].end 11678.42534375
transcript.pyannote[1561].speaker SPEAKER_32
transcript.pyannote[1561].start 11679.06659375
transcript.pyannote[1561].end 11681.41221875
transcript.pyannote[1562].speaker SPEAKER_32
transcript.pyannote[1562].start 11681.81721875
transcript.pyannote[1562].end 11685.07409375
transcript.pyannote[1563].speaker SPEAKER_32
transcript.pyannote[1563].start 11685.52971875
transcript.pyannote[1563].end 11686.84596875
transcript.pyannote[1564].speaker SPEAKER_32
transcript.pyannote[1564].start 11687.58846875
transcript.pyannote[1564].end 11692.92096875
transcript.pyannote[1565].speaker SPEAKER_32
transcript.pyannote[1565].start 11694.06846875
transcript.pyannote[1565].end 11702.53971875
transcript.pyannote[1566].speaker SPEAKER_32
transcript.pyannote[1566].start 11703.45096875
transcript.pyannote[1566].end 11706.87659375
transcript.pyannote[1567].speaker SPEAKER_32
transcript.pyannote[1567].start 11707.04534375
transcript.pyannote[1567].end 11715.11159375
transcript.pyannote[1568].speaker SPEAKER_32
transcript.pyannote[1568].start 11715.71909375
transcript.pyannote[1568].end 11722.90784375
transcript.pyannote[1569].speaker SPEAKER_24
transcript.pyannote[1569].start 11722.90784375
transcript.pyannote[1569].end 11731.54784375
transcript.pyannote[1570].speaker SPEAKER_24
transcript.pyannote[1570].start 11731.85159375
transcript.pyannote[1570].end 11753.06346875
transcript.pyannote[1571].speaker SPEAKER_24
transcript.pyannote[1571].start 11753.16471875
transcript.pyannote[1571].end 11753.99159375
transcript.pyannote[1572].speaker SPEAKER_32
transcript.pyannote[1572].start 11753.18159375
transcript.pyannote[1572].end 11775.38909375
transcript.pyannote[1573].speaker SPEAKER_32
transcript.pyannote[1573].start 11775.67596875
transcript.pyannote[1573].end 11782.83096875
transcript.pyannote[1574].speaker SPEAKER_32
transcript.pyannote[1574].start 11782.96596875
transcript.pyannote[1574].end 11786.93159375
transcript.pyannote[1575].speaker SPEAKER_24
transcript.pyannote[1575].start 11788.26471875
transcript.pyannote[1575].end 11790.76221875
transcript.pyannote[1576].speaker SPEAKER_32
transcript.pyannote[1576].start 11790.42471875
transcript.pyannote[1576].end 11792.24721875
transcript.pyannote[1577].speaker SPEAKER_24
transcript.pyannote[1577].start 11792.21346875
transcript.pyannote[1577].end 11806.21971875
transcript.pyannote[1578].speaker SPEAKER_32
transcript.pyannote[1578].start 11806.33784375
transcript.pyannote[1578].end 11810.87721875
transcript.pyannote[1579].speaker SPEAKER_24
transcript.pyannote[1579].start 11810.82659375
transcript.pyannote[1579].end 11810.86034375
transcript.pyannote[1580].speaker SPEAKER_24
transcript.pyannote[1580].start 11810.87721875
transcript.pyannote[1580].end 11820.54659375
transcript.pyannote[1581].speaker SPEAKER_32
transcript.pyannote[1581].start 11811.13034375
transcript.pyannote[1581].end 11814.58971875
transcript.pyannote[1582].speaker SPEAKER_32
transcript.pyannote[1582].start 11816.81721875
transcript.pyannote[1582].end 11817.13784375
transcript.pyannote[1583].speaker SPEAKER_32
transcript.pyannote[1583].start 11821.71096875
transcript.pyannote[1583].end 11822.90909375
transcript.pyannote[1584].speaker SPEAKER_32
transcript.pyannote[1584].start 11824.69784375
transcript.pyannote[1584].end 11833.30409375
transcript.pyannote[1585].speaker SPEAKER_32
transcript.pyannote[1585].start 11833.77659375
transcript.pyannote[1585].end 11835.51471875
transcript.pyannote[1586].speaker SPEAKER_32
transcript.pyannote[1586].start 11836.79721875
transcript.pyannote[1586].end 11837.43846875
transcript.pyannote[1587].speaker SPEAKER_32
transcript.pyannote[1587].start 11837.99534375
transcript.pyannote[1587].end 11843.83409375
transcript.pyannote[1588].speaker SPEAKER_24
transcript.pyannote[1588].start 11844.47534375
transcript.pyannote[1588].end 11845.90971875
transcript.pyannote[1589].speaker SPEAKER_32
transcript.pyannote[1589].start 11844.64409375
transcript.pyannote[1589].end 11845.26846875
transcript.pyannote[1590].speaker SPEAKER_32
transcript.pyannote[1590].start 11845.90971875
transcript.pyannote[1590].end 11845.97721875
transcript.pyannote[1591].speaker SPEAKER_24
transcript.pyannote[1591].start 11845.97721875
transcript.pyannote[1591].end 11851.54596875
transcript.pyannote[1592].speaker SPEAKER_24
transcript.pyannote[1592].start 11852.15346875
transcript.pyannote[1592].end 11859.47721875
transcript.pyannote[1593].speaker SPEAKER_24
transcript.pyannote[1593].start 11860.42221875
transcript.pyannote[1593].end 11862.02534375
transcript.pyannote[1594].speaker SPEAKER_24
transcript.pyannote[1594].start 11862.49784375
transcript.pyannote[1594].end 11864.03346875
transcript.pyannote[1595].speaker SPEAKER_32
transcript.pyannote[1595].start 11864.03346875
transcript.pyannote[1595].end 11865.07971875
transcript.pyannote[1596].speaker SPEAKER_32
transcript.pyannote[1596].start 11865.51846875
transcript.pyannote[1596].end 11875.44096875
transcript.pyannote[1597].speaker SPEAKER_32
transcript.pyannote[1597].start 11875.79534375
transcript.pyannote[1597].end 11880.99284375
transcript.pyannote[1598].speaker SPEAKER_32
transcript.pyannote[1598].start 11881.44846875
transcript.pyannote[1598].end 11888.18159375
transcript.pyannote[1599].speaker SPEAKER_24
transcript.pyannote[1599].start 11888.72159375
transcript.pyannote[1599].end 11889.95346875
transcript.pyannote[1600].speaker SPEAKER_32
transcript.pyannote[1600].start 11888.72159375
transcript.pyannote[1600].end 11891.03346875
transcript.pyannote[1601].speaker SPEAKER_24
transcript.pyannote[1601].start 11890.74659375
transcript.pyannote[1601].end 11892.90659375
transcript.pyannote[1602].speaker SPEAKER_32
transcript.pyannote[1602].start 11893.14284375
transcript.pyannote[1602].end 11893.44659375
transcript.pyannote[1603].speaker SPEAKER_32
transcript.pyannote[1603].start 11894.49284375
transcript.pyannote[1603].end 11896.77096875
transcript.pyannote[1604].speaker SPEAKER_24
transcript.pyannote[1604].start 11896.14659375
transcript.pyannote[1604].end 11898.79596875
transcript.pyannote[1605].speaker SPEAKER_24
transcript.pyannote[1605].start 11899.48784375
transcript.pyannote[1605].end 11903.36909375
transcript.pyannote[1606].speaker SPEAKER_24
transcript.pyannote[1606].start 11903.45346875
transcript.pyannote[1606].end 11906.01846875
transcript.pyannote[1607].speaker SPEAKER_24
transcript.pyannote[1607].start 11906.89596875
transcript.pyannote[1607].end 11909.73096875
transcript.pyannote[1608].speaker SPEAKER_24
transcript.pyannote[1608].start 11911.09784375
transcript.pyannote[1608].end 11911.36784375
transcript.pyannote[1609].speaker SPEAKER_03
transcript.pyannote[1609].start 11914.55721875
transcript.pyannote[1609].end 11916.32909375
transcript.pyannote[1610].speaker SPEAKER_03
transcript.pyannote[1610].start 11916.98721875
transcript.pyannote[1610].end 11917.67909375
transcript.pyannote[1611].speaker SPEAKER_03
transcript.pyannote[1611].start 11918.26971875
transcript.pyannote[1611].end 11920.85159375
transcript.pyannote[1612].speaker SPEAKER_03
transcript.pyannote[1612].start 11921.98221875
transcript.pyannote[1612].end 11924.91846875
transcript.pyannote[1613].speaker SPEAKER_11
transcript.pyannote[1613].start 11928.96846875
transcript.pyannote[1613].end 11931.80346875
transcript.pyannote[1614].speaker SPEAKER_03
transcript.pyannote[1614].start 11931.92159375
transcript.pyannote[1614].end 11933.10284375
transcript.pyannote[1615].speaker SPEAKER_11
transcript.pyannote[1615].start 11933.45721875
transcript.pyannote[1615].end 11936.03909375
transcript.pyannote[1616].speaker SPEAKER_03
transcript.pyannote[1616].start 11936.29221875
transcript.pyannote[1616].end 11937.11909375
transcript.pyannote[1617].speaker SPEAKER_03
transcript.pyannote[1617].start 11939.98784375
transcript.pyannote[1617].end 11943.02534375
transcript.pyannote[1618].speaker SPEAKER_03
transcript.pyannote[1618].start 11943.41346875
transcript.pyannote[1618].end 11943.61596875
transcript.pyannote[1619].speaker SPEAKER_11
transcript.pyannote[1619].start 11943.43034375
transcript.pyannote[1619].end 11953.99409375
transcript.pyannote[1620].speaker SPEAKER_29
transcript.pyannote[1620].start 11943.61596875
transcript.pyannote[1620].end 11943.88596875
transcript.pyannote[1621].speaker SPEAKER_03
transcript.pyannote[1621].start 11943.88596875
transcript.pyannote[1621].end 11943.95346875
transcript.pyannote[1622].speaker SPEAKER_29
transcript.pyannote[1622].start 11943.95346875
transcript.pyannote[1622].end 11944.08846875
transcript.pyannote[1623].speaker SPEAKER_03
transcript.pyannote[1623].start 11944.08846875
transcript.pyannote[1623].end 11944.13909375
transcript.pyannote[1624].speaker SPEAKER_29
transcript.pyannote[1624].start 11945.57346875
transcript.pyannote[1624].end 11946.33284375
transcript.pyannote[1625].speaker SPEAKER_11
transcript.pyannote[1625].start 11954.44971875
transcript.pyannote[1625].end 11958.17909375
transcript.pyannote[1626].speaker SPEAKER_11
transcript.pyannote[1626].start 11958.68534375
transcript.pyannote[1626].end 11961.21659375
transcript.pyannote[1627].speaker SPEAKER_11
transcript.pyannote[1627].start 11961.62159375
transcript.pyannote[1627].end 11962.75221875
transcript.pyannote[1628].speaker SPEAKER_11
transcript.pyannote[1628].start 11963.29221875
transcript.pyannote[1628].end 11971.00409375
transcript.pyannote[1629].speaker SPEAKER_11
transcript.pyannote[1629].start 11971.76346875
transcript.pyannote[1629].end 11972.15159375
transcript.pyannote[1630].speaker SPEAKER_11
transcript.pyannote[1630].start 11972.55659375
transcript.pyannote[1630].end 11978.05784375
transcript.pyannote[1631].speaker SPEAKER_11
transcript.pyannote[1631].start 11978.19284375
transcript.pyannote[1631].end 11980.30221875
transcript.pyannote[1632].speaker SPEAKER_11
transcript.pyannote[1632].start 11980.63971875
transcript.pyannote[1632].end 11982.66471875
transcript.pyannote[1633].speaker SPEAKER_11
transcript.pyannote[1633].start 11982.88409375
transcript.pyannote[1633].end 11987.28846875
transcript.pyannote[1634].speaker SPEAKER_11
transcript.pyannote[1634].start 11987.82846875
transcript.pyannote[1634].end 11991.06846875
transcript.pyannote[1635].speaker SPEAKER_11
transcript.pyannote[1635].start 11991.33846875
transcript.pyannote[1635].end 11993.98784375
transcript.pyannote[1636].speaker SPEAKER_11
transcript.pyannote[1636].start 11994.49409375
transcript.pyannote[1636].end 11996.28284375
transcript.pyannote[1637].speaker SPEAKER_11
transcript.pyannote[1637].start 11996.78909375
transcript.pyannote[1637].end 12004.99034375
transcript.pyannote[1638].speaker SPEAKER_11
transcript.pyannote[1638].start 12005.12534375
transcript.pyannote[1638].end 12015.72284375
transcript.pyannote[1639].speaker SPEAKER_11
transcript.pyannote[1639].start 12016.02659375
transcript.pyannote[1639].end 12024.91971875
transcript.pyannote[1640].speaker SPEAKER_11
transcript.pyannote[1640].start 12025.51034375
transcript.pyannote[1640].end 12027.36659375
transcript.pyannote[1641].speaker SPEAKER_11
transcript.pyannote[1641].start 12028.04159375
transcript.pyannote[1641].end 12037.71096875
transcript.pyannote[1642].speaker SPEAKER_11
transcript.pyannote[1642].start 12037.93034375
transcript.pyannote[1642].end 12048.76409375
transcript.pyannote[1643].speaker SPEAKER_24
transcript.pyannote[1643].start 12048.98346875
transcript.pyannote[1643].end 12061.23471875
transcript.pyannote[1644].speaker SPEAKER_00
transcript.pyannote[1644].start 12058.41659375
transcript.pyannote[1644].end 12058.85534375
transcript.pyannote[1645].speaker SPEAKER_00
transcript.pyannote[1645].start 12059.68221875
transcript.pyannote[1645].end 12059.78346875
transcript.pyannote[1646].speaker SPEAKER_22
transcript.pyannote[1646].start 12059.78346875
transcript.pyannote[1646].end 12060.05346875
transcript.pyannote[1647].speaker SPEAKER_24
transcript.pyannote[1647].start 12061.55534375
transcript.pyannote[1647].end 12079.12221875
transcript.pyannote[1648].speaker SPEAKER_11
transcript.pyannote[1648].start 12079.86471875
transcript.pyannote[1648].end 12092.18346875
transcript.pyannote[1649].speaker SPEAKER_11
transcript.pyannote[1649].start 12092.20034375
transcript.pyannote[1649].end 12111.47159375
transcript.pyannote[1650].speaker SPEAKER_11
transcript.pyannote[1650].start 12112.11284375
transcript.pyannote[1650].end 12114.08721875
transcript.pyannote[1651].speaker SPEAKER_11
transcript.pyannote[1651].start 12114.25596875
transcript.pyannote[1651].end 12122.01846875
transcript.pyannote[1652].speaker SPEAKER_00
transcript.pyannote[1652].start 12116.09534375
transcript.pyannote[1652].end 12116.60159375
transcript.pyannote[1653].speaker SPEAKER_11
transcript.pyannote[1653].start 12122.08596875
transcript.pyannote[1653].end 12123.75659375
transcript.pyannote[1654].speaker SPEAKER_11
transcript.pyannote[1654].start 12124.17846875
transcript.pyannote[1654].end 12128.58284375
transcript.pyannote[1655].speaker SPEAKER_24
transcript.pyannote[1655].start 12128.00909375
transcript.pyannote[1655].end 12133.96596875
transcript.pyannote[1656].speaker SPEAKER_11
transcript.pyannote[1656].start 12129.08909375
transcript.pyannote[1656].end 12129.51096875
transcript.pyannote[1657].speaker SPEAKER_11
transcript.pyannote[1657].start 12133.96596875
transcript.pyannote[1657].end 12134.47221875
transcript.pyannote[1658].speaker SPEAKER_24
transcript.pyannote[1658].start 12134.47221875
transcript.pyannote[1658].end 12140.83409375
transcript.pyannote[1659].speaker SPEAKER_11
transcript.pyannote[1659].start 12137.72909375
transcript.pyannote[1659].end 12138.70784375
transcript.pyannote[1660].speaker SPEAKER_11
transcript.pyannote[1660].start 12140.14221875
transcript.pyannote[1660].end 12145.84596875
transcript.pyannote[1661].speaker SPEAKER_24
transcript.pyannote[1661].start 12142.60596875
transcript.pyannote[1661].end 12147.90471875
transcript.pyannote[1662].speaker SPEAKER_11
transcript.pyannote[1662].start 12147.29721875
transcript.pyannote[1662].end 12164.59409375
transcript.pyannote[1663].speaker SPEAKER_11
transcript.pyannote[1663].start 12164.83034375
transcript.pyannote[1663].end 12169.33596875
transcript.pyannote[1664].speaker SPEAKER_11
transcript.pyannote[1664].start 12169.82534375
transcript.pyannote[1664].end 12187.12221875
transcript.pyannote[1665].speaker SPEAKER_11
transcript.pyannote[1665].start 12187.27409375
transcript.pyannote[1665].end 12189.33284375
transcript.pyannote[1666].speaker SPEAKER_11
transcript.pyannote[1666].start 12190.04159375
transcript.pyannote[1666].end 12211.79346875
transcript.pyannote[1667].speaker SPEAKER_11
transcript.pyannote[1667].start 12212.23221875
transcript.pyannote[1667].end 12213.58221875
transcript.pyannote[1668].speaker SPEAKER_11
transcript.pyannote[1668].start 12214.27409375
transcript.pyannote[1668].end 12237.61221875
transcript.pyannote[1669].speaker SPEAKER_11
transcript.pyannote[1669].start 12241.34159375
transcript.pyannote[1669].end 12244.05846875
transcript.pyannote[1670].speaker SPEAKER_24
transcript.pyannote[1670].start 12243.53534375
transcript.pyannote[1670].end 12247.38284375
transcript.pyannote[1671].speaker SPEAKER_24
transcript.pyannote[1671].start 12247.70346875
transcript.pyannote[1671].end 12259.83659375
transcript.pyannote[1672].speaker SPEAKER_11
transcript.pyannote[1672].start 12255.43221875
transcript.pyannote[1672].end 12257.01846875
transcript.pyannote[1673].speaker SPEAKER_11
transcript.pyannote[1673].start 12259.56659375
transcript.pyannote[1673].end 12260.76471875
transcript.pyannote[1674].speaker SPEAKER_24
transcript.pyannote[1674].start 12260.14034375
transcript.pyannote[1674].end 12264.19034375
transcript.pyannote[1675].speaker SPEAKER_11
transcript.pyannote[1675].start 12262.18221875
transcript.pyannote[1675].end 12266.65409375
transcript.pyannote[1676].speaker SPEAKER_11
transcript.pyannote[1676].start 12266.78909375
transcript.pyannote[1676].end 12286.81971875
transcript.pyannote[1677].speaker SPEAKER_24
transcript.pyannote[1677].start 12287.51159375
transcript.pyannote[1677].end 12288.64221875
transcript.pyannote[1678].speaker SPEAKER_11
transcript.pyannote[1678].start 12288.37221875
transcript.pyannote[1678].end 12293.65409375
transcript.pyannote[1679].speaker SPEAKER_11
transcript.pyannote[1679].start 12293.89034375
transcript.pyannote[1679].end 12299.79659375
transcript.pyannote[1680].speaker SPEAKER_11
transcript.pyannote[1680].start 12299.89784375
transcript.pyannote[1680].end 12301.55159375
transcript.pyannote[1681].speaker SPEAKER_11
transcript.pyannote[1681].start 12302.00721875
transcript.pyannote[1681].end 12314.62971875
transcript.pyannote[1682].speaker SPEAKER_11
transcript.pyannote[1682].start 12315.76034375
transcript.pyannote[1682].end 12320.68784375
transcript.pyannote[1683].speaker SPEAKER_11
transcript.pyannote[1683].start 12320.94096875
transcript.pyannote[1683].end 12322.05471875
transcript.pyannote[1684].speaker SPEAKER_11
transcript.pyannote[1684].start 12322.17284375
transcript.pyannote[1684].end 12325.86846875
transcript.pyannote[1685].speaker SPEAKER_11
transcript.pyannote[1685].start 12326.35784375
transcript.pyannote[1685].end 12330.77909375
transcript.pyannote[1686].speaker SPEAKER_11
transcript.pyannote[1686].start 12331.18409375
transcript.pyannote[1686].end 12339.28409375
transcript.pyannote[1687].speaker SPEAKER_11
transcript.pyannote[1687].start 12339.52034375
transcript.pyannote[1687].end 12342.67596875
transcript.pyannote[1688].speaker SPEAKER_11
transcript.pyannote[1688].start 12343.08096875
transcript.pyannote[1688].end 12347.55284375
transcript.pyannote[1689].speaker SPEAKER_11
transcript.pyannote[1689].start 12348.14346875
transcript.pyannote[1689].end 12353.10471875
transcript.pyannote[1690].speaker SPEAKER_24
transcript.pyannote[1690].start 12353.57721875
transcript.pyannote[1690].end 12357.69471875
transcript.pyannote[1691].speaker SPEAKER_24
transcript.pyannote[1691].start 12357.71159375
transcript.pyannote[1691].end 12360.02346875
transcript.pyannote[1692].speaker SPEAKER_22
transcript.pyannote[1692].start 12359.39909375
transcript.pyannote[1692].end 12359.70284375
transcript.pyannote[1693].speaker SPEAKER_24
transcript.pyannote[1693].start 12360.32721875
transcript.pyannote[1693].end 12374.45159375
transcript.pyannote[1694].speaker SPEAKER_24
transcript.pyannote[1694].start 12374.78909375
transcript.pyannote[1694].end 12377.26971875
transcript.pyannote[1695].speaker SPEAKER_11
transcript.pyannote[1695].start 12376.89846875
transcript.pyannote[1695].end 12384.67784375
transcript.pyannote[1696].speaker SPEAKER_22
transcript.pyannote[1696].start 12384.37409375
transcript.pyannote[1696].end 12384.81284375
transcript.pyannote[1697].speaker SPEAKER_11
transcript.pyannote[1697].start 12384.71159375
transcript.pyannote[1697].end 12393.97596875
transcript.pyannote[1698].speaker SPEAKER_11
transcript.pyannote[1698].start 12394.49909375
transcript.pyannote[1698].end 12395.88284375
transcript.pyannote[1699].speaker SPEAKER_11
transcript.pyannote[1699].start 12396.57471875
transcript.pyannote[1699].end 12412.92659375
transcript.pyannote[1700].speaker SPEAKER_24
transcript.pyannote[1700].start 12412.92659375
transcript.pyannote[1700].end 12433.34534375
transcript.pyannote[1701].speaker SPEAKER_11
transcript.pyannote[1701].start 12430.56096875
transcript.pyannote[1701].end 12430.57784375
transcript.pyannote[1702].speaker SPEAKER_11
transcript.pyannote[1702].start 12430.59471875
transcript.pyannote[1702].end 12448.29659375
transcript.pyannote[1703].speaker SPEAKER_24
transcript.pyannote[1703].start 12448.29659375
transcript.pyannote[1703].end 12451.41846875
transcript.pyannote[1704].speaker SPEAKER_11
transcript.pyannote[1704].start 12451.51971875
transcript.pyannote[1704].end 12452.32971875
transcript.pyannote[1705].speaker SPEAKER_24
transcript.pyannote[1705].start 12452.27909375
transcript.pyannote[1705].end 12455.01284375
transcript.pyannote[1706].speaker SPEAKER_11
transcript.pyannote[1706].start 12452.78534375
transcript.pyannote[1706].end 12453.83159375
transcript.pyannote[1707].speaker SPEAKER_11
transcript.pyannote[1707].start 12454.74284375
transcript.pyannote[1707].end 12463.11284375
transcript.pyannote[1708].speaker SPEAKER_24
transcript.pyannote[1708].start 12463.82159375
transcript.pyannote[1708].end 12464.39534375
transcript.pyannote[1709].speaker SPEAKER_24
transcript.pyannote[1709].start 12465.12096875
transcript.pyannote[1709].end 12468.27659375
transcript.pyannote[1710].speaker SPEAKER_11
transcript.pyannote[1710].start 12465.32346875
transcript.pyannote[1710].end 12465.45846875
transcript.pyannote[1711].speaker SPEAKER_24
transcript.pyannote[1711].start 12468.34409375
transcript.pyannote[1711].end 12468.36096875
transcript.pyannote[1712].speaker SPEAKER_11
transcript.pyannote[1712].start 12468.36096875
transcript.pyannote[1712].end 12468.68159375
transcript.pyannote[1713].speaker SPEAKER_24
transcript.pyannote[1713].start 12469.20471875
transcript.pyannote[1713].end 12474.63846875
transcript.pyannote[1714].speaker SPEAKER_11
transcript.pyannote[1714].start 12473.49096875
transcript.pyannote[1714].end 12473.99721875
transcript.pyannote[1715].speaker SPEAKER_24
transcript.pyannote[1715].start 12475.14471875
transcript.pyannote[1715].end 12477.50721875
transcript.pyannote[1716].speaker SPEAKER_11
transcript.pyannote[1716].start 12477.50721875
transcript.pyannote[1716].end 12494.53409375
transcript.pyannote[1717].speaker SPEAKER_00
transcript.pyannote[1717].start 12491.83409375
transcript.pyannote[1717].end 12492.23909375
transcript.pyannote[1718].speaker SPEAKER_11
transcript.pyannote[1718].start 12495.02346875
transcript.pyannote[1718].end 12504.81096875
transcript.pyannote[1719].speaker SPEAKER_11
transcript.pyannote[1719].start 12504.89534375
transcript.pyannote[1719].end 12510.97034375
transcript.pyannote[1720].speaker SPEAKER_24
transcript.pyannote[1720].start 12510.58221875
transcript.pyannote[1720].end 12537.53159375
transcript.pyannote[1721].speaker SPEAKER_11
transcript.pyannote[1721].start 12537.48096875
transcript.pyannote[1721].end 12537.49784375
transcript.pyannote[1722].speaker SPEAKER_11
transcript.pyannote[1722].start 12537.53159375
transcript.pyannote[1722].end 12549.41159375
transcript.pyannote[1723].speaker SPEAKER_24
transcript.pyannote[1723].start 12538.17284375
transcript.pyannote[1723].end 12538.66221875
transcript.pyannote[1724].speaker SPEAKER_31
transcript.pyannote[1724].start 12551.30159375
transcript.pyannote[1724].end 12556.29659375
transcript.pyannote[1725].speaker SPEAKER_31
transcript.pyannote[1725].start 12556.43159375
transcript.pyannote[1725].end 12556.46534375
transcript.pyannote[1726].speaker SPEAKER_29
transcript.pyannote[1726].start 12556.46534375
transcript.pyannote[1726].end 12556.65096875
transcript.pyannote[1727].speaker SPEAKER_31
transcript.pyannote[1727].start 12556.65096875
transcript.pyannote[1727].end 12556.68471875
transcript.pyannote[1728].speaker SPEAKER_29
transcript.pyannote[1728].start 12556.68471875
transcript.pyannote[1728].end 12556.71846875
transcript.pyannote[1729].speaker SPEAKER_31
transcript.pyannote[1729].start 12556.71846875
transcript.pyannote[1729].end 12556.73534375
transcript.pyannote[1730].speaker SPEAKER_31
transcript.pyannote[1730].start 12557.88284375
transcript.pyannote[1730].end 12562.48971875
transcript.pyannote[1731].speaker SPEAKER_03
transcript.pyannote[1731].start 12564.97034375
transcript.pyannote[1731].end 12567.97409375
transcript.pyannote[1732].speaker SPEAKER_31
transcript.pyannote[1732].start 12570.47159375
transcript.pyannote[1732].end 12570.52221875
transcript.pyannote[1733].speaker SPEAKER_03
transcript.pyannote[1733].start 12570.52221875
transcript.pyannote[1733].end 12572.24346875
transcript.pyannote[1734].speaker SPEAKER_31
transcript.pyannote[1734].start 12572.69909375
transcript.pyannote[1734].end 12574.04909375
transcript.pyannote[1735].speaker SPEAKER_03
transcript.pyannote[1735].start 12576.07409375
transcript.pyannote[1735].end 12579.83721875
transcript.pyannote[1736].speaker SPEAKER_03
transcript.pyannote[1736].start 12580.32659375
transcript.pyannote[1736].end 12580.34346875
transcript.pyannote[1737].speaker SPEAKER_01
transcript.pyannote[1737].start 12580.34346875
transcript.pyannote[1737].end 12580.96784375
transcript.pyannote[1738].speaker SPEAKER_03
transcript.pyannote[1738].start 12580.66409375
transcript.pyannote[1738].end 12582.92534375
transcript.pyannote[1739].speaker SPEAKER_03
transcript.pyannote[1739].start 12583.66784375
transcript.pyannote[1739].end 12585.55784375
transcript.pyannote[1740].speaker SPEAKER_03
transcript.pyannote[1740].start 12586.26659375
transcript.pyannote[1740].end 12590.89034375
transcript.pyannote[1741].speaker SPEAKER_03
transcript.pyannote[1741].start 12591.63284375
transcript.pyannote[1741].end 12592.62846875
transcript.pyannote[1742].speaker SPEAKER_03
transcript.pyannote[1742].start 12594.01221875
transcript.pyannote[1742].end 12595.85159375
transcript.pyannote[1743].speaker SPEAKER_03
transcript.pyannote[1743].start 12596.18909375
transcript.pyannote[1743].end 12597.57284375
transcript.pyannote[1744].speaker SPEAKER_03
transcript.pyannote[1744].start 12598.09596875
transcript.pyannote[1744].end 12599.19284375
transcript.pyannote[1745].speaker SPEAKER_24
transcript.pyannote[1745].start 12599.83409375
transcript.pyannote[1745].end 12600.57659375
transcript.pyannote[1746].speaker SPEAKER_03
transcript.pyannote[1746].start 12601.03221875
transcript.pyannote[1746].end 12601.28534375
transcript.pyannote[1747].speaker SPEAKER_03
transcript.pyannote[1747].start 12602.46659375
transcript.pyannote[1747].end 12604.66034375
transcript.pyannote[1748].speaker SPEAKER_03
transcript.pyannote[1748].start 12606.66846875
transcript.pyannote[1748].end 12606.97221875
transcript.pyannote[1749].speaker SPEAKER_03
transcript.pyannote[1749].start 12607.76534375
transcript.pyannote[1749].end 12608.18721875
transcript.pyannote[1750].speaker SPEAKER_03
transcript.pyannote[1750].start 12609.35159375
transcript.pyannote[1750].end 12610.07721875
transcript.pyannote[1751].speaker SPEAKER_03
transcript.pyannote[1751].start 12612.20346875
transcript.pyannote[1751].end 12613.57034375
transcript.pyannote[1752].speaker SPEAKER_24
transcript.pyannote[1752].start 12617.65409375
transcript.pyannote[1752].end 12621.58596875
transcript.pyannote[1753].speaker SPEAKER_03
transcript.pyannote[1753].start 12621.67034375
transcript.pyannote[1753].end 12624.74159375
transcript.pyannote[1754].speaker SPEAKER_03
transcript.pyannote[1754].start 12625.01159375
transcript.pyannote[1754].end 12638.12346875
transcript.pyannote[1755].speaker SPEAKER_03
transcript.pyannote[1755].start 12638.41034375
transcript.pyannote[1755].end 12655.16721875
transcript.pyannote[1756].speaker SPEAKER_03
transcript.pyannote[1756].start 12655.53846875
transcript.pyannote[1756].end 12663.08159375
transcript.pyannote[1757].speaker SPEAKER_03
transcript.pyannote[1757].start 12664.61721875
transcript.pyannote[1757].end 12670.32096875
transcript.pyannote[1758].speaker SPEAKER_03
transcript.pyannote[1758].start 12670.77659375
transcript.pyannote[1758].end 12673.42596875
transcript.pyannote[1759].speaker SPEAKER_03
transcript.pyannote[1759].start 12674.03346875
transcript.pyannote[1759].end 12675.07971875
transcript.pyannote[1760].speaker SPEAKER_03
transcript.pyannote[1760].start 12675.63659375
transcript.pyannote[1760].end 12676.69971875
transcript.pyannote[1761].speaker SPEAKER_03
transcript.pyannote[1761].start 12676.93596875
transcript.pyannote[1761].end 12681.23909375
transcript.pyannote[1762].speaker SPEAKER_03
transcript.pyannote[1762].start 12682.50471875
transcript.pyannote[1762].end 12695.26221875
transcript.pyannote[1763].speaker SPEAKER_03
transcript.pyannote[1763].start 12695.38034375
transcript.pyannote[1763].end 12697.96221875
transcript.pyannote[1764].speaker SPEAKER_03
transcript.pyannote[1764].start 12698.36721875
transcript.pyannote[1764].end 12701.08409375
transcript.pyannote[1765].speaker SPEAKER_22
transcript.pyannote[1765].start 12700.94909375
transcript.pyannote[1765].end 12700.96596875
transcript.pyannote[1766].speaker SPEAKER_22
transcript.pyannote[1766].start 12700.98284375
transcript.pyannote[1766].end 12701.03346875
transcript.pyannote[1767].speaker SPEAKER_24
transcript.pyannote[1767].start 12701.08409375
transcript.pyannote[1767].end 12701.25284375
transcript.pyannote[1768].speaker SPEAKER_22
transcript.pyannote[1768].start 12701.25284375
transcript.pyannote[1768].end 12701.30346875
transcript.pyannote[1769].speaker SPEAKER_03
transcript.pyannote[1769].start 12701.30346875
transcript.pyannote[1769].end 12706.28159375
transcript.pyannote[1770].speaker SPEAKER_24
transcript.pyannote[1770].start 12706.19721875
transcript.pyannote[1770].end 12706.26471875
transcript.pyannote[1771].speaker SPEAKER_24
transcript.pyannote[1771].start 12706.28159375
transcript.pyannote[1771].end 12706.50096875
transcript.pyannote[1772].speaker SPEAKER_24
transcript.pyannote[1772].start 12706.53471875
transcript.pyannote[1772].end 12742.02284375
transcript.pyannote[1773].speaker SPEAKER_24
transcript.pyannote[1773].start 12743.06909375
transcript.pyannote[1773].end 12758.13846875
transcript.pyannote[1774].speaker SPEAKER_03
transcript.pyannote[1774].start 12758.81346875
transcript.pyannote[1774].end 12759.70784375
transcript.pyannote[1775].speaker SPEAKER_03
transcript.pyannote[1775].start 12760.51784375
transcript.pyannote[1775].end 12764.11221875
transcript.pyannote[1776].speaker SPEAKER_03
transcript.pyannote[1776].start 12764.68596875
transcript.pyannote[1776].end 12769.63034375
transcript.pyannote[1777].speaker SPEAKER_24
transcript.pyannote[1777].start 12769.73159375
transcript.pyannote[1777].end 12770.60909375
transcript.pyannote[1778].speaker SPEAKER_03
transcript.pyannote[1778].start 12770.76096875
transcript.pyannote[1778].end 12771.28409375
transcript.pyannote[1779].speaker SPEAKER_03
transcript.pyannote[1779].start 12771.63846875
transcript.pyannote[1779].end 12772.14471875
transcript.pyannote[1780].speaker SPEAKER_24
transcript.pyannote[1780].start 12772.80284375
transcript.pyannote[1780].end 12773.07284375
transcript.pyannote[1781].speaker SPEAKER_03
transcript.pyannote[1781].start 12773.07284375
transcript.pyannote[1781].end 12774.62534375
transcript.pyannote[1782].speaker SPEAKER_03
transcript.pyannote[1782].start 12774.97971875
transcript.pyannote[1782].end 12775.01346875
transcript.pyannote[1783].speaker SPEAKER_24
transcript.pyannote[1783].start 12775.01346875
transcript.pyannote[1783].end 12775.84034375
transcript.pyannote[1784].speaker SPEAKER_03
transcript.pyannote[1784].start 12775.06409375
transcript.pyannote[1784].end 12775.09784375
transcript.pyannote[1785].speaker SPEAKER_03
transcript.pyannote[1785].start 12775.11471875
transcript.pyannote[1785].end 12779.85659375
transcript.pyannote[1786].speaker SPEAKER_03
transcript.pyannote[1786].start 12780.07596875
transcript.pyannote[1786].end 12784.49721875
transcript.pyannote[1787].speaker SPEAKER_24
transcript.pyannote[1787].start 12784.58159375
transcript.pyannote[1787].end 12788.34471875
transcript.pyannote[1788].speaker SPEAKER_03
transcript.pyannote[1788].start 12788.49659375
transcript.pyannote[1788].end 12791.16284375
transcript.pyannote[1789].speaker SPEAKER_03
transcript.pyannote[1789].start 12792.98534375
transcript.pyannote[1789].end 12793.40721875
transcript.pyannote[1790].speaker SPEAKER_03
transcript.pyannote[1790].start 12794.70659375
transcript.pyannote[1790].end 12799.26284375
transcript.pyannote[1791].speaker SPEAKER_24
transcript.pyannote[1791].start 12795.09471875
transcript.pyannote[1791].end 12795.46596875
transcript.pyannote[1792].speaker SPEAKER_07
transcript.pyannote[1792].start 12797.91284375
transcript.pyannote[1792].end 12812.91471875
transcript.pyannote[1793].speaker SPEAKER_07
transcript.pyannote[1793].start 12814.36596875
transcript.pyannote[1793].end 12819.46221875
transcript.pyannote[1794].speaker SPEAKER_03
transcript.pyannote[1794].start 12819.25971875
transcript.pyannote[1794].end 12821.52096875
transcript.pyannote[1795].speaker SPEAKER_07
transcript.pyannote[1795].start 12820.40721875
transcript.pyannote[1795].end 12824.13659375
transcript.pyannote[1796].speaker SPEAKER_03
transcript.pyannote[1796].start 12824.50784375
transcript.pyannote[1796].end 12826.00971875
transcript.pyannote[1797].speaker SPEAKER_07
transcript.pyannote[1797].start 12826.43159375
transcript.pyannote[1797].end 12829.21596875
transcript.pyannote[1798].speaker SPEAKER_03
transcript.pyannote[1798].start 12829.84034375
transcript.pyannote[1798].end 12835.69596875
transcript.pyannote[1799].speaker SPEAKER_07
transcript.pyannote[1799].start 12831.15659375
transcript.pyannote[1799].end 12831.49409375
transcript.pyannote[1800].speaker SPEAKER_07
transcript.pyannote[1800].start 12832.43909375
transcript.pyannote[1800].end 12832.79346875
transcript.pyannote[1801].speaker SPEAKER_07
transcript.pyannote[1801].start 12834.71721875
transcript.pyannote[1801].end 12838.88534375
transcript.pyannote[1802].speaker SPEAKER_03
transcript.pyannote[1802].start 12837.43409375
transcript.pyannote[1802].end 12838.49721875
transcript.pyannote[1803].speaker SPEAKER_03
transcript.pyannote[1803].start 12838.51409375
transcript.pyannote[1803].end 12838.75034375
transcript.pyannote[1804].speaker SPEAKER_03
transcript.pyannote[1804].start 12838.88534375
transcript.pyannote[1804].end 12840.50534375
transcript.pyannote[1805].speaker SPEAKER_07
transcript.pyannote[1805].start 12840.45471875
transcript.pyannote[1805].end 12840.87659375
transcript.pyannote[1806].speaker SPEAKER_03
transcript.pyannote[1806].start 12841.19721875
transcript.pyannote[1806].end 12845.92221875
transcript.pyannote[1807].speaker SPEAKER_03
transcript.pyannote[1807].start 12848.79096875
transcript.pyannote[1807].end 12854.73096875
transcript.pyannote[1808].speaker SPEAKER_03
transcript.pyannote[1808].start 12855.11909375
transcript.pyannote[1808].end 12857.75159375
transcript.pyannote[1809].speaker SPEAKER_03
transcript.pyannote[1809].start 12858.29159375
transcript.pyannote[1809].end 12863.25284375
transcript.pyannote[1810].speaker SPEAKER_03
transcript.pyannote[1810].start 12863.79284375
transcript.pyannote[1810].end 12864.85596875
transcript.pyannote[1811].speaker SPEAKER_03
transcript.pyannote[1811].start 12865.46346875
transcript.pyannote[1811].end 12867.43784375
transcript.pyannote[1812].speaker SPEAKER_03
transcript.pyannote[1812].start 12868.09596875
transcript.pyannote[1812].end 12869.81721875
transcript.pyannote[1813].speaker SPEAKER_03
transcript.pyannote[1813].start 12870.12096875
transcript.pyannote[1813].end 12876.16221875
transcript.pyannote[1814].speaker SPEAKER_03
transcript.pyannote[1814].start 12876.61784375
transcript.pyannote[1814].end 12877.47846875
transcript.pyannote[1815].speaker SPEAKER_03
transcript.pyannote[1815].start 12881.84909375
transcript.pyannote[1815].end 12887.04659375
transcript.pyannote[1816].speaker SPEAKER_03
transcript.pyannote[1816].start 12887.38409375
transcript.pyannote[1816].end 12889.72971875
transcript.pyannote[1817].speaker SPEAKER_03
transcript.pyannote[1817].start 12890.84346875
transcript.pyannote[1817].end 12891.46784375
transcript.pyannote[1818].speaker SPEAKER_24
transcript.pyannote[1818].start 12891.46784375
transcript.pyannote[1818].end 12892.63221875
transcript.pyannote[1819].speaker SPEAKER_03
transcript.pyannote[1819].start 12893.03721875
transcript.pyannote[1819].end 12894.03284375
transcript.pyannote[1820].speaker SPEAKER_03
transcript.pyannote[1820].start 12894.79221875
transcript.pyannote[1820].end 12897.20534375
transcript.pyannote[1821].speaker SPEAKER_07
transcript.pyannote[1821].start 12897.79596875
transcript.pyannote[1821].end 12899.58471875
transcript.pyannote[1822].speaker SPEAKER_03
transcript.pyannote[1822].start 12899.65221875
transcript.pyannote[1822].end 12904.02284375
transcript.pyannote[1823].speaker SPEAKER_07
transcript.pyannote[1823].start 12900.58034375
transcript.pyannote[1823].end 12901.32284375
transcript.pyannote[1824].speaker SPEAKER_07
transcript.pyannote[1824].start 12904.27596875
transcript.pyannote[1824].end 12907.90409375
transcript.pyannote[1825].speaker SPEAKER_03
transcript.pyannote[1825].start 12907.90409375
transcript.pyannote[1825].end 12912.57846875
transcript.pyannote[1826].speaker SPEAKER_07
transcript.pyannote[1826].start 12912.32534375
transcript.pyannote[1826].end 12912.89909375
transcript.pyannote[1827].speaker SPEAKER_03
transcript.pyannote[1827].start 12912.84846875
transcript.pyannote[1827].end 12913.94534375
transcript.pyannote[1828].speaker SPEAKER_07
transcript.pyannote[1828].start 12913.28721875
transcript.pyannote[1828].end 12913.77659375
transcript.pyannote[1829].speaker SPEAKER_07
transcript.pyannote[1829].start 12913.94534375
transcript.pyannote[1829].end 12914.53596875
transcript.pyannote[1830].speaker SPEAKER_03
transcript.pyannote[1830].start 12915.41346875
transcript.pyannote[1830].end 12916.29096875
transcript.pyannote[1831].speaker SPEAKER_07
transcript.pyannote[1831].start 12916.40909375
transcript.pyannote[1831].end 12921.48846875
transcript.pyannote[1832].speaker SPEAKER_07
transcript.pyannote[1832].start 12921.57284375
transcript.pyannote[1832].end 12921.62346875
transcript.pyannote[1833].speaker SPEAKER_03
transcript.pyannote[1833].start 12921.62346875
transcript.pyannote[1833].end 12922.04534375
transcript.pyannote[1834].speaker SPEAKER_07
transcript.pyannote[1834].start 12921.70784375
transcript.pyannote[1834].end 12924.35721875
transcript.pyannote[1835].speaker SPEAKER_03
transcript.pyannote[1835].start 12924.52596875
transcript.pyannote[1835].end 12925.20096875
transcript.pyannote[1836].speaker SPEAKER_03
transcript.pyannote[1836].start 12925.62284375
transcript.pyannote[1836].end 12934.16159375
transcript.pyannote[1837].speaker SPEAKER_03
transcript.pyannote[1837].start 12934.63409375
transcript.pyannote[1837].end 12945.14721875
transcript.pyannote[1838].speaker SPEAKER_03
transcript.pyannote[1838].start 12945.63659375
transcript.pyannote[1838].end 12947.59409375
transcript.pyannote[1839].speaker SPEAKER_03
transcript.pyannote[1839].start 12948.25221875
transcript.pyannote[1839].end 12958.46159375
transcript.pyannote[1840].speaker SPEAKER_03
transcript.pyannote[1840].start 12959.99721875
transcript.pyannote[1840].end 12963.03471875
transcript.pyannote[1841].speaker SPEAKER_03
transcript.pyannote[1841].start 12963.06846875
transcript.pyannote[1841].end 12964.18221875
transcript.pyannote[1842].speaker SPEAKER_03
transcript.pyannote[1842].start 12964.36784375
transcript.pyannote[1842].end 12966.34221875
transcript.pyannote[1843].speaker SPEAKER_03
transcript.pyannote[1843].start 12967.87784375
transcript.pyannote[1843].end 12974.49284375
transcript.pyannote[1844].speaker SPEAKER_24
transcript.pyannote[1844].start 12967.92846875
transcript.pyannote[1844].end 12968.45159375
transcript.pyannote[1845].speaker SPEAKER_24
transcript.pyannote[1845].start 12968.50221875
transcript.pyannote[1845].end 12969.34596875
transcript.pyannote[1846].speaker SPEAKER_03
transcript.pyannote[1846].start 12975.79221875
transcript.pyannote[1846].end 12980.78721875
transcript.pyannote[1847].speaker SPEAKER_03
transcript.pyannote[1847].start 12981.64784375
transcript.pyannote[1847].end 12983.62221875
transcript.pyannote[1848].speaker SPEAKER_03
transcript.pyannote[1848].start 12984.24659375
transcript.pyannote[1848].end 12985.91721875
transcript.pyannote[1849].speaker SPEAKER_03
transcript.pyannote[1849].start 12986.65971875
transcript.pyannote[1849].end 12988.39784375
transcript.pyannote[1850].speaker SPEAKER_03
transcript.pyannote[1850].start 12988.97159375
transcript.pyannote[1850].end 12989.25846875
transcript.pyannote[1851].speaker SPEAKER_03
transcript.pyannote[1851].start 12990.65909375
transcript.pyannote[1851].end 12991.38471875
transcript.pyannote[1852].speaker SPEAKER_03
transcript.pyannote[1852].start 12993.54471875
transcript.pyannote[1852].end 12994.67534375
transcript.pyannote[1853].speaker SPEAKER_03
transcript.pyannote[1853].start 12996.36284375
transcript.pyannote[1853].end 12998.13471875
transcript.pyannote[1854].speaker SPEAKER_03
transcript.pyannote[1854].start 12998.45534375
transcript.pyannote[1854].end 13000.02471875
transcript.pyannote[1855].speaker SPEAKER_03
transcript.pyannote[1855].start 13002.28596875
transcript.pyannote[1855].end 13005.39096875
transcript.pyannote[1856].speaker SPEAKER_03
transcript.pyannote[1856].start 13005.44159375
transcript.pyannote[1856].end 13006.62284375
transcript.pyannote[1857].speaker SPEAKER_03
transcript.pyannote[1857].start 13007.21346875
transcript.pyannote[1857].end 13009.30596875
transcript.pyannote[1858].speaker SPEAKER_03
transcript.pyannote[1858].start 13009.67721875
transcript.pyannote[1858].end 13012.37721875
transcript.pyannote[1859].speaker SPEAKER_03
transcript.pyannote[1859].start 13015.04346875
transcript.pyannote[1859].end 13017.01784375
transcript.pyannote[1860].speaker SPEAKER_03
transcript.pyannote[1860].start 13018.03034375
transcript.pyannote[1860].end 13018.63784375
transcript.pyannote[1861].speaker SPEAKER_03
transcript.pyannote[1861].start 13019.59971875
transcript.pyannote[1861].end 13021.03409375
transcript.pyannote[1862].speaker SPEAKER_03
transcript.pyannote[1862].start 13021.47284375
transcript.pyannote[1862].end 13023.73409375
transcript.pyannote[1863].speaker SPEAKER_03
transcript.pyannote[1863].start 13024.22346875
transcript.pyannote[1863].end 13027.63221875
transcript.pyannote[1864].speaker SPEAKER_03
transcript.pyannote[1864].start 13028.15534375
transcript.pyannote[1864].end 13032.57659375
transcript.pyannote[1865].speaker SPEAKER_03
transcript.pyannote[1865].start 13033.75784375
transcript.pyannote[1865].end 13035.20909375
transcript.pyannote[1866].speaker SPEAKER_03
transcript.pyannote[1866].start 13036.69409375
transcript.pyannote[1866].end 13038.88784375
transcript.pyannote[1867].speaker SPEAKER_03
transcript.pyannote[1867].start 13039.57971875
transcript.pyannote[1867].end 13043.93346875
transcript.pyannote[1868].speaker SPEAKER_02
transcript.pyannote[1868].start 13045.90784375
transcript.pyannote[1868].end 13046.09346875
transcript.pyannote[1869].speaker SPEAKER_03
transcript.pyannote[1869].start 13046.09346875
transcript.pyannote[1869].end 13047.37596875
transcript.pyannote[1870].speaker SPEAKER_03
transcript.pyannote[1870].start 13047.66284375
transcript.pyannote[1870].end 13059.52596875
transcript.pyannote[1871].speaker SPEAKER_03
transcript.pyannote[1871].start 13060.40346875
transcript.pyannote[1871].end 13063.49159375
transcript.pyannote[1872].speaker SPEAKER_03
transcript.pyannote[1872].start 13064.36909375
transcript.pyannote[1872].end 13065.71909375
transcript.pyannote[1873].speaker SPEAKER_03
transcript.pyannote[1873].start 13066.15784375
transcript.pyannote[1873].end 13066.47846875
transcript.pyannote[1874].speaker SPEAKER_03
transcript.pyannote[1874].start 13067.08596875
transcript.pyannote[1874].end 13068.77346875
transcript.pyannote[1875].speaker SPEAKER_03
transcript.pyannote[1875].start 13069.39784375
transcript.pyannote[1875].end 13073.02596875
transcript.pyannote[1876].speaker SPEAKER_03
transcript.pyannote[1876].start 13073.29596875
transcript.pyannote[1876].end 13076.51909375
transcript.pyannote[1877].speaker SPEAKER_03
transcript.pyannote[1877].start 13076.56971875
transcript.pyannote[1877].end 13078.34159375
transcript.pyannote[1878].speaker SPEAKER_03
transcript.pyannote[1878].start 13079.10096875
transcript.pyannote[1878].end 13088.23034375
transcript.pyannote[1879].speaker SPEAKER_03
transcript.pyannote[1879].start 13088.95596875
transcript.pyannote[1879].end 13090.87971875
transcript.pyannote[1880].speaker SPEAKER_03
transcript.pyannote[1880].start 13091.53784375
transcript.pyannote[1880].end 13097.96721875
transcript.pyannote[1881].speaker SPEAKER_03
transcript.pyannote[1881].start 13098.35534375
transcript.pyannote[1881].end 13099.24971875
transcript.pyannote[1882].speaker SPEAKER_03
transcript.pyannote[1882].start 13099.82346875
transcript.pyannote[1882].end 13100.71784375
transcript.pyannote[1883].speaker SPEAKER_03
transcript.pyannote[1883].start 13100.97096875
transcript.pyannote[1883].end 13101.76409375
transcript.pyannote[1884].speaker SPEAKER_03
transcript.pyannote[1884].start 13102.15221875
transcript.pyannote[1884].end 13104.80159375
transcript.pyannote[1885].speaker SPEAKER_03
transcript.pyannote[1885].start 13105.45971875
transcript.pyannote[1885].end 13107.09659375
transcript.pyannote[1886].speaker SPEAKER_03
transcript.pyannote[1886].start 13107.61971875
transcript.pyannote[1886].end 13108.85159375
transcript.pyannote[1887].speaker SPEAKER_03
transcript.pyannote[1887].start 13109.17221875
transcript.pyannote[1887].end 13110.20159375
transcript.pyannote[1888].speaker SPEAKER_03
transcript.pyannote[1888].start 13110.77534375
transcript.pyannote[1888].end 13112.20971875
transcript.pyannote[1889].speaker SPEAKER_03
transcript.pyannote[1889].start 13112.98596875
transcript.pyannote[1889].end 13113.54284375
transcript.pyannote[1890].speaker SPEAKER_03
transcript.pyannote[1890].start 13113.77909375
transcript.pyannote[1890].end 13115.44971875
transcript.pyannote[1891].speaker SPEAKER_03
transcript.pyannote[1891].start 13115.90534375
transcript.pyannote[1891].end 13116.88409375
transcript.pyannote[1892].speaker SPEAKER_03
transcript.pyannote[1892].start 13117.44096875
transcript.pyannote[1892].end 13118.63909375
transcript.pyannote[1893].speaker SPEAKER_03
transcript.pyannote[1893].start 13121.52471875
transcript.pyannote[1893].end 13122.67221875
transcript.pyannote[1894].speaker SPEAKER_03
transcript.pyannote[1894].start 13123.19534375
transcript.pyannote[1894].end 13127.22846875
transcript.pyannote[1895].speaker SPEAKER_24
transcript.pyannote[1895].start 13125.43971875
transcript.pyannote[1895].end 13126.14846875
transcript.pyannote[1896].speaker SPEAKER_03
transcript.pyannote[1896].start 13127.39721875
transcript.pyannote[1896].end 13129.54034375
transcript.pyannote[1897].speaker SPEAKER_24
transcript.pyannote[1897].start 13129.54034375
transcript.pyannote[1897].end 13130.41784375
transcript.pyannote[1898].speaker SPEAKER_03
transcript.pyannote[1898].start 13130.94096875
transcript.pyannote[1898].end 13131.73409375
transcript.pyannote[1899].speaker SPEAKER_24
transcript.pyannote[1899].start 13131.90284375
transcript.pyannote[1899].end 13132.18971875
transcript.pyannote[1900].speaker SPEAKER_03
transcript.pyannote[1900].start 13132.88159375
transcript.pyannote[1900].end 13133.26971875
transcript.pyannote[1901].speaker SPEAKER_24
transcript.pyannote[1901].start 13133.37096875
transcript.pyannote[1901].end 13133.62409375
transcript.pyannote[1902].speaker SPEAKER_03
transcript.pyannote[1902].start 13133.79284375
transcript.pyannote[1902].end 13134.94034375
transcript.pyannote[1903].speaker SPEAKER_24
transcript.pyannote[1903].start 13137.30284375
transcript.pyannote[1903].end 13138.45034375
transcript.pyannote[1904].speaker SPEAKER_03
transcript.pyannote[1904].start 13138.97346875
transcript.pyannote[1904].end 13140.57659375
transcript.pyannote[1905].speaker SPEAKER_24
transcript.pyannote[1905].start 13140.77909375
transcript.pyannote[1905].end 13143.42846875
transcript.pyannote[1906].speaker SPEAKER_03
transcript.pyannote[1906].start 13143.63096875
transcript.pyannote[1906].end 13144.71096875
transcript.pyannote[1907].speaker SPEAKER_24
transcript.pyannote[1907].start 13144.13721875
transcript.pyannote[1907].end 13144.15409375
transcript.pyannote[1908].speaker SPEAKER_24
transcript.pyannote[1908].start 13144.82909375
transcript.pyannote[1908].end 13144.91346875
transcript.pyannote[1909].speaker SPEAKER_03
transcript.pyannote[1909].start 13146.83721875
transcript.pyannote[1909].end 13147.91721875
transcript.pyannote[1910].speaker SPEAKER_24
transcript.pyannote[1910].start 13152.82784375
transcript.pyannote[1910].end 13152.97971875
transcript.pyannote[1911].speaker SPEAKER_24
transcript.pyannote[1911].start 13154.43096875
transcript.pyannote[1911].end 13159.69596875
transcript.pyannote[1912].speaker SPEAKER_03
transcript.pyannote[1912].start 13159.56096875
transcript.pyannote[1912].end 13159.66221875
transcript.pyannote[1913].speaker SPEAKER_03
transcript.pyannote[1913].start 13159.69596875
transcript.pyannote[1913].end 13160.92784375
transcript.pyannote[1914].speaker SPEAKER_24
transcript.pyannote[1914].start 13162.02471875
transcript.pyannote[1914].end 13195.13346875
transcript.pyannote[1915].speaker SPEAKER_03
transcript.pyannote[1915].start 13165.60221875
transcript.pyannote[1915].end 13166.00721875
transcript.pyannote[1916].speaker SPEAKER_03
transcript.pyannote[1916].start 13195.28534375
transcript.pyannote[1916].end 13195.90971875
transcript.pyannote[1917].speaker SPEAKER_03
transcript.pyannote[1917].start 13196.12909375
transcript.pyannote[1917].end 13210.01721875
transcript.pyannote[1918].speaker SPEAKER_03
transcript.pyannote[1918].start 13210.43909375
transcript.pyannote[1918].end 13216.58159375
transcript.pyannote[1919].speaker SPEAKER_03
transcript.pyannote[1919].start 13217.99909375
transcript.pyannote[1919].end 13222.20096875
transcript.pyannote[1920].speaker SPEAKER_03
transcript.pyannote[1920].start 13222.38659375
transcript.pyannote[1920].end 13223.31471875
transcript.pyannote[1921].speaker SPEAKER_03
transcript.pyannote[1921].start 13224.29346875
transcript.pyannote[1921].end 13237.91159375
transcript.pyannote[1922].speaker SPEAKER_03
transcript.pyannote[1922].start 13238.24909375
transcript.pyannote[1922].end 13245.38721875
transcript.pyannote[1923].speaker SPEAKER_03
transcript.pyannote[1923].start 13246.60221875
transcript.pyannote[1923].end 13247.74971875
transcript.pyannote[1924].speaker SPEAKER_22
transcript.pyannote[1924].start 13247.73284375
transcript.pyannote[1924].end 13248.03659375
transcript.pyannote[1925].speaker SPEAKER_03
transcript.pyannote[1925].start 13248.35721875
transcript.pyannote[1925].end 13258.00971875
transcript.pyannote[1926].speaker SPEAKER_03
transcript.pyannote[1926].start 13258.27971875
transcript.pyannote[1926].end 13260.69284375
transcript.pyannote[1927].speaker SPEAKER_24
transcript.pyannote[1927].start 13262.05971875
transcript.pyannote[1927].end 13279.66034375
transcript.pyannote[1928].speaker SPEAKER_24
transcript.pyannote[1928].start 13279.84596875
transcript.pyannote[1928].end 13299.79221875
transcript.pyannote[1929].speaker SPEAKER_03
transcript.pyannote[1929].start 13301.02409375
transcript.pyannote[1929].end 13309.74846875
transcript.pyannote[1930].speaker SPEAKER_24
transcript.pyannote[1930].start 13303.48784375
transcript.pyannote[1930].end 13303.75784375
transcript.pyannote[1931].speaker SPEAKER_03
transcript.pyannote[1931].start 13310.32221875
transcript.pyannote[1931].end 13311.50346875
transcript.pyannote[1932].speaker SPEAKER_03
transcript.pyannote[1932].start 13312.14471875
transcript.pyannote[1932].end 13313.42721875
transcript.pyannote[1933].speaker SPEAKER_03
transcript.pyannote[1933].start 13314.23721875
transcript.pyannote[1933].end 13314.97971875
transcript.pyannote[1934].speaker SPEAKER_03
transcript.pyannote[1934].start 13316.46471875
transcript.pyannote[1934].end 13318.70909375
transcript.pyannote[1935].speaker SPEAKER_03
transcript.pyannote[1935].start 13319.19846875
transcript.pyannote[1935].end 13326.72471875
transcript.pyannote[1936].speaker SPEAKER_24
transcript.pyannote[1936].start 13327.60221875
transcript.pyannote[1936].end 13336.78221875
transcript.pyannote[1937].speaker SPEAKER_24
transcript.pyannote[1937].start 13337.30534375
transcript.pyannote[1937].end 13339.93784375
transcript.pyannote[1938].speaker SPEAKER_24
transcript.pyannote[1938].start 13340.32596875
transcript.pyannote[1938].end 13358.78721875
transcript.pyannote[1939].speaker SPEAKER_24
transcript.pyannote[1939].start 13359.09096875
transcript.pyannote[1939].end 13360.32284375
transcript.pyannote[1940].speaker SPEAKER_24
transcript.pyannote[1940].start 13360.76159375
transcript.pyannote[1940].end 13394.15721875
transcript.pyannote[1941].speaker SPEAKER_03
transcript.pyannote[1941].start 13394.22471875
transcript.pyannote[1941].end 13407.18471875
transcript.pyannote[1942].speaker SPEAKER_03
transcript.pyannote[1942].start 13407.70784375
transcript.pyannote[1942].end 13412.17971875
transcript.pyannote[1943].speaker SPEAKER_24
transcript.pyannote[1943].start 13412.68596875
transcript.pyannote[1943].end 13428.54846875
transcript.pyannote[1944].speaker SPEAKER_03
transcript.pyannote[1944].start 13415.41971875
transcript.pyannote[1944].end 13415.82471875
transcript.pyannote[1945].speaker SPEAKER_03
transcript.pyannote[1945].start 13419.13221875
transcript.pyannote[1945].end 13420.41471875
transcript.pyannote[1946].speaker SPEAKER_03
transcript.pyannote[1946].start 13427.77221875
transcript.pyannote[1946].end 13434.28596875
transcript.pyannote[1947].speaker SPEAKER_24
transcript.pyannote[1947].start 13431.07971875
transcript.pyannote[1947].end 13431.40034375
transcript.pyannote[1948].speaker SPEAKER_24
transcript.pyannote[1948].start 13434.58971875
transcript.pyannote[1948].end 13439.04471875
transcript.pyannote[1949].speaker SPEAKER_03
transcript.pyannote[1949].start 13437.66096875
transcript.pyannote[1949].end 13437.74534375
transcript.pyannote[1950].speaker SPEAKER_31
transcript.pyannote[1950].start 13437.74534375
transcript.pyannote[1950].end 13437.88034375
transcript.pyannote[1951].speaker SPEAKER_03
transcript.pyannote[1951].start 13437.88034375
transcript.pyannote[1951].end 13437.96471875
transcript.pyannote[1952].speaker SPEAKER_31
transcript.pyannote[1952].start 13437.96471875
transcript.pyannote[1952].end 13439.09534375
transcript.pyannote[1953].speaker SPEAKER_03
transcript.pyannote[1953].start 13439.04471875
transcript.pyannote[1953].end 13439.97284375
transcript.pyannote[1954].speaker SPEAKER_24
transcript.pyannote[1954].start 13439.97284375
transcript.pyannote[1954].end 13440.02346875
transcript.pyannote[1955].speaker SPEAKER_03
transcript.pyannote[1955].start 13440.02346875
transcript.pyannote[1955].end 13440.36096875
transcript.pyannote[1956].speaker SPEAKER_24
transcript.pyannote[1956].start 13440.36096875
transcript.pyannote[1956].end 13440.37784375
transcript.pyannote[1957].speaker SPEAKER_31
transcript.pyannote[1957].start 13440.95159375
transcript.pyannote[1957].end 13447.04346875
transcript.pyannote[1958].speaker SPEAKER_31
transcript.pyannote[1958].start 13449.16971875
transcript.pyannote[1958].end 13449.49034375
transcript.pyannote[1959].speaker SPEAKER_27
transcript.pyannote[1959].start 13455.31221875
transcript.pyannote[1959].end 13456.88159375
transcript.pyannote[1960].speaker SPEAKER_31
transcript.pyannote[1960].start 13457.32034375
transcript.pyannote[1960].end 13457.70846875
transcript.pyannote[1961].speaker SPEAKER_31
transcript.pyannote[1961].start 13457.82659375
transcript.pyannote[1961].end 13458.90659375
transcript.pyannote[1962].speaker SPEAKER_27
transcript.pyannote[1962].start 13464.67784375
transcript.pyannote[1962].end 13481.80596875
transcript.pyannote[1963].speaker SPEAKER_24
transcript.pyannote[1963].start 13481.80596875
transcript.pyannote[1963].end 13482.37971875
transcript.pyannote[1964].speaker SPEAKER_27
transcript.pyannote[1964].start 13482.37971875
transcript.pyannote[1964].end 13497.16221875
transcript.pyannote[1965].speaker SPEAKER_24
transcript.pyannote[1965].start 13482.97034375
transcript.pyannote[1965].end 13483.35846875
transcript.pyannote[1966].speaker SPEAKER_27
transcript.pyannote[1966].start 13497.36471875
transcript.pyannote[1966].end 13498.81596875
transcript.pyannote[1967].speaker SPEAKER_27
transcript.pyannote[1967].start 13498.96784375
transcript.pyannote[1967].end 13501.68471875
transcript.pyannote[1968].speaker SPEAKER_27
transcript.pyannote[1968].start 13502.88284375
transcript.pyannote[1968].end 13502.89971875
transcript.pyannote[1969].speaker SPEAKER_24
transcript.pyannote[1969].start 13502.89971875
transcript.pyannote[1969].end 13509.58221875
transcript.pyannote[1970].speaker SPEAKER_27
transcript.pyannote[1970].start 13508.41784375
transcript.pyannote[1970].end 13508.53596875
transcript.pyannote[1971].speaker SPEAKER_24
transcript.pyannote[1971].start 13509.76784375
transcript.pyannote[1971].end 13519.60596875
transcript.pyannote[1972].speaker SPEAKER_27
transcript.pyannote[1972].start 13510.07159375
transcript.pyannote[1972].end 13510.93221875
transcript.pyannote[1973].speaker SPEAKER_24
transcript.pyannote[1973].start 13519.96034375
transcript.pyannote[1973].end 13543.46721875
transcript.pyannote[1974].speaker SPEAKER_00
transcript.pyannote[1974].start 13522.35659375
transcript.pyannote[1974].end 13522.72784375
transcript.pyannote[1975].speaker SPEAKER_29
transcript.pyannote[1975].start 13527.75659375
transcript.pyannote[1975].end 13527.97596875
transcript.pyannote[1976].speaker SPEAKER_00
transcript.pyannote[1976].start 13527.97596875
transcript.pyannote[1976].end 13528.09409375
transcript.pyannote[1977].speaker SPEAKER_22
transcript.pyannote[1977].start 13539.13034375
transcript.pyannote[1977].end 13539.14721875
transcript.pyannote[1978].speaker SPEAKER_27
transcript.pyannote[1978].start 13539.14721875
transcript.pyannote[1978].end 13539.53534375
transcript.pyannote[1979].speaker SPEAKER_27
transcript.pyannote[1979].start 13542.28596875
transcript.pyannote[1979].end 13543.88909375
transcript.pyannote[1980].speaker SPEAKER_27
transcript.pyannote[1980].start 13546.09971875
transcript.pyannote[1980].end 13566.70409375
transcript.pyannote[1981].speaker SPEAKER_24
transcript.pyannote[1981].start 13547.75346875
transcript.pyannote[1981].end 13547.78721875
transcript.pyannote[1982].speaker SPEAKER_00
transcript.pyannote[1982].start 13550.35221875
transcript.pyannote[1982].end 13550.50409375
transcript.pyannote[1983].speaker SPEAKER_24
transcript.pyannote[1983].start 13561.11846875
transcript.pyannote[1983].end 13561.67534375
transcript.pyannote[1984].speaker SPEAKER_24
transcript.pyannote[1984].start 13567.02471875
transcript.pyannote[1984].end 13571.78346875
transcript.pyannote[1985].speaker SPEAKER_24
transcript.pyannote[1985].start 13572.34034375
transcript.pyannote[1985].end 13574.34846875
transcript.pyannote[1986].speaker SPEAKER_27
transcript.pyannote[1986].start 13574.34846875
transcript.pyannote[1986].end 13574.39909375
transcript.pyannote[1987].speaker SPEAKER_22
transcript.pyannote[1987].start 13574.39909375
transcript.pyannote[1987].end 13574.68596875
transcript.pyannote[1988].speaker SPEAKER_27
transcript.pyannote[1988].start 13574.68596875
transcript.pyannote[1988].end 13574.75346875
transcript.pyannote[1989].speaker SPEAKER_24
transcript.pyannote[1989].start 13574.75346875
transcript.pyannote[1989].end 13576.13721875
transcript.pyannote[1990].speaker SPEAKER_27
transcript.pyannote[1990].start 13576.03596875
transcript.pyannote[1990].end 13579.05659375
transcript.pyannote[1991].speaker SPEAKER_27
transcript.pyannote[1991].start 13579.78221875
transcript.pyannote[1991].end 13590.48096875
transcript.pyannote[1992].speaker SPEAKER_24
transcript.pyannote[1992].start 13590.00846875
transcript.pyannote[1992].end 13590.51471875
transcript.pyannote[1993].speaker SPEAKER_27
transcript.pyannote[1993].start 13590.51471875
transcript.pyannote[1993].end 13590.54846875
transcript.pyannote[1994].speaker SPEAKER_24
transcript.pyannote[1994].start 13590.54846875
transcript.pyannote[1994].end 13611.96284375
transcript.pyannote[1995].speaker SPEAKER_27
transcript.pyannote[1995].start 13591.30784375
transcript.pyannote[1995].end 13591.86471875
transcript.pyannote[1996].speaker SPEAKER_27
transcript.pyannote[1996].start 13592.43846875
transcript.pyannote[1996].end 13592.59034375
transcript.pyannote[1997].speaker SPEAKER_27
transcript.pyannote[1997].start 13595.22284375
transcript.pyannote[1997].end 13595.88096875
transcript.pyannote[1998].speaker SPEAKER_27
transcript.pyannote[1998].start 13611.96284375
transcript.pyannote[1998].end 13612.03034375
transcript.pyannote[1999].speaker SPEAKER_24
transcript.pyannote[1999].start 13612.03034375
transcript.pyannote[1999].end 13612.97534375
transcript.pyannote[2000].speaker SPEAKER_27
transcript.pyannote[2000].start 13612.97534375
transcript.pyannote[2000].end 13620.53534375
transcript.pyannote[2001].speaker SPEAKER_24
transcript.pyannote[2001].start 13613.65034375
transcript.pyannote[2001].end 13613.98784375
transcript.pyannote[2002].speaker SPEAKER_24
transcript.pyannote[2002].start 13620.53534375
transcript.pyannote[2002].end 13626.74534375
transcript.pyannote[2003].speaker SPEAKER_27
transcript.pyannote[2003].start 13623.28596875
transcript.pyannote[2003].end 13623.70784375
transcript.pyannote[2004].speaker SPEAKER_24
transcript.pyannote[2004].start 13626.96471875
transcript.pyannote[2004].end 13641.59534375
transcript.pyannote[2005].speaker SPEAKER_00
transcript.pyannote[2005].start 13627.94346875
transcript.pyannote[2005].end 13628.21346875
transcript.pyannote[2006].speaker SPEAKER_00
transcript.pyannote[2006].start 13631.11596875
transcript.pyannote[2006].end 13631.13284375
transcript.pyannote[2007].speaker SPEAKER_22
transcript.pyannote[2007].start 13631.13284375
transcript.pyannote[2007].end 13631.31846875
transcript.pyannote[2008].speaker SPEAKER_00
transcript.pyannote[2008].start 13631.31846875
transcript.pyannote[2008].end 13631.38596875
transcript.pyannote[2009].speaker SPEAKER_27
transcript.pyannote[2009].start 13640.12721875
transcript.pyannote[2009].end 13640.97096875
transcript.pyannote[2010].speaker SPEAKER_27
transcript.pyannote[2010].start 13641.00471875
transcript.pyannote[2010].end 13666.70534375
transcript.pyannote[2011].speaker SPEAKER_26
transcript.pyannote[2011].start 13656.37784375
transcript.pyannote[2011].end 13657.27221875
transcript.pyannote[2012].speaker SPEAKER_00
transcript.pyannote[2012].start 13659.65159375
transcript.pyannote[2012].end 13660.03971875
transcript.pyannote[2013].speaker SPEAKER_00
transcript.pyannote[2013].start 13662.03096875
transcript.pyannote[2013].end 13662.06471875
transcript.pyannote[2014].speaker SPEAKER_24
transcript.pyannote[2014].start 13662.06471875
transcript.pyannote[2014].end 13662.33471875
transcript.pyannote[2015].speaker SPEAKER_27
transcript.pyannote[2015].start 13667.36346875
transcript.pyannote[2015].end 13686.17909375
transcript.pyannote[2016].speaker SPEAKER_24
transcript.pyannote[2016].start 13672.39221875
transcript.pyannote[2016].end 13672.72971875
transcript.pyannote[2017].speaker SPEAKER_24
transcript.pyannote[2017].start 13673.37096875
transcript.pyannote[2017].end 13673.48909375
transcript.pyannote[2018].speaker SPEAKER_27
transcript.pyannote[2018].start 13686.87096875
transcript.pyannote[2018].end 13687.41096875
transcript.pyannote[2019].speaker SPEAKER_27
transcript.pyannote[2019].start 13688.59221875
transcript.pyannote[2019].end 13689.90846875
transcript.pyannote[2020].speaker SPEAKER_27
transcript.pyannote[2020].start 13690.34721875
transcript.pyannote[2020].end 13706.02409375
transcript.pyannote[2021].speaker SPEAKER_24
transcript.pyannote[2021].start 13706.02409375
transcript.pyannote[2021].end 13706.14221875
transcript.pyannote[2022].speaker SPEAKER_27
transcript.pyannote[2022].start 13706.14221875
transcript.pyannote[2022].end 13707.03659375
transcript.pyannote[2023].speaker SPEAKER_24
transcript.pyannote[2023].start 13707.03659375
transcript.pyannote[2023].end 13726.17284375
transcript.pyannote[2024].speaker SPEAKER_27
transcript.pyannote[2024].start 13708.72409375
transcript.pyannote[2024].end 13708.90971875
transcript.pyannote[2025].speaker SPEAKER_27
transcript.pyannote[2025].start 13713.39846875
transcript.pyannote[2025].end 13713.73596875
transcript.pyannote[2026].speaker SPEAKER_27
transcript.pyannote[2026].start 13714.98471875
transcript.pyannote[2026].end 13717.95471875
transcript.pyannote[2027].speaker SPEAKER_27
transcript.pyannote[2027].start 13718.74784375
transcript.pyannote[2027].end 13719.43971875
transcript.pyannote[2028].speaker SPEAKER_27
transcript.pyannote[2028].start 13725.10971875
transcript.pyannote[2028].end 13729.73346875
transcript.pyannote[2029].speaker SPEAKER_24
transcript.pyannote[2029].start 13729.02471875
transcript.pyannote[2029].end 13740.97221875
transcript.pyannote[2030].speaker SPEAKER_27
transcript.pyannote[2030].start 13730.49284375
transcript.pyannote[2030].end 13731.35346875
transcript.pyannote[2031].speaker SPEAKER_27
transcript.pyannote[2031].start 13740.97221875
transcript.pyannote[2031].end 13757.23971875
transcript.pyannote[2032].speaker SPEAKER_27
transcript.pyannote[2032].start 13757.64471875
transcript.pyannote[2032].end 13768.37721875
transcript.pyannote[2033].speaker SPEAKER_00
transcript.pyannote[2033].start 13766.38596875
transcript.pyannote[2033].end 13766.82471875
transcript.pyannote[2034].speaker SPEAKER_27
transcript.pyannote[2034].start 13768.54596875
transcript.pyannote[2034].end 13773.43971875
transcript.pyannote[2035].speaker SPEAKER_27
transcript.pyannote[2035].start 13773.67596875
transcript.pyannote[2035].end 13780.39221875
transcript.pyannote[2036].speaker SPEAKER_24
transcript.pyannote[2036].start 13779.71721875
transcript.pyannote[2036].end 13785.13409375
transcript.pyannote[2037].speaker SPEAKER_27
transcript.pyannote[2037].start 13780.66221875
transcript.pyannote[2037].end 13781.50596875
transcript.pyannote[2038].speaker SPEAKER_27
transcript.pyannote[2038].start 13782.33284375
transcript.pyannote[2038].end 13783.76721875
transcript.pyannote[2039].speaker SPEAKER_24
transcript.pyannote[2039].start 13785.65721875
transcript.pyannote[2039].end 13788.96471875
transcript.pyannote[2040].speaker SPEAKER_27
transcript.pyannote[2040].start 13788.96471875
transcript.pyannote[2040].end 13798.95471875
transcript.pyannote[2041].speaker SPEAKER_24
transcript.pyannote[2041].start 13789.11659375
transcript.pyannote[2041].end 13790.56784375
transcript.pyannote[2042].speaker SPEAKER_27
transcript.pyannote[2042].start 13799.76471875
transcript.pyannote[2042].end 13809.53534375
transcript.pyannote[2043].speaker SPEAKER_24
transcript.pyannote[2043].start 13800.18659375
transcript.pyannote[2043].end 13800.32159375
transcript.pyannote[2044].speaker SPEAKER_29
transcript.pyannote[2044].start 13800.32159375
transcript.pyannote[2044].end 13800.96284375
transcript.pyannote[2045].speaker SPEAKER_24
transcript.pyannote[2045].start 13800.96284375
transcript.pyannote[2045].end 13801.03034375
transcript.pyannote[2046].speaker SPEAKER_29
transcript.pyannote[2046].start 13801.03034375
transcript.pyannote[2046].end 13801.55346875
transcript.pyannote[2047].speaker SPEAKER_24
transcript.pyannote[2047].start 13801.55346875
transcript.pyannote[2047].end 13801.60409375
transcript.pyannote[2048].speaker SPEAKER_27
transcript.pyannote[2048].start 13810.09221875
transcript.pyannote[2048].end 13819.08659375
transcript.pyannote[2049].speaker SPEAKER_24
transcript.pyannote[2049].start 13816.65659375
transcript.pyannote[2049].end 13817.02784375
transcript.pyannote[2050].speaker SPEAKER_27
transcript.pyannote[2050].start 13819.99784375
transcript.pyannote[2050].end 13821.26346875
transcript.pyannote[2051].speaker SPEAKER_27
transcript.pyannote[2051].start 13822.37721875
transcript.pyannote[2051].end 13825.75221875
transcript.pyannote[2052].speaker SPEAKER_27
transcript.pyannote[2052].start 13826.25846875
transcript.pyannote[2052].end 13836.19784375
transcript.pyannote[2053].speaker SPEAKER_26
transcript.pyannote[2053].start 13827.08534375
transcript.pyannote[2053].end 13828.30034375
transcript.pyannote[2054].speaker SPEAKER_27
transcript.pyannote[2054].start 13836.70409375
transcript.pyannote[2054].end 13837.90221875
transcript.pyannote[2055].speaker SPEAKER_24
transcript.pyannote[2055].start 13837.90221875
transcript.pyannote[2055].end 13838.47596875
transcript.pyannote[2056].speaker SPEAKER_27
transcript.pyannote[2056].start 13838.47596875
transcript.pyannote[2056].end 13841.66534375
transcript.pyannote[2057].speaker SPEAKER_24
transcript.pyannote[2057].start 13841.66534375
transcript.pyannote[2057].end 13841.69909375
transcript.pyannote[2058].speaker SPEAKER_27
transcript.pyannote[2058].start 13841.69909375
transcript.pyannote[2058].end 13852.19534375
transcript.pyannote[2059].speaker SPEAKER_27
transcript.pyannote[2059].start 13853.71409375
transcript.pyannote[2059].end 13860.22784375
transcript.pyannote[2060].speaker SPEAKER_27
transcript.pyannote[2060].start 13860.58221875
transcript.pyannote[2060].end 13862.03346875
transcript.pyannote[2061].speaker SPEAKER_27
transcript.pyannote[2061].start 13862.35409375
transcript.pyannote[2061].end 13864.02471875
transcript.pyannote[2062].speaker SPEAKER_24
transcript.pyannote[2062].start 13864.02471875
transcript.pyannote[2062].end 13865.83034375
transcript.pyannote[2063].speaker SPEAKER_22
transcript.pyannote[2063].start 13865.12159375
transcript.pyannote[2063].end 13865.35784375
transcript.pyannote[2064].speaker SPEAKER_27
transcript.pyannote[2064].start 13865.35784375
transcript.pyannote[2064].end 13865.39159375
transcript.pyannote[2065].speaker SPEAKER_24
transcript.pyannote[2065].start 13866.01596875
transcript.pyannote[2065].end 13873.32284375
transcript.pyannote[2066].speaker SPEAKER_29
transcript.pyannote[2066].start 13873.32284375
transcript.pyannote[2066].end 13873.62659375
transcript.pyannote[2067].speaker SPEAKER_24
transcript.pyannote[2067].start 13875.22971875
transcript.pyannote[2067].end 13875.63471875
transcript.pyannote[2068].speaker SPEAKER_24
transcript.pyannote[2068].start 13876.63034375
transcript.pyannote[2068].end 13880.34284375
transcript.pyannote[2069].speaker SPEAKER_24
transcript.pyannote[2069].start 13880.76471875
transcript.pyannote[2069].end 13882.08096875
transcript.pyannote[2070].speaker SPEAKER_27
transcript.pyannote[2070].start 13882.08096875
transcript.pyannote[2070].end 13882.16534375
transcript.pyannote[2071].speaker SPEAKER_24
transcript.pyannote[2071].start 13882.16534375
transcript.pyannote[2071].end 13882.18221875
transcript.pyannote[2072].speaker SPEAKER_24
transcript.pyannote[2072].start 13882.68846875
transcript.pyannote[2072].end 13883.73471875
transcript.pyannote[2073].speaker SPEAKER_27
transcript.pyannote[2073].start 13883.73471875
transcript.pyannote[2073].end 13896.17159375
transcript.pyannote[2074].speaker SPEAKER_24
transcript.pyannote[2074].start 13894.43346875
transcript.pyannote[2074].end 13895.61471875
transcript.pyannote[2075].speaker SPEAKER_24
transcript.pyannote[2075].start 13896.17159375
transcript.pyannote[2075].end 13896.20534375
transcript.pyannote[2076].speaker SPEAKER_27
transcript.pyannote[2076].start 13896.20534375
transcript.pyannote[2076].end 13896.86346875
transcript.pyannote[2077].speaker SPEAKER_24
transcript.pyannote[2077].start 13896.22221875
transcript.pyannote[2077].end 13900.59284375
transcript.pyannote[2078].speaker SPEAKER_27
transcript.pyannote[2078].start 13897.90971875
transcript.pyannote[2078].end 13898.19659375
transcript.pyannote[2079].speaker SPEAKER_29
transcript.pyannote[2079].start 13900.59284375
transcript.pyannote[2079].end 13900.60971875
transcript.pyannote[2080].speaker SPEAKER_27
transcript.pyannote[2080].start 13900.60971875
transcript.pyannote[2080].end 13900.86284375
transcript.pyannote[2081].speaker SPEAKER_29
transcript.pyannote[2081].start 13900.86284375
transcript.pyannote[2081].end 13900.96409375
transcript.pyannote[2082].speaker SPEAKER_24
transcript.pyannote[2082].start 13900.99784375
transcript.pyannote[2082].end 13907.96721875
transcript.pyannote[2083].speaker SPEAKER_22
transcript.pyannote[2083].start 13908.08534375
transcript.pyannote[2083].end 13908.11909375
transcript.pyannote[2084].speaker SPEAKER_29
transcript.pyannote[2084].start 13908.11909375
transcript.pyannote[2084].end 13908.40596875
transcript.pyannote[2085].speaker SPEAKER_22
transcript.pyannote[2085].start 13908.40596875
transcript.pyannote[2085].end 13908.42284375
transcript.pyannote[2086].speaker SPEAKER_29
transcript.pyannote[2086].start 13908.42284375
transcript.pyannote[2086].end 13908.43971875
transcript.pyannote[2087].speaker SPEAKER_24
transcript.pyannote[2087].start 13908.57471875
transcript.pyannote[2087].end 13911.93284375
transcript.pyannote[2088].speaker SPEAKER_22
transcript.pyannote[2088].start 13908.82784375
transcript.pyannote[2088].end 13909.03034375
transcript.pyannote[2089].speaker SPEAKER_27
transcript.pyannote[2089].start 13909.03034375
transcript.pyannote[2089].end 13909.70534375
transcript.pyannote[2090].speaker SPEAKER_27
transcript.pyannote[2090].start 13909.94159375
transcript.pyannote[2090].end 13911.78096875
transcript.pyannote[2091].speaker SPEAKER_27
transcript.pyannote[2091].start 13911.93284375
transcript.pyannote[2091].end 13911.94971875
transcript.pyannote[2092].speaker SPEAKER_24
transcript.pyannote[2092].start 13911.94971875
transcript.pyannote[2092].end 13913.63721875
transcript.pyannote[2093].speaker SPEAKER_27
transcript.pyannote[2093].start 13912.55721875
transcript.pyannote[2093].end 13912.79346875
transcript.pyannote[2094].speaker SPEAKER_27
transcript.pyannote[2094].start 13913.63721875
transcript.pyannote[2094].end 13914.39659375
transcript.pyannote[2095].speaker SPEAKER_24
transcript.pyannote[2095].start 13913.68784375
transcript.pyannote[2095].end 13914.54846875
transcript.pyannote[2096].speaker SPEAKER_27
transcript.pyannote[2096].start 13914.43034375
transcript.pyannote[2096].end 13924.77471875
transcript.pyannote[2097].speaker SPEAKER_24
transcript.pyannote[2097].start 13915.37534375
transcript.pyannote[2097].end 13915.88159375
transcript.pyannote[2098].speaker SPEAKER_29
transcript.pyannote[2098].start 13920.23534375
transcript.pyannote[2098].end 13920.53909375
transcript.pyannote[2099].speaker SPEAKER_27
transcript.pyannote[2099].start 13925.36534375
transcript.pyannote[2099].end 13930.88346875
transcript.pyannote[2100].speaker SPEAKER_27
transcript.pyannote[2100].start 13931.11971875
transcript.pyannote[2100].end 13934.22471875
transcript.pyannote[2101].speaker SPEAKER_24
transcript.pyannote[2101].start 13931.67659375
transcript.pyannote[2101].end 13932.41909375
transcript.pyannote[2102].speaker SPEAKER_24
transcript.pyannote[2102].start 13933.53284375
transcript.pyannote[2102].end 13934.20784375
transcript.pyannote[2103].speaker SPEAKER_24
transcript.pyannote[2103].start 13934.22471875
transcript.pyannote[2103].end 13937.09346875
transcript.pyannote[2104].speaker SPEAKER_27
transcript.pyannote[2104].start 13937.09346875
transcript.pyannote[2104].end 13937.24534375
transcript.pyannote[2105].speaker SPEAKER_22
transcript.pyannote[2105].start 13937.24534375
transcript.pyannote[2105].end 13937.31284375
transcript.pyannote[2106].speaker SPEAKER_24
transcript.pyannote[2106].start 13937.31284375
transcript.pyannote[2106].end 13945.83471875
transcript.pyannote[2107].speaker SPEAKER_22
transcript.pyannote[2107].start 13944.61971875
transcript.pyannote[2107].end 13944.99096875
transcript.pyannote[2108].speaker SPEAKER_27
transcript.pyannote[2108].start 13944.99096875
transcript.pyannote[2108].end 13945.02471875
transcript.pyannote[2109].speaker SPEAKER_24
transcript.pyannote[2109].start 13946.66159375
transcript.pyannote[2109].end 13950.94784375
transcript.pyannote[2110].speaker SPEAKER_27
transcript.pyannote[2110].start 13950.94784375
transcript.pyannote[2110].end 13984.05659375
transcript.pyannote[2111].speaker SPEAKER_24
transcript.pyannote[2111].start 13956.71909375
transcript.pyannote[2111].end 13957.47846875
transcript.pyannote[2112].speaker SPEAKER_24
transcript.pyannote[2112].start 13957.54596875
transcript.pyannote[2112].end 13958.49096875
transcript.pyannote[2113].speaker SPEAKER_00
transcript.pyannote[2113].start 13958.49096875
transcript.pyannote[2113].end 13958.76096875
transcript.pyannote[2114].speaker SPEAKER_24
transcript.pyannote[2114].start 13958.76096875
transcript.pyannote[2114].end 13959.21659375
transcript.pyannote[2115].speaker SPEAKER_24
transcript.pyannote[2115].start 13959.70596875
transcript.pyannote[2115].end 13959.80721875
transcript.pyannote[2116].speaker SPEAKER_00
transcript.pyannote[2116].start 13962.00096875
transcript.pyannote[2116].end 13962.91221875
transcript.pyannote[2117].speaker SPEAKER_24
transcript.pyannote[2117].start 13980.05721875
transcript.pyannote[2117].end 13980.19221875
transcript.pyannote[2118].speaker SPEAKER_24
transcript.pyannote[2118].start 13983.07784375
transcript.pyannote[2118].end 13983.39846875
transcript.pyannote[2119].speaker SPEAKER_24
transcript.pyannote[2119].start 13984.78221875
transcript.pyannote[2119].end 13984.81596875
transcript.pyannote[2120].speaker SPEAKER_27
transcript.pyannote[2120].start 13984.81596875
transcript.pyannote[2120].end 14000.83034375
transcript.pyannote[2121].speaker SPEAKER_24
transcript.pyannote[2121].start 13993.94534375
transcript.pyannote[2121].end 13995.12659375
transcript.pyannote[2122].speaker SPEAKER_27
transcript.pyannote[2122].start 14001.33659375
transcript.pyannote[2122].end 14001.62346875
transcript.pyannote[2123].speaker SPEAKER_27
transcript.pyannote[2123].start 14002.56846875
transcript.pyannote[2123].end 14007.02346875
transcript.pyannote[2124].speaker SPEAKER_24
transcript.pyannote[2124].start 14006.39909375
transcript.pyannote[2124].end 14006.70284375
transcript.pyannote[2125].speaker SPEAKER_24
transcript.pyannote[2125].start 14007.02346875
transcript.pyannote[2125].end 14010.31409375
transcript.pyannote[2126].speaker SPEAKER_27
transcript.pyannote[2126].start 14010.48284375
transcript.pyannote[2126].end 14010.82034375
transcript.pyannote[2127].speaker SPEAKER_24
transcript.pyannote[2127].start 14010.82034375
transcript.pyannote[2127].end 14012.40659375
transcript.pyannote[2128].speaker SPEAKER_27
transcript.pyannote[2128].start 14012.49096875
transcript.pyannote[2128].end 14012.98034375
transcript.pyannote[2129].speaker SPEAKER_24
transcript.pyannote[2129].start 14012.98034375
transcript.pyannote[2129].end 14013.31784375
transcript.pyannote[2130].speaker SPEAKER_27
transcript.pyannote[2130].start 14013.31784375
transcript.pyannote[2130].end 14025.75471875
transcript.pyannote[2131].speaker SPEAKER_22
transcript.pyannote[2131].start 14025.70409375
transcript.pyannote[2131].end 14026.09221875
transcript.pyannote[2132].speaker SPEAKER_27
transcript.pyannote[2132].start 14026.02471875
transcript.pyannote[2132].end 14027.25659375
transcript.pyannote[2133].speaker SPEAKER_27
transcript.pyannote[2133].start 14027.71221875
transcript.pyannote[2133].end 14028.28596875
transcript.pyannote[2134].speaker SPEAKER_27
transcript.pyannote[2134].start 14028.69096875
transcript.pyannote[2134].end 14048.29971875
transcript.pyannote[2135].speaker SPEAKER_27
transcript.pyannote[2135].start 14049.10971875
transcript.pyannote[2135].end 14051.47221875
transcript.pyannote[2136].speaker SPEAKER_24
transcript.pyannote[2136].start 14049.86909375
transcript.pyannote[2136].end 14051.45534375
transcript.pyannote[2137].speaker SPEAKER_24
transcript.pyannote[2137].start 14051.47221875
transcript.pyannote[2137].end 14054.66159375
transcript.pyannote[2138].speaker SPEAKER_27
transcript.pyannote[2138].start 14054.00346875
transcript.pyannote[2138].end 14060.70284375
transcript.pyannote[2139].speaker SPEAKER_24
transcript.pyannote[2139].start 14060.31471875
transcript.pyannote[2139].end 14060.63534375
transcript.pyannote[2140].speaker SPEAKER_24
transcript.pyannote[2140].start 14060.70284375
transcript.pyannote[2140].end 14060.92221875
transcript.pyannote[2141].speaker SPEAKER_27
transcript.pyannote[2141].start 14060.92221875
transcript.pyannote[2141].end 14076.98721875
transcript.pyannote[2142].speaker SPEAKER_00
transcript.pyannote[2142].start 14070.00096875
transcript.pyannote[2142].end 14070.40596875
transcript.pyannote[2143].speaker SPEAKER_00
transcript.pyannote[2143].start 14071.43534375
transcript.pyannote[2143].end 14072.02596875
transcript.pyannote[2144].speaker SPEAKER_31
transcript.pyannote[2144].start 14076.04221875
transcript.pyannote[2144].end 14076.46409375
transcript.pyannote[2145].speaker SPEAKER_31
transcript.pyannote[2145].start 14077.45971875
transcript.pyannote[2145].end 14084.37846875
transcript.pyannote[2146].speaker SPEAKER_23
transcript.pyannote[2146].start 14088.34409375
transcript.pyannote[2146].end 14090.13284375
transcript.pyannote[2147].speaker SPEAKER_31
transcript.pyannote[2147].start 14090.82471875
transcript.pyannote[2147].end 14092.27596875
transcript.pyannote[2148].speaker SPEAKER_24
transcript.pyannote[2148].start 14096.56221875
transcript.pyannote[2148].end 14097.08534375
transcript.pyannote[2149].speaker SPEAKER_23
transcript.pyannote[2149].start 14097.22034375
transcript.pyannote[2149].end 14133.21471875
transcript.pyannote[2150].speaker SPEAKER_23
transcript.pyannote[2150].start 14133.92346875
transcript.pyannote[2150].end 14134.22721875
transcript.pyannote[2151].speaker SPEAKER_28
transcript.pyannote[2151].start 14134.78409375
transcript.pyannote[2151].end 14190.53909375
transcript.pyannote[2152].speaker SPEAKER_00
transcript.pyannote[2152].start 14154.71346875
transcript.pyannote[2152].end 14155.11846875
transcript.pyannote[2153].speaker SPEAKER_00
transcript.pyannote[2153].start 14174.01846875
transcript.pyannote[2153].end 14174.49096875
transcript.pyannote[2154].speaker SPEAKER_23
transcript.pyannote[2154].start 14182.45596875
transcript.pyannote[2154].end 14183.01284375
transcript.pyannote[2155].speaker SPEAKER_23
transcript.pyannote[2155].start 14190.53909375
transcript.pyannote[2155].end 14190.58971875
transcript.pyannote[2156].speaker SPEAKER_23
transcript.pyannote[2156].start 14190.64034375
transcript.pyannote[2156].end 14203.78596875
transcript.pyannote[2157].speaker SPEAKER_28
transcript.pyannote[2157].start 14204.02221875
transcript.pyannote[2157].end 14205.16971875
transcript.pyannote[2158].speaker SPEAKER_28
transcript.pyannote[2158].start 14205.74346875
transcript.pyannote[2158].end 14246.05784375
transcript.pyannote[2159].speaker SPEAKER_00
transcript.pyannote[2159].start 14213.55659375
transcript.pyannote[2159].end 14213.96159375
transcript.pyannote[2160].speaker SPEAKER_00
transcript.pyannote[2160].start 14223.39471875
transcript.pyannote[2160].end 14223.41159375
transcript.pyannote[2161].speaker SPEAKER_29
transcript.pyannote[2161].start 14223.41159375
transcript.pyannote[2161].end 14223.86721875
transcript.pyannote[2162].speaker SPEAKER_29
transcript.pyannote[2162].start 14224.84596875
transcript.pyannote[2162].end 14225.33534375
transcript.pyannote[2163].speaker SPEAKER_00
transcript.pyannote[2163].start 14231.88284375
transcript.pyannote[2163].end 14232.06846875
transcript.pyannote[2164].speaker SPEAKER_00
transcript.pyannote[2164].start 14233.38471875
transcript.pyannote[2164].end 14233.99221875
transcript.pyannote[2165].speaker SPEAKER_00
transcript.pyannote[2165].start 14238.21096875
transcript.pyannote[2165].end 14238.26159375
transcript.pyannote[2166].speaker SPEAKER_23
transcript.pyannote[2166].start 14238.26159375
transcript.pyannote[2166].end 14238.68346875
transcript.pyannote[2167].speaker SPEAKER_00
transcript.pyannote[2167].start 14238.68346875
transcript.pyannote[2167].end 14238.70034375
transcript.pyannote[2168].speaker SPEAKER_23
transcript.pyannote[2168].start 14239.37534375
transcript.pyannote[2168].end 14239.88159375
transcript.pyannote[2169].speaker SPEAKER_00
transcript.pyannote[2169].start 14239.88159375
transcript.pyannote[2169].end 14239.89846875
transcript.pyannote[2170].speaker SPEAKER_23
transcript.pyannote[2170].start 14239.98284375
transcript.pyannote[2170].end 14240.28659375
transcript.pyannote[2171].speaker SPEAKER_23
transcript.pyannote[2171].start 14244.37034375
transcript.pyannote[2171].end 14245.04534375
transcript.pyannote[2172].speaker SPEAKER_23
transcript.pyannote[2172].start 14245.56846875
transcript.pyannote[2172].end 14316.25784375
transcript.pyannote[2173].speaker SPEAKER_28
transcript.pyannote[2173].start 14248.52159375
transcript.pyannote[2173].end 14250.88409375
transcript.pyannote[2174].speaker SPEAKER_00
transcript.pyannote[2174].start 14286.33846875
transcript.pyannote[2174].end 14287.06409375
transcript.pyannote[2175].speaker SPEAKER_23
transcript.pyannote[2175].start 14316.67971875
transcript.pyannote[2175].end 14338.41471875
transcript.pyannote[2176].speaker SPEAKER_28
transcript.pyannote[2176].start 14338.41471875
transcript.pyannote[2176].end 14352.89346875
transcript.pyannote[2177].speaker SPEAKER_23
transcript.pyannote[2177].start 14352.89346875
transcript.pyannote[2177].end 14376.87284375
transcript.pyannote[2178].speaker SPEAKER_28
transcript.pyannote[2178].start 14352.99471875
transcript.pyannote[2178].end 14353.48409375
transcript.pyannote[2179].speaker SPEAKER_28
transcript.pyannote[2179].start 14378.49284375
transcript.pyannote[2179].end 14392.93784375
transcript.pyannote[2180].speaker SPEAKER_23
transcript.pyannote[2180].start 14381.05784375
transcript.pyannote[2180].end 14381.47971875
transcript.pyannote[2181].speaker SPEAKER_23
transcript.pyannote[2181].start 14382.05346875
transcript.pyannote[2181].end 14383.60596875
transcript.pyannote[2182].speaker SPEAKER_00
transcript.pyannote[2182].start 14386.59284375
transcript.pyannote[2182].end 14386.60971875
transcript.pyannote[2183].speaker SPEAKER_23
transcript.pyannote[2183].start 14386.60971875
transcript.pyannote[2183].end 14387.23409375
transcript.pyannote[2184].speaker SPEAKER_00
transcript.pyannote[2184].start 14387.52096875
transcript.pyannote[2184].end 14387.53784375
transcript.pyannote[2185].speaker SPEAKER_23
transcript.pyannote[2185].start 14387.53784375
transcript.pyannote[2185].end 14388.14534375
transcript.pyannote[2186].speaker SPEAKER_23
transcript.pyannote[2186].start 14391.57096875
transcript.pyannote[2186].end 14419.76909375
transcript.pyannote[2187].speaker SPEAKER_28
transcript.pyannote[2187].start 14421.23721875
transcript.pyannote[2187].end 14435.02409375
transcript.pyannote[2188].speaker SPEAKER_00
transcript.pyannote[2188].start 14428.03784375
transcript.pyannote[2188].end 14428.08846875
transcript.pyannote[2189].speaker SPEAKER_23
transcript.pyannote[2189].start 14428.08846875
transcript.pyannote[2189].end 14428.51034375
transcript.pyannote[2190].speaker SPEAKER_00
transcript.pyannote[2190].start 14428.51034375
transcript.pyannote[2190].end 14428.54409375
transcript.pyannote[2191].speaker SPEAKER_00
transcript.pyannote[2191].start 14430.80534375
transcript.pyannote[2191].end 14431.02471875
transcript.pyannote[2192].speaker SPEAKER_23
transcript.pyannote[2192].start 14431.02471875
transcript.pyannote[2192].end 14431.36221875
transcript.pyannote[2193].speaker SPEAKER_23
transcript.pyannote[2193].start 14435.02409375
transcript.pyannote[2193].end 14454.68346875
transcript.pyannote[2194].speaker SPEAKER_23
transcript.pyannote[2194].start 14455.08846875
transcript.pyannote[2194].end 14455.27409375
transcript.pyannote[2195].speaker SPEAKER_24
transcript.pyannote[2195].start 14455.27409375
transcript.pyannote[2195].end 14457.23159375
transcript.pyannote[2196].speaker SPEAKER_23
transcript.pyannote[2196].start 14456.55659375
transcript.pyannote[2196].end 14456.96159375
transcript.pyannote[2197].speaker SPEAKER_23
transcript.pyannote[2197].start 14457.43409375
transcript.pyannote[2197].end 14477.09346875
transcript.pyannote[2198].speaker SPEAKER_24
transcript.pyannote[2198].start 14477.41409375
transcript.pyannote[2198].end 14480.77221875
transcript.pyannote[2199].speaker SPEAKER_23
transcript.pyannote[2199].start 14479.99596875
transcript.pyannote[2199].end 14480.21534375
transcript.pyannote[2200].speaker SPEAKER_24
transcript.pyannote[2200].start 14481.32909375
transcript.pyannote[2200].end 14497.95096875
transcript.pyannote[2201].speaker SPEAKER_22
transcript.pyannote[2201].start 14488.92284375
transcript.pyannote[2201].end 14489.26034375
transcript.pyannote[2202].speaker SPEAKER_00
transcript.pyannote[2202].start 14489.26034375
transcript.pyannote[2202].end 14489.29409375
transcript.pyannote[2203].speaker SPEAKER_29
transcript.pyannote[2203].start 14494.35659375
transcript.pyannote[2203].end 14494.69409375
transcript.pyannote[2204].speaker SPEAKER_29
transcript.pyannote[2204].start 14497.29284375
transcript.pyannote[2204].end 14497.83284375
transcript.pyannote[2205].speaker SPEAKER_29
transcript.pyannote[2205].start 14497.95096875
transcript.pyannote[2205].end 14498.54159375
transcript.pyannote[2206].speaker SPEAKER_24
transcript.pyannote[2206].start 14498.74409375
transcript.pyannote[2206].end 14513.39159375
transcript.pyannote[2207].speaker SPEAKER_22
transcript.pyannote[2207].start 14506.55721875
transcript.pyannote[2207].end 14506.57409375
transcript.pyannote[2208].speaker SPEAKER_23
transcript.pyannote[2208].start 14506.57409375
transcript.pyannote[2208].end 14507.01284375
transcript.pyannote[2209].speaker SPEAKER_23
transcript.pyannote[2209].start 14511.26534375
transcript.pyannote[2209].end 14511.83909375
transcript.pyannote[2210].speaker SPEAKER_23
transcript.pyannote[2210].start 14513.44221875
transcript.pyannote[2210].end 14513.84721875
transcript.pyannote[2211].speaker SPEAKER_23
transcript.pyannote[2211].start 14514.23534375
transcript.pyannote[2211].end 14518.36971875
transcript.pyannote[2212].speaker SPEAKER_23
transcript.pyannote[2212].start 14518.57221875
transcript.pyannote[2212].end 14523.12846875
transcript.pyannote[2213].speaker SPEAKER_23
transcript.pyannote[2213].start 14523.33096875
transcript.pyannote[2213].end 14526.52034375
transcript.pyannote[2214].speaker SPEAKER_24
transcript.pyannote[2214].start 14525.52471875
transcript.pyannote[2214].end 14544.17159375
transcript.pyannote[2215].speaker SPEAKER_23
transcript.pyannote[2215].start 14530.40159375
transcript.pyannote[2215].end 14530.65471875
transcript.pyannote[2216].speaker SPEAKER_23
transcript.pyannote[2216].start 14533.70909375
transcript.pyannote[2216].end 14533.84409375
transcript.pyannote[2217].speaker SPEAKER_22
transcript.pyannote[2217].start 14533.84409375
transcript.pyannote[2217].end 14533.86096875
transcript.pyannote[2218].speaker SPEAKER_23
transcript.pyannote[2218].start 14542.88909375
transcript.pyannote[2218].end 14545.89284375
transcript.pyannote[2219].speaker SPEAKER_24
transcript.pyannote[2219].start 14545.15034375
transcript.pyannote[2219].end 14561.62034375
transcript.pyannote[2220].speaker SPEAKER_23
transcript.pyannote[2220].start 14545.99409375
transcript.pyannote[2220].end 14546.55096875
transcript.pyannote[2221].speaker SPEAKER_23
transcript.pyannote[2221].start 14556.27096875
transcript.pyannote[2221].end 14556.76034375
transcript.pyannote[2222].speaker SPEAKER_23
transcript.pyannote[2222].start 14558.19471875
transcript.pyannote[2222].end 14558.59971875
transcript.pyannote[2223].speaker SPEAKER_23
transcript.pyannote[2223].start 14561.16471875
transcript.pyannote[2223].end 14570.56409375
transcript.pyannote[2224].speaker SPEAKER_23
transcript.pyannote[2224].start 14571.03659375
transcript.pyannote[2224].end 14576.01471875
transcript.pyannote[2225].speaker SPEAKER_23
transcript.pyannote[2225].start 14576.43659375
transcript.pyannote[2225].end 14607.25034375
transcript.pyannote[2226].speaker SPEAKER_22
transcript.pyannote[2226].start 14581.48221875
transcript.pyannote[2226].end 14581.51596875
transcript.pyannote[2227].speaker SPEAKER_22
transcript.pyannote[2227].start 14588.09721875
transcript.pyannote[2227].end 14588.50221875
transcript.pyannote[2228].speaker SPEAKER_00
transcript.pyannote[2228].start 14588.50221875
transcript.pyannote[2228].end 14588.53596875
transcript.pyannote[2229].speaker SPEAKER_23
transcript.pyannote[2229].start 14607.80721875
transcript.pyannote[2229].end 14613.30846875
transcript.pyannote[2230].speaker SPEAKER_22
transcript.pyannote[2230].start 14612.93721875
transcript.pyannote[2230].end 14613.67971875
transcript.pyannote[2231].speaker SPEAKER_23
transcript.pyannote[2231].start 14613.56159375
transcript.pyannote[2231].end 14645.84346875
transcript.pyannote[2232].speaker SPEAKER_24
transcript.pyannote[2232].start 14622.15096875
transcript.pyannote[2232].end 14622.85971875
transcript.pyannote[2233].speaker SPEAKER_00
transcript.pyannote[2233].start 14622.85971875
transcript.pyannote[2233].end 14622.91034375
transcript.pyannote[2234].speaker SPEAKER_22
transcript.pyannote[2234].start 14632.17471875
transcript.pyannote[2234].end 14632.56284375
transcript.pyannote[2235].speaker SPEAKER_24
transcript.pyannote[2235].start 14641.35471875
transcript.pyannote[2235].end 14641.65846875
transcript.pyannote[2236].speaker SPEAKER_24
transcript.pyannote[2236].start 14645.18534375
transcript.pyannote[2236].end 14647.51409375
transcript.pyannote[2237].speaker SPEAKER_23
transcript.pyannote[2237].start 14646.83909375
transcript.pyannote[2237].end 14655.52971875
transcript.pyannote[2238].speaker SPEAKER_31
transcript.pyannote[2238].start 14654.24721875
transcript.pyannote[2238].end 14655.41159375
transcript.pyannote[2239].speaker SPEAKER_31
transcript.pyannote[2239].start 14656.37346875
transcript.pyannote[2239].end 14659.88346875
transcript.pyannote[2240].speaker SPEAKER_31
transcript.pyannote[2240].start 14659.95096875
transcript.pyannote[2240].end 14662.04346875
transcript.pyannote[2241].speaker SPEAKER_17
transcript.pyannote[2241].start 14670.48096875
transcript.pyannote[2241].end 14673.21471875
transcript.pyannote[2242].speaker SPEAKER_31
transcript.pyannote[2242].start 14673.94034375
transcript.pyannote[2242].end 14674.96971875
transcript.pyannote[2243].speaker SPEAKER_22
transcript.pyannote[2243].start 14679.74534375
transcript.pyannote[2243].end 14680.52159375
transcript.pyannote[2244].speaker SPEAKER_17
transcript.pyannote[2244].start 14680.90971875
transcript.pyannote[2244].end 14686.64721875
transcript.pyannote[2245].speaker SPEAKER_17
transcript.pyannote[2245].start 14686.95096875
transcript.pyannote[2245].end 14689.90409375
transcript.pyannote[2246].speaker SPEAKER_17
transcript.pyannote[2246].start 14690.25846875
transcript.pyannote[2246].end 14711.14971875
transcript.pyannote[2247].speaker SPEAKER_24
transcript.pyannote[2247].start 14711.57159375
transcript.pyannote[2247].end 14715.01409375
transcript.pyannote[2248].speaker SPEAKER_17
transcript.pyannote[2248].start 14715.23346875
transcript.pyannote[2248].end 14768.71034375
transcript.pyannote[2249].speaker SPEAKER_24
transcript.pyannote[2249].start 14769.95909375
transcript.pyannote[2249].end 14770.65096875
transcript.pyannote[2250].speaker SPEAKER_17
transcript.pyannote[2250].start 14770.65096875
transcript.pyannote[2250].end 14772.49034375
transcript.pyannote[2251].speaker SPEAKER_24
transcript.pyannote[2251].start 14772.03471875
transcript.pyannote[2251].end 14784.42096875
transcript.pyannote[2252].speaker SPEAKER_17
transcript.pyannote[2252].start 14784.42096875
transcript.pyannote[2252].end 14792.18346875
transcript.pyannote[2253].speaker SPEAKER_17
transcript.pyannote[2253].start 14792.30159375
transcript.pyannote[2253].end 14799.45659375
transcript.pyannote[2254].speaker SPEAKER_17
transcript.pyannote[2254].start 14800.36784375
transcript.pyannote[2254].end 14810.74596875
transcript.pyannote[2255].speaker SPEAKER_17
transcript.pyannote[2255].start 14810.91471875
transcript.pyannote[2255].end 14814.28971875
transcript.pyannote[2256].speaker SPEAKER_17
transcript.pyannote[2256].start 14814.52596875
transcript.pyannote[2256].end 14833.20659375
transcript.pyannote[2257].speaker SPEAKER_17
transcript.pyannote[2257].start 14833.89846875
transcript.pyannote[2257].end 14846.57159375
transcript.pyannote[2258].speaker SPEAKER_17
transcript.pyannote[2258].start 14846.99346875
transcript.pyannote[2258].end 14848.09034375
transcript.pyannote[2259].speaker SPEAKER_17
transcript.pyannote[2259].start 14849.32221875
transcript.pyannote[2259].end 14853.69284375
transcript.pyannote[2260].speaker SPEAKER_17
transcript.pyannote[2260].start 14854.26659375
transcript.pyannote[2260].end 14857.77659375
transcript.pyannote[2261].speaker SPEAKER_17
transcript.pyannote[2261].start 14858.35034375
transcript.pyannote[2261].end 14866.99034375
transcript.pyannote[2262].speaker SPEAKER_17
transcript.pyannote[2262].start 14867.96909375
transcript.pyannote[2262].end 14871.49596875
transcript.pyannote[2263].speaker SPEAKER_17
transcript.pyannote[2263].start 14871.63096875
transcript.pyannote[2263].end 14874.78659375
transcript.pyannote[2264].speaker SPEAKER_17
transcript.pyannote[2264].start 14875.66409375
transcript.pyannote[2264].end 14877.52034375
transcript.pyannote[2265].speaker SPEAKER_17
transcript.pyannote[2265].start 14878.02659375
transcript.pyannote[2265].end 14890.80096875
transcript.pyannote[2266].speaker SPEAKER_17
transcript.pyannote[2266].start 14892.16784375
transcript.pyannote[2266].end 14897.06159375
transcript.pyannote[2267].speaker SPEAKER_24
transcript.pyannote[2267].start 14898.59721875
transcript.pyannote[2267].end 14899.98096875
transcript.pyannote[2268].speaker SPEAKER_17
transcript.pyannote[2268].start 14900.13284375
transcript.pyannote[2268].end 14905.97159375
transcript.pyannote[2269].speaker SPEAKER_17
transcript.pyannote[2269].start 14906.96721875
transcript.pyannote[2269].end 14908.68846875
transcript.pyannote[2270].speaker SPEAKER_17
transcript.pyannote[2270].start 14909.68409375
transcript.pyannote[2270].end 14926.98096875
transcript.pyannote[2271].speaker SPEAKER_17
transcript.pyannote[2271].start 14927.62221875
transcript.pyannote[2271].end 14928.41534375
transcript.pyannote[2272].speaker SPEAKER_17
transcript.pyannote[2272].start 14928.65159375
transcript.pyannote[2272].end 14932.16159375
transcript.pyannote[2273].speaker SPEAKER_17
transcript.pyannote[2273].start 14932.65096875
transcript.pyannote[2273].end 14954.04846875
transcript.pyannote[2274].speaker SPEAKER_24
transcript.pyannote[2274].start 14955.38159375
transcript.pyannote[2274].end 14956.98471875
transcript.pyannote[2275].speaker SPEAKER_24
transcript.pyannote[2275].start 14957.40659375
transcript.pyannote[2275].end 14958.46971875
transcript.pyannote[2276].speaker SPEAKER_24
transcript.pyannote[2276].start 14958.75659375
transcript.pyannote[2276].end 14960.39346875
transcript.pyannote[2277].speaker SPEAKER_17
transcript.pyannote[2277].start 14960.39346875
transcript.pyannote[2277].end 14960.71409375
transcript.pyannote[2278].speaker SPEAKER_17
transcript.pyannote[2278].start 14961.42284375
transcript.pyannote[2278].end 14962.51971875
transcript.pyannote[2279].speaker SPEAKER_24
transcript.pyannote[2279].start 14963.00909375
transcript.pyannote[2279].end 14964.39284375
transcript.pyannote[2280].speaker SPEAKER_17
transcript.pyannote[2280].start 14964.40971875
transcript.pyannote[2280].end 14971.48034375
transcript.pyannote[2281].speaker SPEAKER_24
transcript.pyannote[2281].start 14973.35346875
transcript.pyannote[2281].end 14976.22221875
transcript.pyannote[2282].speaker SPEAKER_24
transcript.pyannote[2282].start 14976.66096875
transcript.pyannote[2282].end 14978.88846875
transcript.pyannote[2283].speaker SPEAKER_17
transcript.pyannote[2283].start 14978.28096875
transcript.pyannote[2283].end 14979.66471875
transcript.pyannote[2284].speaker SPEAKER_17
transcript.pyannote[2284].start 14980.18784375
transcript.pyannote[2284].end 15004.03221875
transcript.pyannote[2285].speaker SPEAKER_17
transcript.pyannote[2285].start 15005.02784375
transcript.pyannote[2285].end 15005.80409375
transcript.pyannote[2286].speaker SPEAKER_17
transcript.pyannote[2286].start 15007.77846875
transcript.pyannote[2286].end 15014.12346875
transcript.pyannote[2287].speaker SPEAKER_24
transcript.pyannote[2287].start 15008.03159375
transcript.pyannote[2287].end 15008.87534375
transcript.pyannote[2288].speaker SPEAKER_24
transcript.pyannote[2288].start 15015.62534375
transcript.pyannote[2288].end 15018.83159375
transcript.pyannote[2289].speaker SPEAKER_17
transcript.pyannote[2289].start 15018.96659375
transcript.pyannote[2289].end 15022.83096875
transcript.pyannote[2290].speaker SPEAKER_24
transcript.pyannote[2290].start 15019.08471875
transcript.pyannote[2290].end 15019.15221875
transcript.pyannote[2291].speaker SPEAKER_24
transcript.pyannote[2291].start 15019.23659375
transcript.pyannote[2291].end 15019.27034375
transcript.pyannote[2292].speaker SPEAKER_24
transcript.pyannote[2292].start 15022.37534375
transcript.pyannote[2292].end 15023.20221875
transcript.pyannote[2293].speaker SPEAKER_17
transcript.pyannote[2293].start 15023.55659375
transcript.pyannote[2293].end 15023.86034375
transcript.pyannote[2294].speaker SPEAKER_24
transcript.pyannote[2294].start 15023.86034375
transcript.pyannote[2294].end 15025.07534375
transcript.pyannote[2295].speaker SPEAKER_17
transcript.pyannote[2295].start 15025.12596875
transcript.pyannote[2295].end 15026.35784375
transcript.pyannote[2296].speaker SPEAKER_24
transcript.pyannote[2296].start 15026.35784375
transcript.pyannote[2296].end 15027.82596875
transcript.pyannote[2297].speaker SPEAKER_17
transcript.pyannote[2297].start 15027.85971875
transcript.pyannote[2297].end 15029.27721875
transcript.pyannote[2298].speaker SPEAKER_24
transcript.pyannote[2298].start 15029.34471875
transcript.pyannote[2298].end 15031.25159375
transcript.pyannote[2299].speaker SPEAKER_17
transcript.pyannote[2299].start 15031.25159375
transcript.pyannote[2299].end 15031.40346875
transcript.pyannote[2300].speaker SPEAKER_17
transcript.pyannote[2300].start 15031.45409375
transcript.pyannote[2300].end 15031.99409375
transcript.pyannote[2301].speaker SPEAKER_17
transcript.pyannote[2301].start 15032.34846875
transcript.pyannote[2301].end 15034.87971875
transcript.pyannote[2302].speaker SPEAKER_17
transcript.pyannote[2302].start 15035.08221875
transcript.pyannote[2302].end 15040.92096875
transcript.pyannote[2303].speaker SPEAKER_17
transcript.pyannote[2303].start 15042.15284375
transcript.pyannote[2303].end 15046.21971875
transcript.pyannote[2304].speaker SPEAKER_17
transcript.pyannote[2304].start 15047.38409375
transcript.pyannote[2304].end 15053.50971875
transcript.pyannote[2305].speaker SPEAKER_17
transcript.pyannote[2305].start 15054.64034375
transcript.pyannote[2305].end 15055.31534375
transcript.pyannote[2306].speaker SPEAKER_17
transcript.pyannote[2306].start 15056.44596875
transcript.pyannote[2306].end 15057.35721875
transcript.pyannote[2307].speaker SPEAKER_17
transcript.pyannote[2307].start 15058.04909375
transcript.pyannote[2307].end 15060.27659375
transcript.pyannote[2308].speaker SPEAKER_24
transcript.pyannote[2308].start 15062.25096875
transcript.pyannote[2308].end 15065.08596875
transcript.pyannote[2309].speaker SPEAKER_17
transcript.pyannote[2309].start 15064.69784375
transcript.pyannote[2309].end 15065.23784375
transcript.pyannote[2310].speaker SPEAKER_17
transcript.pyannote[2310].start 15065.74409375
transcript.pyannote[2310].end 15066.75659375
transcript.pyannote[2311].speaker SPEAKER_17
transcript.pyannote[2311].start 15067.44846875
transcript.pyannote[2311].end 15089.60534375
transcript.pyannote[2312].speaker SPEAKER_17
transcript.pyannote[2312].start 15089.92596875
transcript.pyannote[2312].end 15107.67846875
transcript.pyannote[2313].speaker SPEAKER_17
transcript.pyannote[2313].start 15109.29846875
transcript.pyannote[2313].end 15125.78534375
transcript.pyannote[2314].speaker SPEAKER_17
transcript.pyannote[2314].start 15126.49409375
transcript.pyannote[2314].end 15129.97034375
transcript.pyannote[2315].speaker SPEAKER_17
transcript.pyannote[2315].start 15131.05034375
transcript.pyannote[2315].end 15137.93534375
transcript.pyannote[2316].speaker SPEAKER_17
transcript.pyannote[2316].start 15139.16721875
transcript.pyannote[2316].end 15158.48909375
transcript.pyannote[2317].speaker SPEAKER_17
transcript.pyannote[2317].start 15158.79284375
transcript.pyannote[2317].end 15161.23971875
transcript.pyannote[2318].speaker SPEAKER_17
transcript.pyannote[2318].start 15161.39159375
transcript.pyannote[2318].end 15163.77096875
transcript.pyannote[2319].speaker SPEAKER_17
transcript.pyannote[2319].start 15164.26034375
transcript.pyannote[2319].end 15165.40784375
transcript.pyannote[2320].speaker SPEAKER_17
transcript.pyannote[2320].start 15166.26846875
transcript.pyannote[2320].end 15174.82409375
transcript.pyannote[2321].speaker SPEAKER_17
transcript.pyannote[2321].start 15175.34721875
transcript.pyannote[2321].end 15180.71346875
transcript.pyannote[2322].speaker SPEAKER_17
transcript.pyannote[2322].start 15181.06784375
transcript.pyannote[2322].end 15204.94596875
transcript.pyannote[2323].speaker SPEAKER_17
transcript.pyannote[2323].start 15205.90784375
transcript.pyannote[2323].end 15214.00784375
transcript.pyannote[2324].speaker SPEAKER_17
transcript.pyannote[2324].start 15214.58159375
transcript.pyannote[2324].end 15215.84721875
transcript.pyannote[2325].speaker SPEAKER_17
transcript.pyannote[2325].start 15216.75846875
transcript.pyannote[2325].end 15218.93534375
transcript.pyannote[2326].speaker SPEAKER_17
transcript.pyannote[2326].start 15221.60159375
transcript.pyannote[2326].end 15222.46221875
transcript.pyannote[2327].speaker SPEAKER_17
transcript.pyannote[2327].start 15224.31846875
transcript.pyannote[2327].end 15226.36034375
transcript.pyannote[2328].speaker SPEAKER_17
transcript.pyannote[2328].start 15226.91721875
transcript.pyannote[2328].end 15231.37221875
transcript.pyannote[2329].speaker SPEAKER_17
transcript.pyannote[2329].start 15231.82784375
transcript.pyannote[2329].end 15236.46846875
transcript.pyannote[2330].speaker SPEAKER_17
transcript.pyannote[2330].start 15237.07596875
transcript.pyannote[2330].end 15242.22284375
transcript.pyannote[2331].speaker SPEAKER_17
transcript.pyannote[2331].start 15242.81346875
transcript.pyannote[2331].end 15248.58471875
transcript.pyannote[2332].speaker SPEAKER_17
transcript.pyannote[2332].start 15249.31034375
transcript.pyannote[2332].end 15252.22971875
transcript.pyannote[2333].speaker SPEAKER_17
transcript.pyannote[2333].start 15253.05659375
transcript.pyannote[2333].end 15253.83284375
transcript.pyannote[2334].speaker SPEAKER_17
transcript.pyannote[2334].start 15254.38971875
transcript.pyannote[2334].end 15256.81971875
transcript.pyannote[2335].speaker SPEAKER_17
transcript.pyannote[2335].start 15258.60846875
transcript.pyannote[2335].end 15261.44346875
transcript.pyannote[2336].speaker SPEAKER_17
transcript.pyannote[2336].start 15261.81471875
transcript.pyannote[2336].end 15269.32409375
transcript.pyannote[2337].speaker SPEAKER_17
transcript.pyannote[2337].start 15269.71221875
transcript.pyannote[2337].end 15270.58971875
transcript.pyannote[2338].speaker SPEAKER_17
transcript.pyannote[2338].start 15271.90596875
transcript.pyannote[2338].end 15275.97284375
transcript.pyannote[2339].speaker SPEAKER_17
transcript.pyannote[2339].start 15277.01909375
transcript.pyannote[2339].end 15278.55471875
transcript.pyannote[2340].speaker SPEAKER_17
transcript.pyannote[2340].start 15281.91284375
transcript.pyannote[2340].end 15285.08534375
transcript.pyannote[2341].speaker SPEAKER_17
transcript.pyannote[2341].start 15285.65909375
transcript.pyannote[2341].end 15287.02596875
transcript.pyannote[2342].speaker SPEAKER_17
transcript.pyannote[2342].start 15287.26221875
transcript.pyannote[2342].end 15289.03409375
transcript.pyannote[2343].speaker SPEAKER_17
transcript.pyannote[2343].start 15289.40534375
transcript.pyannote[2343].end 15295.98659375
transcript.pyannote[2344].speaker SPEAKER_17
transcript.pyannote[2344].start 15298.29846875
transcript.pyannote[2344].end 15300.57659375
transcript.pyannote[2345].speaker SPEAKER_17
transcript.pyannote[2345].start 15300.86346875
transcript.pyannote[2345].end 15303.36096875
transcript.pyannote[2346].speaker SPEAKER_17
transcript.pyannote[2346].start 15305.01471875
transcript.pyannote[2346].end 15315.00471875
transcript.pyannote[2347].speaker SPEAKER_17
transcript.pyannote[2347].start 15315.49409375
transcript.pyannote[2347].end 15320.45534375
transcript.pyannote[2348].speaker SPEAKER_17
transcript.pyannote[2348].start 15320.86034375
transcript.pyannote[2348].end 15325.68659375
transcript.pyannote[2349].speaker SPEAKER_17
transcript.pyannote[2349].start 15327.67784375
transcript.pyannote[2349].end 15330.17534375
transcript.pyannote[2350].speaker SPEAKER_17
transcript.pyannote[2350].start 15330.81659375
transcript.pyannote[2350].end 15333.38159375
transcript.pyannote[2351].speaker SPEAKER_17
transcript.pyannote[2351].start 15335.45721875
transcript.pyannote[2351].end 15347.94471875
transcript.pyannote[2352].speaker SPEAKER_17
transcript.pyannote[2352].start 15348.48471875
transcript.pyannote[2352].end 15353.95221875
transcript.pyannote[2353].speaker SPEAKER_17
transcript.pyannote[2353].start 15354.17159375
transcript.pyannote[2353].end 15372.48096875
transcript.pyannote[2354].speaker SPEAKER_17
transcript.pyannote[2354].start 15373.00409375
transcript.pyannote[2354].end 15382.06596875
transcript.pyannote[2355].speaker SPEAKER_17
transcript.pyannote[2355].start 15382.53846875
transcript.pyannote[2355].end 15386.80784375
transcript.pyannote[2356].speaker SPEAKER_17
transcript.pyannote[2356].start 15387.29721875
transcript.pyannote[2356].end 15394.31721875
transcript.pyannote[2357].speaker SPEAKER_17
transcript.pyannote[2357].start 15394.90784375
transcript.pyannote[2357].end 15402.75471875
transcript.pyannote[2358].speaker SPEAKER_24
transcript.pyannote[2358].start 15404.76284375
transcript.pyannote[2358].end 15408.17159375
transcript.pyannote[2359].speaker SPEAKER_24
transcript.pyannote[2359].start 15408.81284375
transcript.pyannote[2359].end 15413.40284375
transcript.pyannote[2360].speaker SPEAKER_17
transcript.pyannote[2360].start 15412.81221875
transcript.pyannote[2360].end 15417.28409375
transcript.pyannote[2361].speaker SPEAKER_24
transcript.pyannote[2361].start 15416.38971875
transcript.pyannote[2361].end 15423.71346875
transcript.pyannote[2362].speaker SPEAKER_24
transcript.pyannote[2362].start 15423.83159375
transcript.pyannote[2362].end 15424.86096875
transcript.pyannote[2363].speaker SPEAKER_22
transcript.pyannote[2363].start 15424.03409375
transcript.pyannote[2363].end 15424.06784375
transcript.pyannote[2364].speaker SPEAKER_17
transcript.pyannote[2364].start 15424.06784375
transcript.pyannote[2364].end 15424.08471875
transcript.pyannote[2365].speaker SPEAKER_22
transcript.pyannote[2365].start 15424.08471875
transcript.pyannote[2365].end 15424.70909375
transcript.pyannote[2366].speaker SPEAKER_17
transcript.pyannote[2366].start 15424.70909375
transcript.pyannote[2366].end 15424.77659375
transcript.pyannote[2367].speaker SPEAKER_22
transcript.pyannote[2367].start 15424.86096875
transcript.pyannote[2367].end 15424.97909375
transcript.pyannote[2368].speaker SPEAKER_17
transcript.pyannote[2368].start 15424.97909375
transcript.pyannote[2368].end 15431.05409375
transcript.pyannote[2369].speaker SPEAKER_17
transcript.pyannote[2369].start 15431.84721875
transcript.pyannote[2369].end 15436.18409375
transcript.pyannote[2370].speaker SPEAKER_17
transcript.pyannote[2370].start 15436.38659375
transcript.pyannote[2370].end 15442.83284375
transcript.pyannote[2371].speaker SPEAKER_17
transcript.pyannote[2371].start 15443.69346875
transcript.pyannote[2371].end 15445.14471875
transcript.pyannote[2372].speaker SPEAKER_17
transcript.pyannote[2372].start 15445.73534375
transcript.pyannote[2372].end 15446.89971875
transcript.pyannote[2373].speaker SPEAKER_17
transcript.pyannote[2373].start 15448.68846875
transcript.pyannote[2373].end 15449.59971875
transcript.pyannote[2374].speaker SPEAKER_17
transcript.pyannote[2374].start 15451.57409375
transcript.pyannote[2374].end 15454.22346875
transcript.pyannote[2375].speaker SPEAKER_17
transcript.pyannote[2375].start 15455.10096875
transcript.pyannote[2375].end 15461.58096875
transcript.pyannote[2376].speaker SPEAKER_17
transcript.pyannote[2376].start 15462.01971875
transcript.pyannote[2376].end 15467.04846875
transcript.pyannote[2377].speaker SPEAKER_17
transcript.pyannote[2377].start 15467.68971875
transcript.pyannote[2377].end 15470.52471875
transcript.pyannote[2378].speaker SPEAKER_17
transcript.pyannote[2378].start 15470.57534375
transcript.pyannote[2378].end 15475.70534375
transcript.pyannote[2379].speaker SPEAKER_17
transcript.pyannote[2379].start 15476.07659375
transcript.pyannote[2379].end 15477.59534375
transcript.pyannote[2380].speaker SPEAKER_17
transcript.pyannote[2380].start 15479.58659375
transcript.pyannote[2380].end 15483.31596875
transcript.pyannote[2381].speaker SPEAKER_17
transcript.pyannote[2381].start 15484.64909375
transcript.pyannote[2381].end 15494.94284375
transcript.pyannote[2382].speaker SPEAKER_17
transcript.pyannote[2382].start 15498.04784375
transcript.pyannote[2382].end 15498.26721875
transcript.pyannote[2383].speaker SPEAKER_17
transcript.pyannote[2383].start 15499.34721875
transcript.pyannote[2383].end 15500.27534375
transcript.pyannote[2384].speaker SPEAKER_24
transcript.pyannote[2384].start 15500.37659375
transcript.pyannote[2384].end 15500.39346875
transcript.pyannote[2385].speaker SPEAKER_22
transcript.pyannote[2385].start 15500.39346875
transcript.pyannote[2385].end 15500.56221875
transcript.pyannote[2386].speaker SPEAKER_17
transcript.pyannote[2386].start 15500.56221875
transcript.pyannote[2386].end 15507.95346875
transcript.pyannote[2387].speaker SPEAKER_22
transcript.pyannote[2387].start 15500.59596875
transcript.pyannote[2387].end 15502.03034375
transcript.pyannote[2388].speaker SPEAKER_24
transcript.pyannote[2388].start 15502.03034375
transcript.pyannote[2388].end 15502.55346875
transcript.pyannote[2389].speaker SPEAKER_24
transcript.pyannote[2389].start 15509.05034375
transcript.pyannote[2389].end 15510.46784375
transcript.pyannote[2390].speaker SPEAKER_17
transcript.pyannote[2390].start 15510.31596875
transcript.pyannote[2390].end 15514.73721875
transcript.pyannote[2391].speaker SPEAKER_24
transcript.pyannote[2391].start 15515.90159375
transcript.pyannote[2391].end 15515.93534375
transcript.pyannote[2392].speaker SPEAKER_17
transcript.pyannote[2392].start 15515.93534375
transcript.pyannote[2392].end 15515.98596875
transcript.pyannote[2393].speaker SPEAKER_29
transcript.pyannote[2393].start 15515.98596875
transcript.pyannote[2393].end 15516.00284375
transcript.pyannote[2394].speaker SPEAKER_24
transcript.pyannote[2394].start 15516.00284375
transcript.pyannote[2394].end 15517.96034375
transcript.pyannote[2395].speaker SPEAKER_17
transcript.pyannote[2395].start 15517.69034375
transcript.pyannote[2395].end 15518.51721875
transcript.pyannote[2396].speaker SPEAKER_17
transcript.pyannote[2396].start 15518.71971875
transcript.pyannote[2396].end 15520.99784375
transcript.pyannote[2397].speaker SPEAKER_17
transcript.pyannote[2397].start 15521.67284375
transcript.pyannote[2397].end 15524.27159375
transcript.pyannote[2398].speaker SPEAKER_17
transcript.pyannote[2398].start 15525.85784375
transcript.pyannote[2398].end 15536.86034375
transcript.pyannote[2399].speaker SPEAKER_17
transcript.pyannote[2399].start 15537.58596875
transcript.pyannote[2399].end 15539.89784375
transcript.pyannote[2400].speaker SPEAKER_17
transcript.pyannote[2400].start 15540.69096875
transcript.pyannote[2400].end 15554.62971875
transcript.pyannote[2401].speaker SPEAKER_17
transcript.pyannote[2401].start 15554.91659375
transcript.pyannote[2401].end 15557.44784375
transcript.pyannote[2402].speaker SPEAKER_17
transcript.pyannote[2402].start 15558.34221875
transcript.pyannote[2402].end 15562.47659375
transcript.pyannote[2403].speaker SPEAKER_17
transcript.pyannote[2403].start 15566.93159375
transcript.pyannote[2403].end 15567.28596875
transcript.pyannote[2404].speaker SPEAKER_24
transcript.pyannote[2404].start 15568.92284375
transcript.pyannote[2404].end 15570.49221875
transcript.pyannote[2405].speaker SPEAKER_17
transcript.pyannote[2405].start 15571.45409375
transcript.pyannote[2405].end 15581.98409375
transcript.pyannote[2406].speaker SPEAKER_17
transcript.pyannote[2406].start 15584.04284375
transcript.pyannote[2406].end 15588.14346875
transcript.pyannote[2407].speaker SPEAKER_17
transcript.pyannote[2407].start 15589.30784375
transcript.pyannote[2407].end 15590.53971875
transcript.pyannote[2408].speaker SPEAKER_24
transcript.pyannote[2408].start 15591.28221875
transcript.pyannote[2408].end 15592.91909375
transcript.pyannote[2409].speaker SPEAKER_17
transcript.pyannote[2409].start 15593.27346875
transcript.pyannote[2409].end 15598.03221875
transcript.pyannote[2410].speaker SPEAKER_17
transcript.pyannote[2410].start 15598.60596875
transcript.pyannote[2410].end 15599.44971875
transcript.pyannote[2411].speaker SPEAKER_17
transcript.pyannote[2411].start 15599.63534375
transcript.pyannote[2411].end 15601.45784375
transcript.pyannote[2412].speaker SPEAKER_17
transcript.pyannote[2412].start 15603.87096875
transcript.pyannote[2412].end 15605.49096875
transcript.pyannote[2413].speaker SPEAKER_00
transcript.pyannote[2413].start 15603.95534375
transcript.pyannote[2413].end 15603.98909375
transcript.pyannote[2414].speaker SPEAKER_29
transcript.pyannote[2414].start 15603.98909375
transcript.pyannote[2414].end 15604.61346875
transcript.pyannote[2415].speaker SPEAKER_17
transcript.pyannote[2415].start 15606.21659375
transcript.pyannote[2415].end 15611.09346875
transcript.pyannote[2416].speaker SPEAKER_17
transcript.pyannote[2416].start 15611.26221875
transcript.pyannote[2416].end 15614.02971875
transcript.pyannote[2417].speaker SPEAKER_17
transcript.pyannote[2417].start 15614.53596875
transcript.pyannote[2417].end 15619.21034375
transcript.pyannote[2418].speaker SPEAKER_17
transcript.pyannote[2418].start 15619.49721875
transcript.pyannote[2418].end 15626.63534375
transcript.pyannote[2419].speaker SPEAKER_17
transcript.pyannote[2419].start 15626.75346875
transcript.pyannote[2419].end 15631.46159375
transcript.pyannote[2420].speaker SPEAKER_17
transcript.pyannote[2420].start 15631.88346875
transcript.pyannote[2420].end 15636.47346875
transcript.pyannote[2421].speaker SPEAKER_17
transcript.pyannote[2421].start 15637.09784375
transcript.pyannote[2421].end 15638.38034375
transcript.pyannote[2422].speaker SPEAKER_17
transcript.pyannote[2422].start 15639.34221875
transcript.pyannote[2422].end 15645.58596875
transcript.pyannote[2423].speaker SPEAKER_17
transcript.pyannote[2423].start 15645.92346875
transcript.pyannote[2423].end 15649.56846875
transcript.pyannote[2424].speaker SPEAKER_17
transcript.pyannote[2424].start 15649.80471875
transcript.pyannote[2424].end 15662.29221875
transcript.pyannote[2425].speaker SPEAKER_24
transcript.pyannote[2425].start 15662.91659375
transcript.pyannote[2425].end 15668.31659375
transcript.pyannote[2426].speaker SPEAKER_24
transcript.pyannote[2426].start 15668.75534375
transcript.pyannote[2426].end 15671.79284375
transcript.pyannote[2427].speaker SPEAKER_17
transcript.pyannote[2427].start 15670.35846875
transcript.pyannote[2427].end 15672.19784375
transcript.pyannote[2428].speaker SPEAKER_24
transcript.pyannote[2428].start 15671.99534375
transcript.pyannote[2428].end 15673.68284375
transcript.pyannote[2429].speaker SPEAKER_17
transcript.pyannote[2429].start 15673.17659375
transcript.pyannote[2429].end 15676.07909375
transcript.pyannote[2430].speaker SPEAKER_24
transcript.pyannote[2430].start 15676.63596875
transcript.pyannote[2430].end 15692.53221875
transcript.pyannote[2431].speaker SPEAKER_17
transcript.pyannote[2431].start 15677.15909375
transcript.pyannote[2431].end 15678.13784375
transcript.pyannote[2432].speaker SPEAKER_17
transcript.pyannote[2432].start 15690.77721875
transcript.pyannote[2432].end 15693.44346875
transcript.pyannote[2433].speaker SPEAKER_24
transcript.pyannote[2433].start 15693.27471875
transcript.pyannote[2433].end 15693.51096875
transcript.pyannote[2434].speaker SPEAKER_17
transcript.pyannote[2434].start 15693.51096875
transcript.pyannote[2434].end 15693.64596875
transcript.pyannote[2435].speaker SPEAKER_17
transcript.pyannote[2435].start 15693.83159375
transcript.pyannote[2435].end 15695.11409375
transcript.pyannote[2436].speaker SPEAKER_17
transcript.pyannote[2436].start 15695.23221875
transcript.pyannote[2436].end 15711.07784375
transcript.pyannote[2437].speaker SPEAKER_24
transcript.pyannote[2437].start 15711.93846875
transcript.pyannote[2437].end 15713.77784375
transcript.pyannote[2438].speaker SPEAKER_17
transcript.pyannote[2438].start 15713.10284375
transcript.pyannote[2438].end 15715.90409375
transcript.pyannote[2439].speaker SPEAKER_24
transcript.pyannote[2439].start 15715.53284375
transcript.pyannote[2439].end 15717.72659375
transcript.pyannote[2440].speaker SPEAKER_24
transcript.pyannote[2440].start 15718.38471875
transcript.pyannote[2440].end 15725.65784375
transcript.pyannote[2441].speaker SPEAKER_17
transcript.pyannote[2441].start 15726.70409375
transcript.pyannote[2441].end 15729.16784375
transcript.pyannote[2442].speaker SPEAKER_24
transcript.pyannote[2442].start 15728.99909375
transcript.pyannote[2442].end 15735.17534375
transcript.pyannote[2443].speaker SPEAKER_24
transcript.pyannote[2443].start 15735.52971875
transcript.pyannote[2443].end 15738.90471875
transcript.pyannote[2444].speaker SPEAKER_17
transcript.pyannote[2444].start 15735.56346875
transcript.pyannote[2444].end 15749.58659375
transcript.pyannote[2445].speaker SPEAKER_17
transcript.pyannote[2445].start 15750.81846875
transcript.pyannote[2445].end 15751.35846875
transcript.pyannote[2446].speaker SPEAKER_22
transcript.pyannote[2446].start 15751.30784375
transcript.pyannote[2446].end 15752.25284375
transcript.pyannote[2447].speaker SPEAKER_17
transcript.pyannote[2447].start 15752.10096875
transcript.pyannote[2447].end 15759.89721875
transcript.pyannote[2448].speaker SPEAKER_22
transcript.pyannote[2448].start 15757.36596875
transcript.pyannote[2448].end 15757.97346875
transcript.pyannote[2449].speaker SPEAKER_24
transcript.pyannote[2449].start 15757.97346875
transcript.pyannote[2449].end 15758.19284375
transcript.pyannote[2450].speaker SPEAKER_17
transcript.pyannote[2450].start 15760.09971875
transcript.pyannote[2450].end 15761.48346875
transcript.pyannote[2451].speaker SPEAKER_24
transcript.pyannote[2451].start 15761.56784375
transcript.pyannote[2451].end 15763.66034375
transcript.pyannote[2452].speaker SPEAKER_24
transcript.pyannote[2452].start 15763.89659375
transcript.pyannote[2452].end 15773.54909375
transcript.pyannote[2453].speaker SPEAKER_17
transcript.pyannote[2453].start 15772.58721875
transcript.pyannote[2453].end 15776.16471875
transcript.pyannote[2454].speaker SPEAKER_17
transcript.pyannote[2454].start 15776.92409375
transcript.pyannote[2454].end 15780.40034375
transcript.pyannote[2455].speaker SPEAKER_17
transcript.pyannote[2455].start 15782.13846875
transcript.pyannote[2455].end 15788.36534375
transcript.pyannote[2456].speaker SPEAKER_11
transcript.pyannote[2456].start 15783.20159375
transcript.pyannote[2456].end 15783.21846875
transcript.pyannote[2457].speaker SPEAKER_24
transcript.pyannote[2457].start 15783.21846875
transcript.pyannote[2457].end 15790.28909375
transcript.pyannote[2458].speaker SPEAKER_17
transcript.pyannote[2458].start 15790.32284375
transcript.pyannote[2458].end 15796.88721875
transcript.pyannote[2459].speaker SPEAKER_17
transcript.pyannote[2459].start 15798.45659375
transcript.pyannote[2459].end 15799.58721875
transcript.pyannote[2460].speaker SPEAKER_24
transcript.pyannote[2460].start 15802.05096875
transcript.pyannote[2460].end 15803.78909375
transcript.pyannote[2461].speaker SPEAKER_24
transcript.pyannote[2461].start 15803.97471875
transcript.pyannote[2461].end 15807.13034375
transcript.pyannote[2462].speaker SPEAKER_24
transcript.pyannote[2462].start 15807.82221875
transcript.pyannote[2462].end 15809.30721875
transcript.pyannote[2463].speaker SPEAKER_17
transcript.pyannote[2463].start 15808.53096875
transcript.pyannote[2463].end 15814.03221875
transcript.pyannote[2464].speaker SPEAKER_24
transcript.pyannote[2464].start 15809.35784375
transcript.pyannote[2464].end 15809.49284375
transcript.pyannote[2465].speaker SPEAKER_17
transcript.pyannote[2465].start 15815.23034375
transcript.pyannote[2465].end 15836.57721875
transcript.pyannote[2466].speaker SPEAKER_17
transcript.pyannote[2466].start 15836.93159375
transcript.pyannote[2466].end 15842.12909375
transcript.pyannote[2467].speaker SPEAKER_17
transcript.pyannote[2467].start 15842.50034375
transcript.pyannote[2467].end 15853.26659375
transcript.pyannote[2468].speaker SPEAKER_17
transcript.pyannote[2468].start 15853.53659375
transcript.pyannote[2468].end 15856.69221875
transcript.pyannote[2469].speaker SPEAKER_17
transcript.pyannote[2469].start 15856.87784375
transcript.pyannote[2469].end 15858.36284375
transcript.pyannote[2470].speaker SPEAKER_17
transcript.pyannote[2470].start 15858.59909375
transcript.pyannote[2470].end 15861.38346875
transcript.pyannote[2471].speaker SPEAKER_17
transcript.pyannote[2471].start 15862.42971875
transcript.pyannote[2471].end 15865.09596875
transcript.pyannote[2472].speaker SPEAKER_17
transcript.pyannote[2472].start 15865.46721875
transcript.pyannote[2472].end 15867.18846875
transcript.pyannote[2473].speaker SPEAKER_24
transcript.pyannote[2473].start 15865.48409375
transcript.pyannote[2473].end 15865.80471875
transcript.pyannote[2474].speaker SPEAKER_17
transcript.pyannote[2474].start 15868.28534375
transcript.pyannote[2474].end 15872.23409375
transcript.pyannote[2475].speaker SPEAKER_24
transcript.pyannote[2475].start 15872.60534375
transcript.pyannote[2475].end 15875.45721875
transcript.pyannote[2476].speaker SPEAKER_17
transcript.pyannote[2476].start 15875.67659375
transcript.pyannote[2476].end 15877.98846875
transcript.pyannote[2477].speaker SPEAKER_17
transcript.pyannote[2477].start 15878.25846875
transcript.pyannote[2477].end 15881.56596875
transcript.pyannote[2478].speaker SPEAKER_17
transcript.pyannote[2478].start 15881.59971875
transcript.pyannote[2478].end 15881.65034375
transcript.pyannote[2479].speaker SPEAKER_17
transcript.pyannote[2479].start 15882.51096875
transcript.pyannote[2479].end 15885.49784375
transcript.pyannote[2480].speaker SPEAKER_17
transcript.pyannote[2480].start 15885.98721875
transcript.pyannote[2480].end 15887.16846875
transcript.pyannote[2481].speaker SPEAKER_17
transcript.pyannote[2481].start 15888.07971875
transcript.pyannote[2481].end 15895.97721875
transcript.pyannote[2482].speaker SPEAKER_29
transcript.pyannote[2482].start 15888.11346875
transcript.pyannote[2482].end 15889.24409375
transcript.pyannote[2483].speaker SPEAKER_03
transcript.pyannote[2483].start 15889.24409375
transcript.pyannote[2483].end 15889.69971875
transcript.pyannote[2484].speaker SPEAKER_03
transcript.pyannote[2484].start 15896.04471875
transcript.pyannote[2484].end 15896.36534375
transcript.pyannote[2485].speaker SPEAKER_03
transcript.pyannote[2485].start 15896.71971875
transcript.pyannote[2485].end 15900.29721875
transcript.pyannote[2486].speaker SPEAKER_12
transcript.pyannote[2486].start 15909.81471875
transcript.pyannote[2486].end 15910.89471875
transcript.pyannote[2487].speaker SPEAKER_03
transcript.pyannote[2487].start 15910.96221875
transcript.pyannote[2487].end 15911.92409375
transcript.pyannote[2488].speaker SPEAKER_12
transcript.pyannote[2488].start 15919.93971875
transcript.pyannote[2488].end 15931.09409375
transcript.pyannote[2489].speaker SPEAKER_12
transcript.pyannote[2489].start 15931.49909375
transcript.pyannote[2489].end 15939.09284375
transcript.pyannote[2490].speaker SPEAKER_12
transcript.pyannote[2490].start 15939.19409375
transcript.pyannote[2490].end 15943.31159375
transcript.pyannote[2491].speaker SPEAKER_12
transcript.pyannote[2491].start 15943.54784375
transcript.pyannote[2491].end 15958.66784375
transcript.pyannote[2492].speaker SPEAKER_24
transcript.pyannote[2492].start 15960.70971875
transcript.pyannote[2492].end 15961.14846875
transcript.pyannote[2493].speaker SPEAKER_24
transcript.pyannote[2493].start 15961.68846875
transcript.pyannote[2493].end 15962.02596875
transcript.pyannote[2494].speaker SPEAKER_12
transcript.pyannote[2494].start 15962.02596875
transcript.pyannote[2494].end 15962.36346875
transcript.pyannote[2495].speaker SPEAKER_24
transcript.pyannote[2495].start 15962.36346875
transcript.pyannote[2495].end 15962.38034375
transcript.pyannote[2496].speaker SPEAKER_12
transcript.pyannote[2496].start 15962.38034375
transcript.pyannote[2496].end 15962.41409375
transcript.pyannote[2497].speaker SPEAKER_24
transcript.pyannote[2497].start 15962.41409375
transcript.pyannote[2497].end 15962.92034375
transcript.pyannote[2498].speaker SPEAKER_12
transcript.pyannote[2498].start 15962.92034375
transcript.pyannote[2498].end 15963.17346875
transcript.pyannote[2499].speaker SPEAKER_12
transcript.pyannote[2499].start 15963.27471875
transcript.pyannote[2499].end 15966.37971875
transcript.pyannote[2500].speaker SPEAKER_12
transcript.pyannote[2500].start 15966.80159375
transcript.pyannote[2500].end 15974.85096875
transcript.pyannote[2501].speaker SPEAKER_12
transcript.pyannote[2501].start 15975.15471875
transcript.pyannote[2501].end 15979.69409375
transcript.pyannote[2502].speaker SPEAKER_24
transcript.pyannote[2502].start 15981.41534375
transcript.pyannote[2502].end 15983.84534375
transcript.pyannote[2503].speaker SPEAKER_24
transcript.pyannote[2503].start 15984.18284375
transcript.pyannote[2503].end 15985.53284375
transcript.pyannote[2504].speaker SPEAKER_12
transcript.pyannote[2504].start 15985.19534375
transcript.pyannote[2504].end 15985.93784375
transcript.pyannote[2505].speaker SPEAKER_12
transcript.pyannote[2505].start 15986.46096875
transcript.pyannote[2505].end 15987.13596875
transcript.pyannote[2506].speaker SPEAKER_12
transcript.pyannote[2506].start 15987.74346875
transcript.pyannote[2506].end 15991.91159375
transcript.pyannote[2507].speaker SPEAKER_12
transcript.pyannote[2507].start 15992.56971875
transcript.pyannote[2507].end 15994.34159375
transcript.pyannote[2508].speaker SPEAKER_12
transcript.pyannote[2508].start 15994.49346875
transcript.pyannote[2508].end 16011.31784375
transcript.pyannote[2509].speaker SPEAKER_12
transcript.pyannote[2509].start 16012.09409375
transcript.pyannote[2509].end 16015.94159375
transcript.pyannote[2510].speaker SPEAKER_12
transcript.pyannote[2510].start 16016.21159375
transcript.pyannote[2510].end 16017.35909375
transcript.pyannote[2511].speaker SPEAKER_24
transcript.pyannote[2511].start 16017.89909375
transcript.pyannote[2511].end 16018.21971875
transcript.pyannote[2512].speaker SPEAKER_24
transcript.pyannote[2512].start 16019.60346875
transcript.pyannote[2512].end 16021.20659375
transcript.pyannote[2513].speaker SPEAKER_12
transcript.pyannote[2513].start 16021.49346875
transcript.pyannote[2513].end 16021.71284375
transcript.pyannote[2514].speaker SPEAKER_12
transcript.pyannote[2514].start 16022.08409375
transcript.pyannote[2514].end 16030.33596875
transcript.pyannote[2515].speaker SPEAKER_12
transcript.pyannote[2515].start 16030.53846875
transcript.pyannote[2515].end 16030.89284375
transcript.pyannote[2516].speaker SPEAKER_12
transcript.pyannote[2516].start 16031.07846875
transcript.pyannote[2516].end 16031.63534375
transcript.pyannote[2517].speaker SPEAKER_22
transcript.pyannote[2517].start 16031.82096875
transcript.pyannote[2517].end 16031.97284375
transcript.pyannote[2518].speaker SPEAKER_12
transcript.pyannote[2518].start 16031.97284375
transcript.pyannote[2518].end 16034.58846875
transcript.pyannote[2519].speaker SPEAKER_22
transcript.pyannote[2519].start 16032.00659375
transcript.pyannote[2519].end 16032.25971875
transcript.pyannote[2520].speaker SPEAKER_22
transcript.pyannote[2520].start 16034.55471875
transcript.pyannote[2520].end 16034.94284375
transcript.pyannote[2521].speaker SPEAKER_12
transcript.pyannote[2521].start 16035.14534375
transcript.pyannote[2521].end 16041.15284375
transcript.pyannote[2522].speaker SPEAKER_12
transcript.pyannote[2522].start 16041.42284375
transcript.pyannote[2522].end 16060.69409375
transcript.pyannote[2523].speaker SPEAKER_12
transcript.pyannote[2523].start 16061.74034375
transcript.pyannote[2523].end 16062.58409375
transcript.pyannote[2524].speaker SPEAKER_24
transcript.pyannote[2524].start 16063.24221875
transcript.pyannote[2524].end 16083.99846875
transcript.pyannote[2525].speaker SPEAKER_12
transcript.pyannote[2525].start 16084.26846875
transcript.pyannote[2525].end 16101.98721875
transcript.pyannote[2526].speaker SPEAKER_12
transcript.pyannote[2526].start 16102.03784375
transcript.pyannote[2526].end 16102.05471875
transcript.pyannote[2527].speaker SPEAKER_12
transcript.pyannote[2527].start 16102.10534375
transcript.pyannote[2527].end 16108.31534375
transcript.pyannote[2528].speaker SPEAKER_12
transcript.pyannote[2528].start 16108.73721875
transcript.pyannote[2528].end 16111.75784375
transcript.pyannote[2529].speaker SPEAKER_12
transcript.pyannote[2529].start 16112.04471875
transcript.pyannote[2529].end 16115.08221875
transcript.pyannote[2530].speaker SPEAKER_24
transcript.pyannote[2530].start 16115.08221875
transcript.pyannote[2530].end 16134.45471875
transcript.pyannote[2531].speaker SPEAKER_12
transcript.pyannote[2531].start 16133.83034375
transcript.pyannote[2531].end 16153.55721875
transcript.pyannote[2532].speaker SPEAKER_12
transcript.pyannote[2532].start 16153.97909375
transcript.pyannote[2532].end 16154.70471875
transcript.pyannote[2533].speaker SPEAKER_24
transcript.pyannote[2533].start 16154.70471875
transcript.pyannote[2533].end 16154.78909375
transcript.pyannote[2534].speaker SPEAKER_12
transcript.pyannote[2534].start 16154.78909375
transcript.pyannote[2534].end 16154.92409375
transcript.pyannote[2535].speaker SPEAKER_24
transcript.pyannote[2535].start 16154.92409375
transcript.pyannote[2535].end 16167.22596875
transcript.pyannote[2536].speaker SPEAKER_12
transcript.pyannote[2536].start 16155.56534375
transcript.pyannote[2536].end 16155.90284375
transcript.pyannote[2537].speaker SPEAKER_12
transcript.pyannote[2537].start 16166.34846875
transcript.pyannote[2537].end 16205.12721875
transcript.pyannote[2538].speaker SPEAKER_24
transcript.pyannote[2538].start 16206.10596875
transcript.pyannote[2538].end 16214.15534375
transcript.pyannote[2539].speaker SPEAKER_12
transcript.pyannote[2539].start 16210.15596875
transcript.pyannote[2539].end 16210.45971875
transcript.pyannote[2540].speaker SPEAKER_12
transcript.pyannote[2540].start 16214.50971875
transcript.pyannote[2540].end 16224.85409375
transcript.pyannote[2541].speaker SPEAKER_12
transcript.pyannote[2541].start 16226.57534375
transcript.pyannote[2541].end 16229.46096875
transcript.pyannote[2542].speaker SPEAKER_15
transcript.pyannote[2542].start 16229.84909375
transcript.pyannote[2542].end 16234.08471875
transcript.pyannote[2543].speaker SPEAKER_15
transcript.pyannote[2543].start 16234.33784375
transcript.pyannote[2543].end 16240.88534375
transcript.pyannote[2544].speaker SPEAKER_12
transcript.pyannote[2544].start 16236.53159375
transcript.pyannote[2544].end 16236.88596875
transcript.pyannote[2545].speaker SPEAKER_00
transcript.pyannote[2545].start 16236.88596875
transcript.pyannote[2545].end 16236.90284375
transcript.pyannote[2546].speaker SPEAKER_00
transcript.pyannote[2546].start 16238.06721875
transcript.pyannote[2546].end 16238.08409375
transcript.pyannote[2547].speaker SPEAKER_12
transcript.pyannote[2547].start 16238.08409375
transcript.pyannote[2547].end 16238.43846875
transcript.pyannote[2548].speaker SPEAKER_00
transcript.pyannote[2548].start 16238.43846875
transcript.pyannote[2548].end 16238.45534375
transcript.pyannote[2549].speaker SPEAKER_00
transcript.pyannote[2549].start 16239.06284375
transcript.pyannote[2549].end 16239.51846875
transcript.pyannote[2550].speaker SPEAKER_00
transcript.pyannote[2550].start 16239.94034375
transcript.pyannote[2550].end 16240.39596875
transcript.pyannote[2551].speaker SPEAKER_15
transcript.pyannote[2551].start 16241.07096875
transcript.pyannote[2551].end 16250.68971875
transcript.pyannote[2552].speaker SPEAKER_00
transcript.pyannote[2552].start 16242.96096875
transcript.pyannote[2552].end 16243.31534375
transcript.pyannote[2553].speaker SPEAKER_15
transcript.pyannote[2553].start 16250.74034375
transcript.pyannote[2553].end 16250.75721875
transcript.pyannote[2554].speaker SPEAKER_15
transcript.pyannote[2554].start 16250.84159375
transcript.pyannote[2554].end 16256.46096875
transcript.pyannote[2555].speaker SPEAKER_15
transcript.pyannote[2555].start 16256.59596875
transcript.pyannote[2555].end 16257.96284375
transcript.pyannote[2556].speaker SPEAKER_15
transcript.pyannote[2556].start 16258.08096875
transcript.pyannote[2556].end 16261.69221875
transcript.pyannote[2557].speaker SPEAKER_15
transcript.pyannote[2557].start 16261.77659375
transcript.pyannote[2557].end 16266.55221875
transcript.pyannote[2558].speaker SPEAKER_12
transcript.pyannote[2558].start 16266.43409375
transcript.pyannote[2558].end 16266.50159375
transcript.pyannote[2559].speaker SPEAKER_12
transcript.pyannote[2559].start 16266.55221875
transcript.pyannote[2559].end 16266.63659375
transcript.pyannote[2560].speaker SPEAKER_15
transcript.pyannote[2560].start 16266.63659375
transcript.pyannote[2560].end 16269.40409375
transcript.pyannote[2561].speaker SPEAKER_12
transcript.pyannote[2561].start 16269.40409375
transcript.pyannote[2561].end 16269.47159375
transcript.pyannote[2562].speaker SPEAKER_12
transcript.pyannote[2562].start 16269.72471875
transcript.pyannote[2562].end 16305.06096875
transcript.pyannote[2563].speaker SPEAKER_24
transcript.pyannote[2563].start 16306.61346875
transcript.pyannote[2563].end 16320.02909375
transcript.pyannote[2564].speaker SPEAKER_24
transcript.pyannote[2564].start 16320.31596875
transcript.pyannote[2564].end 16320.34971875
transcript.pyannote[2565].speaker SPEAKER_12
transcript.pyannote[2565].start 16320.34971875
transcript.pyannote[2565].end 16337.41034375
transcript.pyannote[2566].speaker SPEAKER_24
transcript.pyannote[2566].start 16320.43409375
transcript.pyannote[2566].end 16320.94034375
transcript.pyannote[2567].speaker SPEAKER_24
transcript.pyannote[2567].start 16336.87034375
transcript.pyannote[2567].end 16348.73346875
transcript.pyannote[2568].speaker SPEAKER_12
transcript.pyannote[2568].start 16345.62846875
transcript.pyannote[2568].end 16345.96596875
transcript.pyannote[2569].speaker SPEAKER_12
transcript.pyannote[2569].start 16348.26096875
transcript.pyannote[2569].end 16385.36909375
transcript.pyannote[2570].speaker SPEAKER_24
transcript.pyannote[2570].start 16386.71909375
transcript.pyannote[2570].end 16391.73096875
transcript.pyannote[2571].speaker SPEAKER_12
transcript.pyannote[2571].start 16387.46159375
transcript.pyannote[2571].end 16387.47846875
transcript.pyannote[2572].speaker SPEAKER_12
transcript.pyannote[2572].start 16391.34284375
transcript.pyannote[2572].end 16394.43096875
transcript.pyannote[2573].speaker SPEAKER_24
transcript.pyannote[2573].start 16392.77721875
transcript.pyannote[2573].end 16404.57284375
transcript.pyannote[2574].speaker SPEAKER_12
transcript.pyannote[2574].start 16398.97034375
transcript.pyannote[2574].end 16399.45971875
transcript.pyannote[2575].speaker SPEAKER_12
transcript.pyannote[2575].start 16404.69096875
transcript.pyannote[2575].end 16418.39346875
transcript.pyannote[2576].speaker SPEAKER_24
transcript.pyannote[2576].start 16409.98971875
transcript.pyannote[2576].end 16410.04034375
transcript.pyannote[2577].speaker SPEAKER_03
transcript.pyannote[2577].start 16418.39346875
transcript.pyannote[2577].end 16418.71409375
transcript.pyannote[2578].speaker SPEAKER_03
transcript.pyannote[2578].start 16422.49409375
transcript.pyannote[2578].end 16423.55721875
transcript.pyannote[2579].speaker SPEAKER_03
transcript.pyannote[2579].start 16425.64971875
transcript.pyannote[2579].end 16428.07971875
transcript.pyannote[2580].speaker SPEAKER_34
transcript.pyannote[2580].start 16434.22221875
transcript.pyannote[2580].end 16436.98971875
transcript.pyannote[2581].speaker SPEAKER_34
transcript.pyannote[2581].start 16438.87971875
transcript.pyannote[2581].end 16439.63909375
transcript.pyannote[2582].speaker SPEAKER_34
transcript.pyannote[2582].start 16440.68534375
transcript.pyannote[2582].end 16441.09034375
transcript.pyannote[2583].speaker SPEAKER_03
transcript.pyannote[2583].start 16443.23346875
transcript.pyannote[2583].end 16445.27534375
transcript.pyannote[2584].speaker SPEAKER_34
transcript.pyannote[2584].start 16445.39346875
transcript.pyannote[2584].end 16454.32034375
transcript.pyannote[2585].speaker SPEAKER_24
transcript.pyannote[2585].start 16455.01221875
transcript.pyannote[2585].end 16466.03159375
transcript.pyannote[2586].speaker SPEAKER_34
transcript.pyannote[2586].start 16466.03159375
transcript.pyannote[2586].end 16466.21721875
transcript.pyannote[2587].speaker SPEAKER_34
transcript.pyannote[2587].start 16466.41971875
transcript.pyannote[2587].end 16482.02909375
transcript.pyannote[2588].speaker SPEAKER_24
transcript.pyannote[2588].start 16482.06284375
transcript.pyannote[2588].end 16486.80471875
transcript.pyannote[2589].speaker SPEAKER_34
transcript.pyannote[2589].start 16482.55221875
transcript.pyannote[2589].end 16482.68721875
transcript.pyannote[2590].speaker SPEAKER_34
transcript.pyannote[2590].start 16486.07909375
transcript.pyannote[2590].end 16486.95659375
transcript.pyannote[2591].speaker SPEAKER_24
transcript.pyannote[2591].start 16486.95659375
transcript.pyannote[2591].end 16489.47096875
transcript.pyannote[2592].speaker SPEAKER_34
transcript.pyannote[2592].start 16487.32784375
transcript.pyannote[2592].end 16504.10159375
transcript.pyannote[2593].speaker SPEAKER_34
transcript.pyannote[2593].start 16504.70909375
transcript.pyannote[2593].end 16522.74846875
transcript.pyannote[2594].speaker SPEAKER_24
transcript.pyannote[2594].start 16524.33471875
transcript.pyannote[2594].end 16534.27409375
transcript.pyannote[2595].speaker SPEAKER_29
transcript.pyannote[2595].start 16534.49346875
transcript.pyannote[2595].end 16534.81409375
transcript.pyannote[2596].speaker SPEAKER_24
transcript.pyannote[2596].start 16535.26971875
transcript.pyannote[2596].end 16558.59096875
transcript.pyannote[2597].speaker SPEAKER_00
transcript.pyannote[2597].start 16548.06096875
transcript.pyannote[2597].end 16548.22971875
transcript.pyannote[2598].speaker SPEAKER_34
transcript.pyannote[2598].start 16548.22971875
transcript.pyannote[2598].end 16548.44909375
transcript.pyannote[2599].speaker SPEAKER_34
transcript.pyannote[2599].start 16548.87096875
transcript.pyannote[2599].end 16549.17471875
transcript.pyannote[2600].speaker SPEAKER_00
transcript.pyannote[2600].start 16549.17471875
transcript.pyannote[2600].end 16549.20846875
transcript.pyannote[2601].speaker SPEAKER_34
transcript.pyannote[2601].start 16550.15346875
transcript.pyannote[2601].end 16550.40659375
transcript.pyannote[2602].speaker SPEAKER_00
transcript.pyannote[2602].start 16550.40659375
transcript.pyannote[2602].end 16550.45721875
transcript.pyannote[2603].speaker SPEAKER_34
transcript.pyannote[2603].start 16555.82346875
transcript.pyannote[2603].end 16587.48096875
transcript.pyannote[2604].speaker SPEAKER_34
transcript.pyannote[2604].start 16588.18971875
transcript.pyannote[2604].end 16589.72534375
transcript.pyannote[2605].speaker SPEAKER_34
transcript.pyannote[2605].start 16590.56909375
transcript.pyannote[2605].end 16603.61346875
transcript.pyannote[2606].speaker SPEAKER_34
transcript.pyannote[2606].start 16604.35596875
transcript.pyannote[2606].end 16608.89534375
transcript.pyannote[2607].speaker SPEAKER_34
transcript.pyannote[2607].start 16609.48596875
transcript.pyannote[2607].end 16611.34221875
transcript.pyannote[2608].speaker SPEAKER_34
transcript.pyannote[2608].start 16612.35471875
transcript.pyannote[2608].end 16615.30784375
transcript.pyannote[2609].speaker SPEAKER_34
transcript.pyannote[2609].start 16615.79721875
transcript.pyannote[2609].end 16619.34096875
transcript.pyannote[2610].speaker SPEAKER_34
transcript.pyannote[2610].start 16619.84721875
transcript.pyannote[2610].end 16633.85346875
transcript.pyannote[2611].speaker SPEAKER_34
transcript.pyannote[2611].start 16634.41034375
transcript.pyannote[2611].end 16635.45659375
transcript.pyannote[2612].speaker SPEAKER_34
transcript.pyannote[2612].start 16636.72221875
transcript.pyannote[2612].end 16647.11721875
transcript.pyannote[2613].speaker SPEAKER_34
transcript.pyannote[2613].start 16647.96096875
transcript.pyannote[2613].end 16659.55409375
transcript.pyannote[2614].speaker SPEAKER_24
transcript.pyannote[2614].start 16660.24596875
transcript.pyannote[2614].end 16662.03471875
transcript.pyannote[2615].speaker SPEAKER_34
transcript.pyannote[2615].start 16662.03471875
transcript.pyannote[2615].end 16662.49034375
transcript.pyannote[2616].speaker SPEAKER_24
transcript.pyannote[2616].start 16662.49034375
transcript.pyannote[2616].end 16662.59159375
transcript.pyannote[2617].speaker SPEAKER_34
transcript.pyannote[2617].start 16662.59159375
transcript.pyannote[2617].end 16666.35471875
transcript.pyannote[2618].speaker SPEAKER_24
transcript.pyannote[2618].start 16662.60846875
transcript.pyannote[2618].end 16662.72659375
transcript.pyannote[2619].speaker SPEAKER_24
transcript.pyannote[2619].start 16666.54034375
transcript.pyannote[2619].end 16680.81659375
transcript.pyannote[2620].speaker SPEAKER_34
transcript.pyannote[2620].start 16678.45409375
transcript.pyannote[2620].end 16679.61846875
transcript.pyannote[2621].speaker SPEAKER_34
transcript.pyannote[2621].start 16680.44534375
transcript.pyannote[2621].end 16709.41971875
transcript.pyannote[2622].speaker SPEAKER_34
transcript.pyannote[2622].start 16709.75721875
transcript.pyannote[2622].end 16711.64721875
transcript.pyannote[2623].speaker SPEAKER_24
transcript.pyannote[2623].start 16711.81596875
transcript.pyannote[2623].end 16712.67659375
transcript.pyannote[2624].speaker SPEAKER_34
transcript.pyannote[2624].start 16712.67659375
transcript.pyannote[2624].end 16712.96346875
transcript.pyannote[2625].speaker SPEAKER_24
transcript.pyannote[2625].start 16712.96346875
transcript.pyannote[2625].end 16713.03096875
transcript.pyannote[2626].speaker SPEAKER_34
transcript.pyannote[2626].start 16713.03096875
transcript.pyannote[2626].end 16713.89159375
transcript.pyannote[2627].speaker SPEAKER_24
transcript.pyannote[2627].start 16713.89159375
transcript.pyannote[2627].end 16715.03909375
transcript.pyannote[2628].speaker SPEAKER_34
transcript.pyannote[2628].start 16715.03909375
transcript.pyannote[2628].end 16734.15846875
transcript.pyannote[2629].speaker SPEAKER_34
transcript.pyannote[2629].start 16734.46221875
transcript.pyannote[2629].end 16743.99659375
transcript.pyannote[2630].speaker SPEAKER_34
transcript.pyannote[2630].start 16744.38471875
transcript.pyannote[2630].end 16746.32534375
transcript.pyannote[2631].speaker SPEAKER_24
transcript.pyannote[2631].start 16746.69659375
transcript.pyannote[2631].end 16765.88346875
transcript.pyannote[2632].speaker SPEAKER_34
transcript.pyannote[2632].start 16755.50534375
transcript.pyannote[2632].end 16755.97784375
transcript.pyannote[2633].speaker SPEAKER_00
transcript.pyannote[2633].start 16755.97784375
transcript.pyannote[2633].end 16756.02846875
transcript.pyannote[2634].speaker SPEAKER_22
transcript.pyannote[2634].start 16756.02846875
transcript.pyannote[2634].end 16757.02409375
transcript.pyannote[2635].speaker SPEAKER_34
transcript.pyannote[2635].start 16757.02409375
transcript.pyannote[2635].end 16757.59784375
transcript.pyannote[2636].speaker SPEAKER_22
transcript.pyannote[2636].start 16757.59784375
transcript.pyannote[2636].end 16757.61471875
transcript.pyannote[2637].speaker SPEAKER_34
transcript.pyannote[2637].start 16757.61471875
transcript.pyannote[2637].end 16757.68221875
transcript.pyannote[2638].speaker SPEAKER_22
transcript.pyannote[2638].start 16757.68221875
transcript.pyannote[2638].end 16757.76659375
transcript.pyannote[2639].speaker SPEAKER_34
transcript.pyannote[2639].start 16757.76659375
transcript.pyannote[2639].end 16757.90159375
transcript.pyannote[2640].speaker SPEAKER_24
transcript.pyannote[2640].start 16766.03534375
transcript.pyannote[2640].end 16774.59096875
transcript.pyannote[2641].speaker SPEAKER_34
transcript.pyannote[2641].start 16774.32096875
transcript.pyannote[2641].end 16774.52346875
transcript.pyannote[2642].speaker SPEAKER_34
transcript.pyannote[2642].start 16774.59096875
transcript.pyannote[2642].end 16774.96221875
transcript.pyannote[2643].speaker SPEAKER_24
transcript.pyannote[2643].start 16774.96221875
transcript.pyannote[2643].end 16775.04659375
transcript.pyannote[2644].speaker SPEAKER_34
transcript.pyannote[2644].start 16775.04659375
transcript.pyannote[2644].end 16775.06346875
transcript.pyannote[2645].speaker SPEAKER_24
transcript.pyannote[2645].start 16775.06346875
transcript.pyannote[2645].end 16775.85659375
transcript.pyannote[2646].speaker SPEAKER_34
transcript.pyannote[2646].start 16775.85659375
transcript.pyannote[2646].end 16776.97034375
transcript.pyannote[2647].speaker SPEAKER_24
transcript.pyannote[2647].start 16776.97034375
transcript.pyannote[2647].end 16783.33221875
transcript.pyannote[2648].speaker SPEAKER_34
transcript.pyannote[2648].start 16777.03784375
transcript.pyannote[2648].end 16778.37096875
transcript.pyannote[2649].speaker SPEAKER_24
transcript.pyannote[2649].start 16783.92284375
transcript.pyannote[2649].end 16788.52971875
transcript.pyannote[2650].speaker SPEAKER_24
transcript.pyannote[2650].start 16788.98534375
transcript.pyannote[2650].end 16794.03096875
transcript.pyannote[2651].speaker SPEAKER_34
transcript.pyannote[2651].start 16794.03096875
transcript.pyannote[2651].end 16820.87909375
transcript.pyannote[2652].speaker SPEAKER_00
transcript.pyannote[2652].start 16806.07971875
transcript.pyannote[2652].end 16806.19784375
transcript.pyannote[2653].speaker SPEAKER_35
transcript.pyannote[2653].start 16806.19784375
transcript.pyannote[2653].end 16806.33284375
transcript.pyannote[2654].speaker SPEAKER_00
transcript.pyannote[2654].start 16806.33284375
transcript.pyannote[2654].end 16806.48471875
transcript.pyannote[2655].speaker SPEAKER_24
transcript.pyannote[2655].start 16821.23346875
transcript.pyannote[2655].end 16847.03534375
transcript.pyannote[2656].speaker SPEAKER_34
transcript.pyannote[2656].start 16847.03534375
transcript.pyannote[2656].end 16847.35596875
transcript.pyannote[2657].speaker SPEAKER_24
transcript.pyannote[2657].start 16847.35596875
transcript.pyannote[2657].end 16847.60909375
transcript.pyannote[2658].speaker SPEAKER_34
transcript.pyannote[2658].start 16847.60909375
transcript.pyannote[2658].end 16855.65846875
transcript.pyannote[2659].speaker SPEAKER_24
transcript.pyannote[2659].start 16856.83971875
transcript.pyannote[2659].end 16860.94034375
transcript.pyannote[2660].speaker SPEAKER_24
transcript.pyannote[2660].start 16861.56471875
transcript.pyannote[2660].end 16865.26034375
transcript.pyannote[2661].speaker SPEAKER_34
transcript.pyannote[2661].start 16865.26034375
transcript.pyannote[2661].end 16865.80034375
transcript.pyannote[2662].speaker SPEAKER_24
transcript.pyannote[2662].start 16865.86784375
transcript.pyannote[2662].end 16875.97596875
transcript.pyannote[2663].speaker SPEAKER_34
transcript.pyannote[2663].start 16867.03221875
transcript.pyannote[2663].end 16868.31471875
transcript.pyannote[2664].speaker SPEAKER_34
transcript.pyannote[2664].start 16875.97596875
transcript.pyannote[2664].end 16876.63409375
transcript.pyannote[2665].speaker SPEAKER_24
transcript.pyannote[2665].start 16875.99284375
transcript.pyannote[2665].end 16876.56659375
transcript.pyannote[2666].speaker SPEAKER_24
transcript.pyannote[2666].start 16876.63409375
transcript.pyannote[2666].end 16876.95471875
transcript.pyannote[2667].speaker SPEAKER_34
transcript.pyannote[2667].start 16876.66784375
transcript.pyannote[2667].end 16876.92096875
transcript.pyannote[2668].speaker SPEAKER_34
transcript.pyannote[2668].start 16876.95471875
transcript.pyannote[2668].end 16882.25346875
transcript.pyannote[2669].speaker SPEAKER_24
transcript.pyannote[2669].start 16878.28784375
transcript.pyannote[2669].end 16878.64221875
transcript.pyannote[2670].speaker SPEAKER_24
transcript.pyannote[2670].start 16881.96659375
transcript.pyannote[2670].end 16882.32096875
transcript.pyannote[2671].speaker SPEAKER_34
transcript.pyannote[2671].start 16882.32096875
transcript.pyannote[2671].end 16882.35471875
transcript.pyannote[2672].speaker SPEAKER_24
transcript.pyannote[2672].start 16882.35471875
transcript.pyannote[2672].end 16883.67096875
transcript.pyannote[2673].speaker SPEAKER_34
transcript.pyannote[2673].start 16883.67096875
transcript.pyannote[2673].end 16890.42096875
transcript.pyannote[2674].speaker SPEAKER_24
transcript.pyannote[2674].start 16884.44721875
transcript.pyannote[2674].end 16884.76784375
transcript.pyannote[2675].speaker SPEAKER_34
transcript.pyannote[2675].start 16890.64034375
transcript.pyannote[2675].end 16899.93846875
transcript.pyannote[2676].speaker SPEAKER_34
transcript.pyannote[2676].start 16900.17471875
transcript.pyannote[2676].end 16905.50721875
transcript.pyannote[2677].speaker SPEAKER_24
transcript.pyannote[2677].start 16907.32971875
transcript.pyannote[2677].end 16909.37159375
transcript.pyannote[2678].speaker SPEAKER_24
transcript.pyannote[2678].start 16909.69221875
transcript.pyannote[2678].end 16923.02346875
transcript.pyannote[2679].speaker SPEAKER_34
transcript.pyannote[2679].start 16918.66971875
transcript.pyannote[2679].end 16919.83409375
transcript.pyannote[2680].speaker SPEAKER_34
transcript.pyannote[2680].start 16923.02346875
transcript.pyannote[2680].end 16935.15659375
transcript.pyannote[2681].speaker SPEAKER_34
transcript.pyannote[2681].start 16935.29159375
transcript.pyannote[2681].end 16949.24721875
transcript.pyannote[2682].speaker SPEAKER_24
transcript.pyannote[2682].start 16949.34846875
transcript.pyannote[2682].end 16955.27159375
transcript.pyannote[2683].speaker SPEAKER_34
transcript.pyannote[2683].start 16952.94284375
transcript.pyannote[2683].end 16954.14096875
transcript.pyannote[2684].speaker SPEAKER_24
transcript.pyannote[2684].start 16955.60909375
transcript.pyannote[2684].end 16968.14721875
transcript.pyannote[2685].speaker SPEAKER_34
transcript.pyannote[2685].start 16955.89596875
transcript.pyannote[2685].end 16956.57096875
transcript.pyannote[2686].speaker SPEAKER_34
transcript.pyannote[2686].start 16967.96159375
transcript.pyannote[2686].end 17021.96159375
transcript.pyannote[2687].speaker SPEAKER_24
transcript.pyannote[2687].start 17021.57346875
transcript.pyannote[2687].end 17030.38221875
transcript.pyannote[2688].speaker SPEAKER_24
transcript.pyannote[2688].start 17030.63534375
transcript.pyannote[2688].end 17034.02721875
transcript.pyannote[2689].speaker SPEAKER_34
transcript.pyannote[2689].start 17034.02721875
transcript.pyannote[2689].end 17055.13784375
transcript.pyannote[2690].speaker SPEAKER_03
transcript.pyannote[2690].start 17058.68159375
transcript.pyannote[2690].end 17059.45784375
transcript.pyannote[2691].speaker SPEAKER_03
transcript.pyannote[2691].start 17059.89659375
transcript.pyannote[2691].end 17060.95971875
transcript.pyannote[2692].speaker SPEAKER_03
transcript.pyannote[2692].start 17061.24659375
transcript.pyannote[2692].end 17065.39784375
transcript.pyannote[2693].speaker SPEAKER_35
transcript.pyannote[2693].start 17076.63659375
transcript.pyannote[2693].end 17081.00721875
transcript.pyannote[2694].speaker SPEAKER_35
transcript.pyannote[2694].start 17085.85034375
transcript.pyannote[2694].end 17092.09409375
transcript.pyannote[2695].speaker SPEAKER_00
transcript.pyannote[2695].start 17086.06971875
transcript.pyannote[2695].end 17086.52534375
transcript.pyannote[2696].speaker SPEAKER_35
transcript.pyannote[2696].start 17092.60034375
transcript.pyannote[2696].end 17093.71409375
transcript.pyannote[2697].speaker SPEAKER_35
transcript.pyannote[2697].start 17094.55784375
transcript.pyannote[2697].end 17097.15659375
transcript.pyannote[2698].speaker SPEAKER_35
transcript.pyannote[2698].start 17097.46034375
transcript.pyannote[2698].end 17100.49784375
transcript.pyannote[2699].speaker SPEAKER_35
transcript.pyannote[2699].start 17101.44284375
transcript.pyannote[2699].end 17102.87721875
transcript.pyannote[2700].speaker SPEAKER_35
transcript.pyannote[2700].start 17103.60284375
transcript.pyannote[2700].end 17108.46284375
transcript.pyannote[2701].speaker SPEAKER_35
transcript.pyannote[2701].start 17109.10409375
transcript.pyannote[2701].end 17113.17096875
transcript.pyannote[2702].speaker SPEAKER_35
transcript.pyannote[2702].start 17113.69409375
transcript.pyannote[2702].end 17115.01034375
transcript.pyannote[2703].speaker SPEAKER_35
transcript.pyannote[2703].start 17115.71909375
transcript.pyannote[2703].end 17116.64721875
transcript.pyannote[2704].speaker SPEAKER_35
transcript.pyannote[2704].start 17117.35596875
transcript.pyannote[2704].end 17118.21659375
transcript.pyannote[2705].speaker SPEAKER_35
transcript.pyannote[2705].start 17118.73971875
transcript.pyannote[2705].end 17121.10221875
transcript.pyannote[2706].speaker SPEAKER_35
transcript.pyannote[2706].start 17121.76034375
transcript.pyannote[2706].end 17122.04721875
transcript.pyannote[2707].speaker SPEAKER_35
transcript.pyannote[2707].start 17122.90784375
transcript.pyannote[2707].end 17124.94971875
transcript.pyannote[2708].speaker SPEAKER_35
transcript.pyannote[2708].start 17125.25346875
transcript.pyannote[2708].end 17128.81409375
transcript.pyannote[2709].speaker SPEAKER_35
transcript.pyannote[2709].start 17129.32034375
transcript.pyannote[2709].end 17133.87659375
transcript.pyannote[2710].speaker SPEAKER_35
transcript.pyannote[2710].start 17134.41659375
transcript.pyannote[2710].end 17138.33159375
transcript.pyannote[2711].speaker SPEAKER_35
transcript.pyannote[2711].start 17139.22596875
transcript.pyannote[2711].end 17142.73596875
transcript.pyannote[2712].speaker SPEAKER_35
transcript.pyannote[2712].start 17143.14096875
transcript.pyannote[2712].end 17144.10284375
transcript.pyannote[2713].speaker SPEAKER_35
transcript.pyannote[2713].start 17144.71034375
transcript.pyannote[2713].end 17145.68909375
transcript.pyannote[2714].speaker SPEAKER_35
transcript.pyannote[2714].start 17146.11096875
transcript.pyannote[2714].end 17147.91659375
transcript.pyannote[2715].speaker SPEAKER_35
transcript.pyannote[2715].start 17148.64221875
transcript.pyannote[2715].end 17151.35909375
transcript.pyannote[2716].speaker SPEAKER_35
transcript.pyannote[2716].start 17151.61221875
transcript.pyannote[2716].end 17152.23659375
transcript.pyannote[2717].speaker SPEAKER_35
transcript.pyannote[2717].start 17153.11409375
transcript.pyannote[2717].end 17154.48096875
transcript.pyannote[2718].speaker SPEAKER_35
transcript.pyannote[2718].start 17155.69596875
transcript.pyannote[2718].end 17157.45096875
transcript.pyannote[2719].speaker SPEAKER_35
transcript.pyannote[2719].start 17159.39159375
transcript.pyannote[2719].end 17160.38721875
transcript.pyannote[2720].speaker SPEAKER_35
transcript.pyannote[2720].start 17160.99471875
transcript.pyannote[2720].end 17164.92659375
transcript.pyannote[2721].speaker SPEAKER_35
transcript.pyannote[2721].start 17165.55096875
transcript.pyannote[2721].end 17168.11596875
transcript.pyannote[2722].speaker SPEAKER_35
transcript.pyannote[2722].start 17168.80784375
transcript.pyannote[2722].end 17171.77784375
transcript.pyannote[2723].speaker SPEAKER_35
transcript.pyannote[2723].start 17172.48659375
transcript.pyannote[2723].end 17173.63409375
transcript.pyannote[2724].speaker SPEAKER_35
transcript.pyannote[2724].start 17174.20784375
transcript.pyannote[2724].end 17176.48596875
transcript.pyannote[2725].speaker SPEAKER_35
transcript.pyannote[2725].start 17177.14409375
transcript.pyannote[2725].end 17178.73034375
transcript.pyannote[2726].speaker SPEAKER_35
transcript.pyannote[2726].start 17178.81471875
transcript.pyannote[2726].end 17180.56971875
transcript.pyannote[2727].speaker SPEAKER_35
transcript.pyannote[2727].start 17181.09284375
transcript.pyannote[2727].end 17182.00409375
transcript.pyannote[2728].speaker SPEAKER_35
transcript.pyannote[2728].start 17182.86471875
transcript.pyannote[2728].end 17184.28221875
transcript.pyannote[2729].speaker SPEAKER_35
transcript.pyannote[2729].start 17185.19346875
transcript.pyannote[2729].end 17186.40846875
transcript.pyannote[2730].speaker SPEAKER_35
transcript.pyannote[2730].start 17187.16784375
transcript.pyannote[2730].end 17188.99034375
transcript.pyannote[2731].speaker SPEAKER_35
transcript.pyannote[2731].start 17190.01971875
transcript.pyannote[2731].end 17193.96846875
transcript.pyannote[2732].speaker SPEAKER_35
transcript.pyannote[2732].start 17195.33534375
transcript.pyannote[2732].end 17196.95534375
transcript.pyannote[2733].speaker SPEAKER_35
transcript.pyannote[2733].start 17197.52909375
transcript.pyannote[2733].end 17201.52846875
transcript.pyannote[2734].speaker SPEAKER_35
transcript.pyannote[2734].start 17203.09784375
transcript.pyannote[2734].end 17203.33409375
transcript.pyannote[2735].speaker SPEAKER_35
transcript.pyannote[2735].start 17204.11034375
transcript.pyannote[2735].end 17205.10596875
transcript.pyannote[2736].speaker SPEAKER_35
transcript.pyannote[2736].start 17205.76409375
transcript.pyannote[2736].end 17210.62409375
transcript.pyannote[2737].speaker SPEAKER_35
transcript.pyannote[2737].start 17211.13034375
transcript.pyannote[2737].end 17213.52659375
transcript.pyannote[2738].speaker SPEAKER_35
transcript.pyannote[2738].start 17214.33659375
transcript.pyannote[2738].end 17214.58971875
transcript.pyannote[2739].speaker SPEAKER_35
transcript.pyannote[2739].start 17218.04909375
transcript.pyannote[2739].end 17220.05721875
transcript.pyannote[2740].speaker SPEAKER_35
transcript.pyannote[2740].start 17220.73221875
transcript.pyannote[2740].end 17221.94721875
transcript.pyannote[2741].speaker SPEAKER_35
transcript.pyannote[2741].start 17222.35221875
transcript.pyannote[2741].end 17223.21284375
transcript.pyannote[2742].speaker SPEAKER_35
transcript.pyannote[2742].start 17223.34784375
transcript.pyannote[2742].end 17226.38534375
transcript.pyannote[2743].speaker SPEAKER_35
transcript.pyannote[2743].start 17227.11096875
transcript.pyannote[2743].end 17228.54534375
transcript.pyannote[2744].speaker SPEAKER_35
transcript.pyannote[2744].start 17228.76471875
transcript.pyannote[2744].end 17230.70534375
transcript.pyannote[2745].speaker SPEAKER_35
transcript.pyannote[2745].start 17231.78534375
transcript.pyannote[2745].end 17233.57409375
transcript.pyannote[2746].speaker SPEAKER_35
transcript.pyannote[2746].start 17234.35034375
transcript.pyannote[2746].end 17236.94909375
transcript.pyannote[2747].speaker SPEAKER_35
transcript.pyannote[2747].start 17238.01221875
transcript.pyannote[2747].end 17240.02034375
transcript.pyannote[2748].speaker SPEAKER_35
transcript.pyannote[2748].start 17240.62784375
transcript.pyannote[2748].end 17241.77534375
transcript.pyannote[2749].speaker SPEAKER_35
transcript.pyannote[2749].start 17242.36596875
transcript.pyannote[2749].end 17244.18846875
transcript.pyannote[2750].speaker SPEAKER_35
transcript.pyannote[2750].start 17245.06596875
transcript.pyannote[2750].end 17245.70721875
transcript.pyannote[2751].speaker SPEAKER_35
transcript.pyannote[2751].start 17246.33159375
transcript.pyannote[2751].end 17246.60159375
transcript.pyannote[2752].speaker SPEAKER_35
transcript.pyannote[2752].start 17247.02346875
transcript.pyannote[2752].end 17247.83346875
transcript.pyannote[2753].speaker SPEAKER_35
transcript.pyannote[2753].start 17248.82909375
transcript.pyannote[2753].end 17250.31409375
transcript.pyannote[2754].speaker SPEAKER_35
transcript.pyannote[2754].start 17250.71909375
transcript.pyannote[2754].end 17252.82846875
transcript.pyannote[2755].speaker SPEAKER_35
transcript.pyannote[2755].start 17253.48659375
transcript.pyannote[2755].end 17255.54534375
transcript.pyannote[2756].speaker SPEAKER_35
transcript.pyannote[2756].start 17255.96721875
transcript.pyannote[2756].end 17256.91221875
transcript.pyannote[2757].speaker SPEAKER_35
transcript.pyannote[2757].start 17258.16096875
transcript.pyannote[2757].end 17259.61221875
transcript.pyannote[2758].speaker SPEAKER_35
transcript.pyannote[2758].start 17260.01721875
transcript.pyannote[2758].end 17261.26596875
transcript.pyannote[2759].speaker SPEAKER_35
transcript.pyannote[2759].start 17261.92409375
transcript.pyannote[2759].end 17263.62846875
transcript.pyannote[2760].speaker SPEAKER_35
transcript.pyannote[2760].start 17265.34971875
transcript.pyannote[2760].end 17267.57721875
transcript.pyannote[2761].speaker SPEAKER_35
transcript.pyannote[2761].start 17268.03284375
transcript.pyannote[2761].end 17269.12971875
transcript.pyannote[2762].speaker SPEAKER_35
transcript.pyannote[2762].start 17269.60221875
transcript.pyannote[2762].end 17271.13784375
transcript.pyannote[2763].speaker SPEAKER_35
transcript.pyannote[2763].start 17271.39096875
transcript.pyannote[2763].end 17272.67346875
transcript.pyannote[2764].speaker SPEAKER_35
transcript.pyannote[2764].start 17272.89284375
transcript.pyannote[2764].end 17274.39471875
transcript.pyannote[2765].speaker SPEAKER_35
transcript.pyannote[2765].start 17275.49159375
transcript.pyannote[2765].end 17277.17909375
transcript.pyannote[2766].speaker SPEAKER_35
transcript.pyannote[2766].start 17277.76971875
transcript.pyannote[2766].end 17278.51221875
transcript.pyannote[2767].speaker SPEAKER_35
transcript.pyannote[2767].start 17278.90034375
transcript.pyannote[2767].end 17280.33471875
transcript.pyannote[2768].speaker SPEAKER_35
transcript.pyannote[2768].start 17280.94221875
transcript.pyannote[2768].end 17284.45221875
transcript.pyannote[2769].speaker SPEAKER_35
transcript.pyannote[2769].start 17285.36346875
transcript.pyannote[2769].end 17287.13534375
transcript.pyannote[2770].speaker SPEAKER_35
transcript.pyannote[2770].start 17287.97909375
transcript.pyannote[2770].end 17289.36284375
transcript.pyannote[2771].speaker SPEAKER_35
transcript.pyannote[2771].start 17290.18971875
transcript.pyannote[2771].end 17292.90659375
transcript.pyannote[2772].speaker SPEAKER_35
transcript.pyannote[2772].start 17293.51409375
transcript.pyannote[2772].end 17293.90221875
transcript.pyannote[2773].speaker SPEAKER_35
transcript.pyannote[2773].start 17295.82596875
transcript.pyannote[2773].end 17296.38284375
transcript.pyannote[2774].speaker SPEAKER_35
transcript.pyannote[2774].start 17296.97346875
transcript.pyannote[2774].end 17298.18846875
transcript.pyannote[2775].speaker SPEAKER_35
transcript.pyannote[2775].start 17298.27284375
transcript.pyannote[2775].end 17302.67721875
transcript.pyannote[2776].speaker SPEAKER_35
transcript.pyannote[2776].start 17302.93034375
transcript.pyannote[2776].end 17304.11159375
transcript.pyannote[2777].speaker SPEAKER_35
transcript.pyannote[2777].start 17305.07346875
transcript.pyannote[2777].end 17306.11971875
transcript.pyannote[2778].speaker SPEAKER_35
transcript.pyannote[2778].start 17306.42346875
transcript.pyannote[2778].end 17307.62159375
transcript.pyannote[2779].speaker SPEAKER_35
transcript.pyannote[2779].start 17307.77346875
transcript.pyannote[2779].end 17308.93784375
transcript.pyannote[2780].speaker SPEAKER_35
transcript.pyannote[2780].start 17309.32596875
transcript.pyannote[2780].end 17310.03471875
transcript.pyannote[2781].speaker SPEAKER_35
transcript.pyannote[2781].start 17310.57471875
transcript.pyannote[2781].end 17311.18221875
transcript.pyannote[2782].speaker SPEAKER_35
transcript.pyannote[2782].start 17311.85721875
transcript.pyannote[2782].end 17313.57846875
transcript.pyannote[2783].speaker SPEAKER_24
transcript.pyannote[2783].start 17314.52346875
transcript.pyannote[2783].end 17314.54034375
transcript.pyannote[2784].speaker SPEAKER_35
transcript.pyannote[2784].start 17314.54034375
transcript.pyannote[2784].end 17315.58659375
transcript.pyannote[2785].speaker SPEAKER_24
transcript.pyannote[2785].start 17315.58659375
transcript.pyannote[2785].end 17315.70471875
transcript.pyannote[2786].speaker SPEAKER_24
transcript.pyannote[2786].start 17316.41346875
transcript.pyannote[2786].end 17326.09971875
transcript.pyannote[2787].speaker SPEAKER_35
transcript.pyannote[2787].start 17326.09971875
transcript.pyannote[2787].end 17326.53846875
transcript.pyannote[2788].speaker SPEAKER_24
transcript.pyannote[2788].start 17326.53846875
transcript.pyannote[2788].end 17326.60596875
transcript.pyannote[2789].speaker SPEAKER_24
transcript.pyannote[2789].start 17327.48346875
transcript.pyannote[2789].end 17327.50034375
transcript.pyannote[2790].speaker SPEAKER_35
transcript.pyannote[2790].start 17327.50034375
transcript.pyannote[2790].end 17333.30534375
transcript.pyannote[2791].speaker SPEAKER_35
transcript.pyannote[2791].start 17333.89596875
transcript.pyannote[2791].end 17335.85346875
transcript.pyannote[2792].speaker SPEAKER_35
transcript.pyannote[2792].start 17336.51159375
transcript.pyannote[2792].end 17343.00846875
transcript.pyannote[2793].speaker SPEAKER_35
transcript.pyannote[2793].start 17344.07159375
transcript.pyannote[2793].end 17344.81409375
transcript.pyannote[2794].speaker SPEAKER_35
transcript.pyannote[2794].start 17345.79284375
transcript.pyannote[2794].end 17347.05846875
transcript.pyannote[2795].speaker SPEAKER_35
transcript.pyannote[2795].start 17347.27784375
transcript.pyannote[2795].end 17347.71659375
transcript.pyannote[2796].speaker SPEAKER_35
transcript.pyannote[2796].start 17348.32409375
transcript.pyannote[2796].end 17350.02846875
transcript.pyannote[2797].speaker SPEAKER_35
transcript.pyannote[2797].start 17350.70346875
transcript.pyannote[2797].end 17351.64846875
transcript.pyannote[2798].speaker SPEAKER_35
transcript.pyannote[2798].start 17352.59346875
transcript.pyannote[2798].end 17356.27221875
transcript.pyannote[2799].speaker SPEAKER_35
transcript.pyannote[2799].start 17356.62659375
transcript.pyannote[2799].end 17358.33096875
transcript.pyannote[2800].speaker SPEAKER_35
transcript.pyannote[2800].start 17358.71909375
transcript.pyannote[2800].end 17360.60909375
transcript.pyannote[2801].speaker SPEAKER_35
transcript.pyannote[2801].start 17361.31784375
transcript.pyannote[2801].end 17362.38096875
transcript.pyannote[2802].speaker SPEAKER_35
transcript.pyannote[2802].start 17363.73096875
transcript.pyannote[2802].end 17368.91159375
transcript.pyannote[2803].speaker SPEAKER_24
transcript.pyannote[2803].start 17366.41409375
transcript.pyannote[2803].end 17367.34221875
transcript.pyannote[2804].speaker SPEAKER_35
transcript.pyannote[2804].start 17369.38409375
transcript.pyannote[2804].end 17371.88159375
transcript.pyannote[2805].speaker SPEAKER_24
transcript.pyannote[2805].start 17372.33721875
transcript.pyannote[2805].end 17383.13721875
transcript.pyannote[2806].speaker SPEAKER_35
transcript.pyannote[2806].start 17383.13721875
transcript.pyannote[2806].end 17383.17096875
transcript.pyannote[2807].speaker SPEAKER_24
transcript.pyannote[2807].start 17384.41971875
transcript.pyannote[2807].end 17384.45346875
transcript.pyannote[2808].speaker SPEAKER_35
transcript.pyannote[2808].start 17384.45346875
transcript.pyannote[2808].end 17386.05659375
transcript.pyannote[2809].speaker SPEAKER_24
transcript.pyannote[2809].start 17386.05659375
transcript.pyannote[2809].end 17388.26721875
transcript.pyannote[2810].speaker SPEAKER_35
transcript.pyannote[2810].start 17386.07346875
transcript.pyannote[2810].end 17386.56284375
transcript.pyannote[2811].speaker SPEAKER_35
transcript.pyannote[2811].start 17386.61346875
transcript.pyannote[2811].end 17386.64721875
transcript.pyannote[2812].speaker SPEAKER_35
transcript.pyannote[2812].start 17386.93409375
transcript.pyannote[2812].end 17390.57909375
transcript.pyannote[2813].speaker SPEAKER_24
transcript.pyannote[2813].start 17389.07721875
transcript.pyannote[2813].end 17389.11096875
transcript.pyannote[2814].speaker SPEAKER_24
transcript.pyannote[2814].start 17390.57909375
transcript.pyannote[2814].end 17390.96721875
transcript.pyannote[2815].speaker SPEAKER_35
transcript.pyannote[2815].start 17390.59596875
transcript.pyannote[2815].end 17392.51971875
transcript.pyannote[2816].speaker SPEAKER_24
transcript.pyannote[2816].start 17391.82784375
transcript.pyannote[2816].end 17391.96284375
transcript.pyannote[2817].speaker SPEAKER_35
transcript.pyannote[2817].start 17392.57034375
transcript.pyannote[2817].end 17394.34221875
transcript.pyannote[2818].speaker SPEAKER_35
transcript.pyannote[2818].start 17395.06784375
transcript.pyannote[2818].end 17401.41284375
transcript.pyannote[2819].speaker SPEAKER_35
transcript.pyannote[2819].start 17404.58534375
transcript.pyannote[2819].end 17407.65659375
transcript.pyannote[2820].speaker SPEAKER_35
transcript.pyannote[2820].start 17408.06159375
transcript.pyannote[2820].end 17412.66846875
transcript.pyannote[2821].speaker SPEAKER_35
transcript.pyannote[2821].start 17413.07346875
transcript.pyannote[2821].end 17414.81159375
transcript.pyannote[2822].speaker SPEAKER_35
transcript.pyannote[2822].start 17415.43596875
transcript.pyannote[2822].end 17416.90409375
transcript.pyannote[2823].speaker SPEAKER_35
transcript.pyannote[2823].start 17417.91659375
transcript.pyannote[2823].end 17419.08096875
transcript.pyannote[2824].speaker SPEAKER_35
transcript.pyannote[2824].start 17420.02596875
transcript.pyannote[2824].end 17422.97909375
transcript.pyannote[2825].speaker SPEAKER_35
transcript.pyannote[2825].start 17423.58659375
transcript.pyannote[2825].end 17429.30721875
transcript.pyannote[2826].speaker SPEAKER_35
transcript.pyannote[2826].start 17430.33659375
transcript.pyannote[2826].end 17431.82159375
transcript.pyannote[2827].speaker SPEAKER_35
transcript.pyannote[2827].start 17432.86784375
transcript.pyannote[2827].end 17434.33596875
transcript.pyannote[2828].speaker SPEAKER_35
transcript.pyannote[2828].start 17434.77471875
transcript.pyannote[2828].end 17436.86721875
transcript.pyannote[2829].speaker SPEAKER_35
transcript.pyannote[2829].start 17437.62659375
transcript.pyannote[2829].end 17438.90909375
transcript.pyannote[2830].speaker SPEAKER_35
transcript.pyannote[2830].start 17439.53346875
transcript.pyannote[2830].end 17440.91721875
transcript.pyannote[2831].speaker SPEAKER_35
transcript.pyannote[2831].start 17442.28409375
transcript.pyannote[2831].end 17444.78159375
transcript.pyannote[2832].speaker SPEAKER_35
transcript.pyannote[2832].start 17445.67596875
transcript.pyannote[2832].end 17446.55346875
transcript.pyannote[2833].speaker SPEAKER_35
transcript.pyannote[2833].start 17447.44784375
transcript.pyannote[2833].end 17448.27471875
transcript.pyannote[2834].speaker SPEAKER_35
transcript.pyannote[2834].start 17448.67971875
transcript.pyannote[2834].end 17455.51409375
transcript.pyannote[2835].speaker SPEAKER_35
transcript.pyannote[2835].start 17456.22284375
transcript.pyannote[2835].end 17458.77096875
transcript.pyannote[2836].speaker SPEAKER_22
transcript.pyannote[2836].start 17458.73721875
transcript.pyannote[2836].end 17460.12096875
transcript.pyannote[2837].speaker SPEAKER_35
transcript.pyannote[2837].start 17459.09159375
transcript.pyannote[2837].end 17461.36971875
transcript.pyannote[2838].speaker SPEAKER_35
transcript.pyannote[2838].start 17461.48784375
transcript.pyannote[2838].end 17466.95534375
transcript.pyannote[2839].speaker SPEAKER_22
transcript.pyannote[2839].start 17461.55534375
transcript.pyannote[2839].end 17462.70284375
transcript.pyannote[2840].speaker SPEAKER_24
transcript.pyannote[2840].start 17462.70284375
transcript.pyannote[2840].end 17462.73659375
transcript.pyannote[2841].speaker SPEAKER_22
transcript.pyannote[2841].start 17465.20034375
transcript.pyannote[2841].end 17465.21721875
transcript.pyannote[2842].speaker SPEAKER_24
transcript.pyannote[2842].start 17465.21721875
transcript.pyannote[2842].end 17465.65596875
transcript.pyannote[2843].speaker SPEAKER_35
transcript.pyannote[2843].start 17467.54596875
transcript.pyannote[2843].end 17470.33034375
transcript.pyannote[2844].speaker SPEAKER_35
transcript.pyannote[2844].start 17471.24159375
transcript.pyannote[2844].end 17479.03784375
transcript.pyannote[2845].speaker SPEAKER_35
transcript.pyannote[2845].start 17479.39221875
transcript.pyannote[2845].end 17481.60284375
transcript.pyannote[2846].speaker SPEAKER_35
transcript.pyannote[2846].start 17481.97409375
transcript.pyannote[2846].end 17488.72409375
transcript.pyannote[2847].speaker SPEAKER_35
transcript.pyannote[2847].start 17489.04471875
transcript.pyannote[2847].end 17491.20471875
transcript.pyannote[2848].speaker SPEAKER_35
transcript.pyannote[2848].start 17491.55909375
transcript.pyannote[2848].end 17492.74034375
transcript.pyannote[2849].speaker SPEAKER_24
transcript.pyannote[2849].start 17491.64346875
transcript.pyannote[2849].end 17492.03159375
transcript.pyannote[2850].speaker SPEAKER_24
transcript.pyannote[2850].start 17492.74034375
transcript.pyannote[2850].end 17515.13346875
transcript.pyannote[2851].speaker SPEAKER_35
transcript.pyannote[2851].start 17493.66846875
transcript.pyannote[2851].end 17498.20784375
transcript.pyannote[2852].speaker SPEAKER_24
transcript.pyannote[2852].start 17515.33596875
transcript.pyannote[2852].end 17517.90096875
transcript.pyannote[2853].speaker SPEAKER_35
transcript.pyannote[2853].start 17517.90096875
transcript.pyannote[2853].end 17526.76034375
transcript.pyannote[2854].speaker SPEAKER_35
transcript.pyannote[2854].start 17527.16534375
transcript.pyannote[2854].end 17528.00909375
transcript.pyannote[2855].speaker SPEAKER_35
transcript.pyannote[2855].start 17529.25784375
transcript.pyannote[2855].end 17533.03784375
transcript.pyannote[2856].speaker SPEAKER_35
transcript.pyannote[2856].start 17533.29096875
transcript.pyannote[2856].end 17534.87721875
transcript.pyannote[2857].speaker SPEAKER_35
transcript.pyannote[2857].start 17535.18096875
transcript.pyannote[2857].end 17536.95284375
transcript.pyannote[2858].speaker SPEAKER_35
transcript.pyannote[2858].start 17537.44221875
transcript.pyannote[2858].end 17539.73721875
transcript.pyannote[2859].speaker SPEAKER_35
transcript.pyannote[2859].start 17540.17596875
transcript.pyannote[2859].end 17540.56409375
transcript.pyannote[2860].speaker SPEAKER_35
transcript.pyannote[2860].start 17540.90159375
transcript.pyannote[2860].end 17541.86346875
transcript.pyannote[2861].speaker SPEAKER_35
transcript.pyannote[2861].start 17542.25159375
transcript.pyannote[2861].end 17543.41596875
transcript.pyannote[2862].speaker SPEAKER_35
transcript.pyannote[2862].start 17545.71096875
transcript.pyannote[2862].end 17555.65034375
transcript.pyannote[2863].speaker SPEAKER_35
transcript.pyannote[2863].start 17557.48971875
transcript.pyannote[2863].end 17559.86909375
transcript.pyannote[2864].speaker SPEAKER_24
transcript.pyannote[2864].start 17559.22784375
transcript.pyannote[2864].end 17560.93221875
transcript.pyannote[2865].speaker SPEAKER_35
transcript.pyannote[2865].start 17560.08846875
transcript.pyannote[2865].end 17564.39159375
transcript.pyannote[2866].speaker SPEAKER_35
transcript.pyannote[2866].start 17564.99909375
transcript.pyannote[2866].end 17569.62284375
transcript.pyannote[2867].speaker SPEAKER_03
transcript.pyannote[2867].start 17571.90096875
transcript.pyannote[2867].end 17579.27534375
transcript.pyannote[2868].speaker SPEAKER_09
transcript.pyannote[2868].start 17589.73784375
transcript.pyannote[2868].end 17591.76284375
transcript.pyannote[2869].speaker SPEAKER_03
transcript.pyannote[2869].start 17592.13409375
transcript.pyannote[2869].end 17592.94409375
transcript.pyannote[2870].speaker SPEAKER_22
transcript.pyannote[2870].start 17602.37721875
transcript.pyannote[2870].end 17602.93409375
transcript.pyannote[2871].speaker SPEAKER_19
transcript.pyannote[2871].start 17602.98471875
transcript.pyannote[2871].end 17616.40034375
transcript.pyannote[2872].speaker SPEAKER_19
transcript.pyannote[2872].start 17616.48471875
transcript.pyannote[2872].end 17618.39159375
transcript.pyannote[2873].speaker SPEAKER_19
transcript.pyannote[2873].start 17618.76284375
transcript.pyannote[2873].end 17621.14221875
transcript.pyannote[2874].speaker SPEAKER_19
transcript.pyannote[2874].start 17621.46284375
transcript.pyannote[2874].end 17624.97284375
transcript.pyannote[2875].speaker SPEAKER_19
transcript.pyannote[2875].start 17625.34409375
transcript.pyannote[2875].end 17626.87971875
transcript.pyannote[2876].speaker SPEAKER_19
transcript.pyannote[2876].start 17626.99784375
transcript.pyannote[2876].end 17629.81596875
transcript.pyannote[2877].speaker SPEAKER_19
transcript.pyannote[2877].start 17630.10284375
transcript.pyannote[2877].end 17671.51409375
transcript.pyannote[2878].speaker SPEAKER_24
transcript.pyannote[2878].start 17671.75034375
transcript.pyannote[2878].end 17704.35284375
transcript.pyannote[2879].speaker SPEAKER_19
transcript.pyannote[2879].start 17677.52159375
transcript.pyannote[2879].end 17677.82534375
transcript.pyannote[2880].speaker SPEAKER_00
transcript.pyannote[2880].start 17683.64721875
transcript.pyannote[2880].end 17683.79909375
transcript.pyannote[2881].speaker SPEAKER_22
transcript.pyannote[2881].start 17684.01846875
transcript.pyannote[2881].end 17684.37284375
transcript.pyannote[2882].speaker SPEAKER_23
transcript.pyannote[2882].start 17704.35284375
transcript.pyannote[2882].end 17704.43721875
transcript.pyannote[2883].speaker SPEAKER_24
transcript.pyannote[2883].start 17704.43721875
transcript.pyannote[2883].end 17704.60596875
transcript.pyannote[2884].speaker SPEAKER_19
transcript.pyannote[2884].start 17704.60596875
transcript.pyannote[2884].end 17705.02784375
transcript.pyannote[2885].speaker SPEAKER_24
transcript.pyannote[2885].start 17704.72409375
transcript.pyannote[2885].end 17705.04471875
transcript.pyannote[2886].speaker SPEAKER_33
transcript.pyannote[2886].start 17705.02784375
transcript.pyannote[2886].end 17705.09534375
transcript.pyannote[2887].speaker SPEAKER_19
transcript.pyannote[2887].start 17705.04471875
transcript.pyannote[2887].end 17705.19659375
transcript.pyannote[2888].speaker SPEAKER_33
transcript.pyannote[2888].start 17705.19659375
transcript.pyannote[2888].end 17705.23034375
transcript.pyannote[2889].speaker SPEAKER_33
transcript.pyannote[2889].start 17705.77034375
transcript.pyannote[2889].end 17726.32409375
transcript.pyannote[2890].speaker SPEAKER_19
transcript.pyannote[2890].start 17722.59471875
transcript.pyannote[2890].end 17722.88159375
transcript.pyannote[2891].speaker SPEAKER_19
transcript.pyannote[2891].start 17726.47596875
transcript.pyannote[2891].end 17726.84721875
transcript.pyannote[2892].speaker SPEAKER_19
transcript.pyannote[2892].start 17727.15096875
transcript.pyannote[2892].end 17738.62596875
transcript.pyannote[2893].speaker SPEAKER_19
transcript.pyannote[2893].start 17738.87909375
transcript.pyannote[2893].end 17745.57846875
transcript.pyannote[2894].speaker SPEAKER_19
transcript.pyannote[2894].start 17745.96659375
transcript.pyannote[2894].end 17755.61909375
transcript.pyannote[2895].speaker SPEAKER_19
transcript.pyannote[2895].start 17755.85534375
transcript.pyannote[2895].end 17765.62596875
transcript.pyannote[2896].speaker SPEAKER_19
transcript.pyannote[2896].start 17766.14909375
transcript.pyannote[2896].end 17767.27971875
transcript.pyannote[2897].speaker SPEAKER_19
transcript.pyannote[2897].start 17767.60034375
transcript.pyannote[2897].end 17768.93346875
transcript.pyannote[2898].speaker SPEAKER_19
transcript.pyannote[2898].start 17769.49034375
transcript.pyannote[2898].end 17774.02971875
transcript.pyannote[2899].speaker SPEAKER_19
transcript.pyannote[2899].start 17774.45159375
transcript.pyannote[2899].end 17786.02784375
transcript.pyannote[2900].speaker SPEAKER_19
transcript.pyannote[2900].start 17786.14596875
transcript.pyannote[2900].end 17789.20034375
transcript.pyannote[2901].speaker SPEAKER_24
transcript.pyannote[2901].start 17789.80784375
transcript.pyannote[2901].end 17792.47409375
transcript.pyannote[2902].speaker SPEAKER_24
transcript.pyannote[2902].start 17793.36846875
transcript.pyannote[2902].end 17803.02096875
transcript.pyannote[2903].speaker SPEAKER_19
transcript.pyannote[2903].start 17803.02096875
transcript.pyannote[2903].end 17803.25721875
transcript.pyannote[2904].speaker SPEAKER_24
transcript.pyannote[2904].start 17803.25721875
transcript.pyannote[2904].end 17803.79721875
transcript.pyannote[2905].speaker SPEAKER_19
transcript.pyannote[2905].start 17803.44284375
transcript.pyannote[2905].end 17806.86846875
transcript.pyannote[2906].speaker SPEAKER_24
transcript.pyannote[2906].start 17806.71659375
transcript.pyannote[2906].end 17807.12159375
transcript.pyannote[2907].speaker SPEAKER_19
transcript.pyannote[2907].start 17807.12159375
transcript.pyannote[2907].end 17810.14221875
transcript.pyannote[2908].speaker SPEAKER_24
transcript.pyannote[2908].start 17810.49659375
transcript.pyannote[2908].end 17813.71971875
transcript.pyannote[2909].speaker SPEAKER_24
transcript.pyannote[2909].start 17814.10784375
transcript.pyannote[2909].end 17837.05784375
transcript.pyannote[2910].speaker SPEAKER_29
transcript.pyannote[2910].start 17823.99659375
transcript.pyannote[2910].end 17824.35096875
transcript.pyannote[2911].speaker SPEAKER_24
transcript.pyannote[2911].start 17837.69909375
transcript.pyannote[2911].end 17840.77034375
transcript.pyannote[2912].speaker SPEAKER_24
transcript.pyannote[2912].start 17841.58034375
transcript.pyannote[2912].end 17848.76909375
transcript.pyannote[2913].speaker SPEAKER_22
transcript.pyannote[2913].start 17844.68534375
transcript.pyannote[2913].end 17845.02284375
transcript.pyannote[2914].speaker SPEAKER_24
transcript.pyannote[2914].start 17849.03909375
transcript.pyannote[2914].end 17856.93659375
transcript.pyannote[2915].speaker SPEAKER_19
transcript.pyannote[2915].start 17854.13534375
transcript.pyannote[2915].end 17854.42221875
transcript.pyannote[2916].speaker SPEAKER_19
transcript.pyannote[2916].start 17857.02096875
transcript.pyannote[2916].end 17866.13346875
transcript.pyannote[2917].speaker SPEAKER_22
transcript.pyannote[2917].start 17865.94784375
transcript.pyannote[2917].end 17866.30221875
transcript.pyannote[2918].speaker SPEAKER_19
transcript.pyannote[2918].start 17866.30221875
transcript.pyannote[2918].end 17873.18721875
transcript.pyannote[2919].speaker SPEAKER_22
transcript.pyannote[2919].start 17872.52909375
transcript.pyannote[2919].end 17875.87034375
transcript.pyannote[2920].speaker SPEAKER_19
transcript.pyannote[2920].start 17873.32221875
transcript.pyannote[2920].end 17875.63409375
transcript.pyannote[2921].speaker SPEAKER_19
transcript.pyannote[2921].start 17875.76909375
transcript.pyannote[2921].end 17897.23409375
transcript.pyannote[2922].speaker SPEAKER_24
transcript.pyannote[2922].start 17897.85846875
transcript.pyannote[2922].end 17906.04284375
transcript.pyannote[2923].speaker SPEAKER_19
transcript.pyannote[2923].start 17902.63409375
transcript.pyannote[2923].end 17903.57909375
transcript.pyannote[2924].speaker SPEAKER_19
transcript.pyannote[2924].start 17905.13159375
transcript.pyannote[2924].end 17908.96221875
transcript.pyannote[2925].speaker SPEAKER_24
transcript.pyannote[2925].start 17906.83596875
transcript.pyannote[2925].end 17907.52784375
transcript.pyannote[2926].speaker SPEAKER_24
transcript.pyannote[2926].start 17908.27034375
transcript.pyannote[2926].end 17912.25284375
transcript.pyannote[2927].speaker SPEAKER_24
transcript.pyannote[2927].start 17912.84346875
transcript.pyannote[2927].end 17923.06971875
transcript.pyannote[2928].speaker SPEAKER_19
transcript.pyannote[2928].start 17914.27784375
transcript.pyannote[2928].end 17914.71659375
transcript.pyannote[2929].speaker SPEAKER_19
transcript.pyannote[2929].start 17920.30221875
transcript.pyannote[2929].end 17920.89284375
transcript.pyannote[2930].speaker SPEAKER_19
transcript.pyannote[2930].start 17921.97284375
transcript.pyannote[2930].end 17927.64284375
transcript.pyannote[2931].speaker SPEAKER_24
transcript.pyannote[2931].start 17926.95096875
transcript.pyannote[2931].end 17932.75596875
transcript.pyannote[2932].speaker SPEAKER_19
transcript.pyannote[2932].start 17932.03034375
transcript.pyannote[2932].end 17932.28346875
transcript.pyannote[2933].speaker SPEAKER_19
transcript.pyannote[2933].start 17932.70534375
transcript.pyannote[2933].end 17942.69534375
transcript.pyannote[2934].speaker SPEAKER_19
transcript.pyannote[2934].start 17943.50534375
transcript.pyannote[2934].end 17944.93971875
transcript.pyannote[2935].speaker SPEAKER_24
transcript.pyannote[2935].start 17945.59784375
transcript.pyannote[2935].end 17962.16909375
transcript.pyannote[2936].speaker SPEAKER_19
transcript.pyannote[2936].start 17950.06971875
transcript.pyannote[2936].end 17952.29721875
transcript.pyannote[2937].speaker SPEAKER_22
transcript.pyannote[2937].start 17952.29721875
transcript.pyannote[2937].end 17952.38159375
transcript.pyannote[2938].speaker SPEAKER_22
transcript.pyannote[2938].start 17955.43596875
transcript.pyannote[2938].end 17955.46971875
transcript.pyannote[2939].speaker SPEAKER_19
transcript.pyannote[2939].start 17955.46971875
transcript.pyannote[2939].end 17955.80721875
transcript.pyannote[2940].speaker SPEAKER_19
transcript.pyannote[2940].start 17960.76846875
transcript.pyannote[2940].end 17961.35909375
transcript.pyannote[2941].speaker SPEAKER_19
transcript.pyannote[2941].start 17961.52784375
transcript.pyannote[2941].end 17964.37971875
transcript.pyannote[2942].speaker SPEAKER_24
transcript.pyannote[2942].start 17963.60346875
transcript.pyannote[2942].end 17967.55221875
transcript.pyannote[2943].speaker SPEAKER_19
transcript.pyannote[2943].start 17965.13909375
transcript.pyannote[2943].end 17965.49346875
transcript.pyannote[2944].speaker SPEAKER_19
transcript.pyannote[2944].start 17966.89409375
transcript.pyannote[2944].end 18002.88846875
transcript.pyannote[2945].speaker SPEAKER_19
transcript.pyannote[2945].start 18003.05721875
transcript.pyannote[2945].end 18030.96846875
transcript.pyannote[2946].speaker SPEAKER_19
transcript.pyannote[2946].start 18031.13721875
transcript.pyannote[2946].end 18045.90284375
transcript.pyannote[2947].speaker SPEAKER_19
transcript.pyannote[2947].start 18045.97034375
transcript.pyannote[2947].end 18084.93471875
transcript.pyannote[2948].speaker SPEAKER_19
transcript.pyannote[2948].start 18085.60971875
transcript.pyannote[2948].end 18088.54596875
transcript.pyannote[2949].speaker SPEAKER_24
transcript.pyannote[2949].start 18087.93846875
transcript.pyannote[2949].end 18098.13096875
transcript.pyannote[2950].speaker SPEAKER_24
transcript.pyannote[2950].start 18098.50221875
transcript.pyannote[2950].end 18114.28034375
transcript.pyannote[2951].speaker SPEAKER_09
transcript.pyannote[2951].start 18107.42909375
transcript.pyannote[2951].end 18107.44596875
transcript.pyannote[2952].speaker SPEAKER_19
transcript.pyannote[2952].start 18107.44596875
transcript.pyannote[2952].end 18107.74971875
transcript.pyannote[2953].speaker SPEAKER_09
transcript.pyannote[2953].start 18107.74971875
transcript.pyannote[2953].end 18107.76659375
transcript.pyannote[2954].speaker SPEAKER_19
transcript.pyannote[2954].start 18113.33534375
transcript.pyannote[2954].end 18118.97159375
transcript.pyannote[2955].speaker SPEAKER_19
transcript.pyannote[2955].start 18119.46096875
transcript.pyannote[2955].end 18129.61971875
transcript.pyannote[2956].speaker SPEAKER_24
transcript.pyannote[2956].start 18129.34971875
transcript.pyannote[2956].end 18148.78971875
transcript.pyannote[2957].speaker SPEAKER_19
transcript.pyannote[2957].start 18136.65659375
transcript.pyannote[2957].end 18136.97721875
transcript.pyannote[2958].speaker SPEAKER_22
transcript.pyannote[2958].start 18136.97721875
transcript.pyannote[2958].end 18137.31471875
transcript.pyannote[2959].speaker SPEAKER_22
transcript.pyannote[2959].start 18137.61846875
transcript.pyannote[2959].end 18137.82096875
transcript.pyannote[2960].speaker SPEAKER_19
transcript.pyannote[2960].start 18144.06471875
transcript.pyannote[2960].end 18144.62159375
transcript.pyannote[2961].speaker SPEAKER_19
transcript.pyannote[2961].start 18145.97159375
transcript.pyannote[2961].end 18146.66346875
transcript.pyannote[2962].speaker SPEAKER_19
transcript.pyannote[2962].start 18146.68034375
transcript.pyannote[2962].end 18155.30346875
transcript.pyannote[2963].speaker SPEAKER_03
transcript.pyannote[2963].start 18150.40971875
transcript.pyannote[2963].end 18150.42659375
transcript.pyannote[2964].speaker SPEAKER_03
transcript.pyannote[2964].start 18152.46846875
transcript.pyannote[2964].end 18152.89034375
transcript.pyannote[2965].speaker SPEAKER_03
transcript.pyannote[2965].start 18153.26159375
transcript.pyannote[2965].end 18154.08846875
transcript.pyannote[2966].speaker SPEAKER_03
transcript.pyannote[2966].start 18155.82659375
transcript.pyannote[2966].end 18157.73346875
transcript.pyannote[2967].speaker SPEAKER_03
transcript.pyannote[2967].start 18159.10034375
transcript.pyannote[2967].end 18160.48409375
transcript.pyannote[2968].speaker SPEAKER_03
transcript.pyannote[2968].start 18161.20971875
transcript.pyannote[2968].end 18166.03596875
transcript.pyannote[2969].speaker SPEAKER_19
transcript.pyannote[2969].start 18174.77721875
transcript.pyannote[2969].end 18176.38034375
transcript.pyannote[2970].speaker SPEAKER_03
transcript.pyannote[2970].start 18176.80221875
transcript.pyannote[2970].end 18177.62909375
transcript.pyannote[2971].speaker SPEAKER_03
transcript.pyannote[2971].start 18178.79346875
transcript.pyannote[2971].end 18180.43034375
transcript.pyannote[2972].speaker SPEAKER_03
transcript.pyannote[2972].start 18181.12221875
transcript.pyannote[2972].end 18182.15159375
transcript.pyannote[2973].speaker SPEAKER_03
transcript.pyannote[2973].start 18182.82659375
transcript.pyannote[2973].end 18184.48034375
transcript.pyannote[2974].speaker SPEAKER_22
transcript.pyannote[2974].start 18185.99909375
transcript.pyannote[2974].end 18186.53909375
transcript.pyannote[2975].speaker SPEAKER_19
transcript.pyannote[2975].start 18186.64034375
transcript.pyannote[2975].end 18195.61784375
transcript.pyannote[2976].speaker SPEAKER_24
transcript.pyannote[2976].start 18196.61346875
transcript.pyannote[2976].end 18200.68034375
transcript.pyannote[2977].speaker SPEAKER_19
transcript.pyannote[2977].start 18200.00534375
transcript.pyannote[2977].end 18201.13596875
transcript.pyannote[2978].speaker SPEAKER_24
transcript.pyannote[2978].start 18201.13596875
transcript.pyannote[2978].end 18201.35534375
transcript.pyannote[2979].speaker SPEAKER_24
transcript.pyannote[2979].start 18202.11471875
transcript.pyannote[2979].end 18202.35096875
transcript.pyannote[2980].speaker SPEAKER_24
transcript.pyannote[2980].start 18203.24534375
transcript.pyannote[2980].end 18205.35471875
transcript.pyannote[2981].speaker SPEAKER_19
transcript.pyannote[2981].start 18205.62471875
transcript.pyannote[2981].end 18208.20659375
transcript.pyannote[2982].speaker SPEAKER_24
transcript.pyannote[2982].start 18207.91971875
transcript.pyannote[2982].end 18208.76346875
transcript.pyannote[2983].speaker SPEAKER_19
transcript.pyannote[2983].start 18208.91534375
transcript.pyannote[2983].end 18209.99534375
transcript.pyannote[2984].speaker SPEAKER_24
transcript.pyannote[2984].start 18209.35409375
transcript.pyannote[2984].end 18214.82159375
transcript.pyannote[2985].speaker SPEAKER_19
transcript.pyannote[2985].start 18213.31971875
transcript.pyannote[2985].end 18218.11221875
transcript.pyannote[2986].speaker SPEAKER_24
transcript.pyannote[2986].start 18216.13784375
transcript.pyannote[2986].end 18216.71159375
transcript.pyannote[2987].speaker SPEAKER_24
transcript.pyannote[2987].start 18216.84659375
transcript.pyannote[2987].end 18218.16284375
transcript.pyannote[2988].speaker SPEAKER_19
transcript.pyannote[2988].start 18218.39909375
transcript.pyannote[2988].end 18218.80409375
transcript.pyannote[2989].speaker SPEAKER_19
transcript.pyannote[2989].start 18219.00659375
transcript.pyannote[2989].end 18221.58846875
transcript.pyannote[2990].speaker SPEAKER_24
transcript.pyannote[2990].start 18222.04409375
transcript.pyannote[2990].end 18223.19159375
transcript.pyannote[2991].speaker SPEAKER_19
transcript.pyannote[2991].start 18223.19159375
transcript.pyannote[2991].end 18227.61284375
transcript.pyannote[2992].speaker SPEAKER_19
transcript.pyannote[2992].start 18228.10221875
transcript.pyannote[2992].end 18231.22409375
transcript.pyannote[2993].speaker SPEAKER_24
transcript.pyannote[2993].start 18232.42221875
transcript.pyannote[2993].end 18233.38409375
transcript.pyannote[2994].speaker SPEAKER_24
transcript.pyannote[2994].start 18234.29534375
transcript.pyannote[2994].end 18236.10096875
transcript.pyannote[2995].speaker SPEAKER_19
transcript.pyannote[2995].start 18236.30346875
transcript.pyannote[2995].end 18237.85596875
transcript.pyannote[2996].speaker SPEAKER_24
transcript.pyannote[2996].start 18240.37034375
transcript.pyannote[2996].end 18240.97784375
transcript.pyannote[2997].speaker SPEAKER_22
transcript.pyannote[2997].start 18240.97784375
transcript.pyannote[2997].end 18241.26471875
transcript.pyannote[2998].speaker SPEAKER_19
transcript.pyannote[2998].start 18241.43346875
transcript.pyannote[2998].end 18254.57909375
transcript.pyannote[2999].speaker SPEAKER_19
transcript.pyannote[2999].start 18254.61284375
transcript.pyannote[2999].end 18268.80471875
transcript.pyannote[3000].speaker SPEAKER_19
transcript.pyannote[3000].start 18269.32784375
transcript.pyannote[3000].end 18270.42471875
transcript.pyannote[3001].speaker SPEAKER_19
transcript.pyannote[3001].start 18270.74534375
transcript.pyannote[3001].end 18276.31409375
transcript.pyannote[3002].speaker SPEAKER_19
transcript.pyannote[3002].start 18276.78659375
transcript.pyannote[3002].end 18282.40596875
transcript.pyannote[3003].speaker SPEAKER_19
transcript.pyannote[3003].start 18282.65909375
transcript.pyannote[3003].end 18285.56159375
transcript.pyannote[3004].speaker SPEAKER_24
transcript.pyannote[3004].start 18286.40534375
transcript.pyannote[3004].end 18287.04659375
transcript.pyannote[3005].speaker SPEAKER_19
transcript.pyannote[3005].start 18287.04659375
transcript.pyannote[3005].end 18288.61596875
transcript.pyannote[3006].speaker SPEAKER_19
transcript.pyannote[3006].start 18289.03784375
transcript.pyannote[3006].end 18290.53971875
transcript.pyannote[3007].speaker SPEAKER_19
transcript.pyannote[3007].start 18290.89409375
transcript.pyannote[3007].end 18311.17784375
transcript.pyannote[3008].speaker SPEAKER_19
transcript.pyannote[3008].start 18312.13971875
transcript.pyannote[3008].end 18319.19346875
transcript.pyannote[3009].speaker SPEAKER_22
transcript.pyannote[3009].start 18319.07534375
transcript.pyannote[3009].end 18319.46346875
transcript.pyannote[3010].speaker SPEAKER_19
transcript.pyannote[3010].start 18319.46346875
transcript.pyannote[3010].end 18330.29721875
transcript.pyannote[3011].speaker SPEAKER_19
transcript.pyannote[3011].start 18330.93846875
transcript.pyannote[3011].end 18336.13596875
transcript.pyannote[3012].speaker SPEAKER_24
transcript.pyannote[3012].start 18336.13596875
transcript.pyannote[3012].end 18341.82284375
transcript.pyannote[3013].speaker SPEAKER_19
transcript.pyannote[3013].start 18336.15284375
transcript.pyannote[3013].end 18336.16971875
transcript.pyannote[3014].speaker SPEAKER_19
transcript.pyannote[3014].start 18336.47346875
transcript.pyannote[3014].end 18336.62534375
transcript.pyannote[3015].speaker SPEAKER_24
transcript.pyannote[3015].start 18342.48096875
transcript.pyannote[3015].end 18345.01221875
transcript.pyannote[3016].speaker SPEAKER_19
transcript.pyannote[3016].start 18344.87721875
transcript.pyannote[3016].end 18344.94471875
transcript.pyannote[3017].speaker SPEAKER_19
transcript.pyannote[3017].start 18345.01221875
transcript.pyannote[3017].end 18345.40034375
transcript.pyannote[3018].speaker SPEAKER_24
transcript.pyannote[3018].start 18345.40034375
transcript.pyannote[3018].end 18347.25659375
transcript.pyannote[3019].speaker SPEAKER_19
transcript.pyannote[3019].start 18345.99096875
transcript.pyannote[3019].end 18350.09159375
transcript.pyannote[3020].speaker SPEAKER_24
transcript.pyannote[3020].start 18347.88096875
transcript.pyannote[3020].end 18349.02846875
transcript.pyannote[3021].speaker SPEAKER_24
transcript.pyannote[3021].start 18349.36596875
transcript.pyannote[3021].end 18360.48659375
transcript.pyannote[3022].speaker SPEAKER_19
transcript.pyannote[3022].start 18358.37721875
transcript.pyannote[3022].end 18361.43159375
transcript.pyannote[3023].speaker SPEAKER_19
transcript.pyannote[3023].start 18361.95471875
transcript.pyannote[3023].end 18387.03096875
transcript.pyannote[3024].speaker SPEAKER_00
transcript.pyannote[3024].start 18370.61159375
transcript.pyannote[3024].end 18371.01659375
transcript.pyannote[3025].speaker SPEAKER_19
transcript.pyannote[3025].start 18387.53721875
transcript.pyannote[3025].end 18393.93284375
transcript.pyannote[3026].speaker SPEAKER_19
transcript.pyannote[3026].start 18394.48971875
transcript.pyannote[3026].end 18403.90596875
transcript.pyannote[3027].speaker SPEAKER_19
transcript.pyannote[3027].start 18404.15909375
transcript.pyannote[3027].end 18429.40409375
transcript.pyannote[3028].speaker SPEAKER_19
transcript.pyannote[3028].start 18430.16346875
transcript.pyannote[3028].end 18436.32284375
transcript.pyannote[3029].speaker SPEAKER_19
transcript.pyannote[3029].start 18437.75721875
transcript.pyannote[3029].end 18439.71471875
transcript.pyannote[3030].speaker SPEAKER_19
transcript.pyannote[3030].start 18440.06909375
transcript.pyannote[3030].end 18446.51534375
transcript.pyannote[3031].speaker SPEAKER_19
transcript.pyannote[3031].start 18446.97096875
transcript.pyannote[3031].end 18461.92221875
transcript.pyannote[3032].speaker SPEAKER_19
transcript.pyannote[3032].start 18462.09096875
transcript.pyannote[3032].end 18463.44096875
transcript.pyannote[3033].speaker SPEAKER_19
transcript.pyannote[3033].start 18464.21721875
transcript.pyannote[3033].end 18469.63409375
transcript.pyannote[3034].speaker SPEAKER_19
transcript.pyannote[3034].start 18469.68471875
transcript.pyannote[3034].end 18472.21596875
transcript.pyannote[3035].speaker SPEAKER_24
transcript.pyannote[3035].start 18471.55784375
transcript.pyannote[3035].end 18474.10596875
transcript.pyannote[3036].speaker SPEAKER_10
transcript.pyannote[3036].start 18475.57409375
transcript.pyannote[3036].end 18478.57784375
transcript.pyannote[3037].speaker SPEAKER_10
transcript.pyannote[3037].start 18479.10096875
transcript.pyannote[3037].end 18482.45909375
transcript.pyannote[3038].speaker SPEAKER_19
transcript.pyannote[3038].start 18481.88534375
transcript.pyannote[3038].end 18481.96971875
transcript.pyannote[3039].speaker SPEAKER_19
transcript.pyannote[3039].start 18482.45909375
transcript.pyannote[3039].end 18482.71221875
transcript.pyannote[3040].speaker SPEAKER_10
transcript.pyannote[3040].start 18482.71221875
transcript.pyannote[3040].end 18483.92721875
transcript.pyannote[3041].speaker SPEAKER_10
transcript.pyannote[3041].start 18485.37846875
transcript.pyannote[3041].end 18496.12784375
transcript.pyannote[3042].speaker SPEAKER_10
transcript.pyannote[3042].start 18496.16159375
transcript.pyannote[3042].end 18511.65284375
transcript.pyannote[3043].speaker SPEAKER_19
transcript.pyannote[3043].start 18499.19909375
transcript.pyannote[3043].end 18499.68846875
transcript.pyannote[3044].speaker SPEAKER_19
transcript.pyannote[3044].start 18511.65284375
transcript.pyannote[3044].end 18540.76221875
transcript.pyannote[3045].speaker SPEAKER_24
transcript.pyannote[3045].start 18539.49659375
transcript.pyannote[3045].end 18539.90159375
transcript.pyannote[3046].speaker SPEAKER_24
transcript.pyannote[3046].start 18540.66096875
transcript.pyannote[3046].end 18549.87471875
transcript.pyannote[3047].speaker SPEAKER_19
transcript.pyannote[3047].start 18549.67221875
transcript.pyannote[3047].end 18552.96284375
transcript.pyannote[3048].speaker SPEAKER_19
transcript.pyannote[3048].start 18553.90784375
transcript.pyannote[3048].end 18554.29596875
transcript.pyannote[3049].speaker SPEAKER_19
transcript.pyannote[3049].start 18554.73471875
transcript.pyannote[3049].end 18557.83971875
transcript.pyannote[3050].speaker SPEAKER_19
transcript.pyannote[3050].start 18558.24471875
transcript.pyannote[3050].end 18558.63284375
transcript.pyannote[3051].speaker SPEAKER_19
transcript.pyannote[3051].start 18559.27409375
transcript.pyannote[3051].end 18563.74596875
transcript.pyannote[3052].speaker SPEAKER_19
transcript.pyannote[3052].start 18564.69096875
transcript.pyannote[3052].end 18566.31096875
transcript.pyannote[3053].speaker SPEAKER_19
transcript.pyannote[3053].start 18566.85096875
transcript.pyannote[3053].end 18571.47471875
transcript.pyannote[3054].speaker SPEAKER_19
transcript.pyannote[3054].start 18572.38596875
transcript.pyannote[3054].end 18579.96284375
transcript.pyannote[3055].speaker SPEAKER_19
transcript.pyannote[3055].start 18580.50284375
transcript.pyannote[3055].end 18581.80221875
transcript.pyannote[3056].speaker SPEAKER_19
transcript.pyannote[3056].start 18582.20721875
transcript.pyannote[3056].end 18583.99596875
transcript.pyannote[3057].speaker SPEAKER_19
transcript.pyannote[3057].start 18584.77221875
transcript.pyannote[3057].end 18585.39659375
transcript.pyannote[3058].speaker SPEAKER_19
transcript.pyannote[3058].start 18586.00409375
transcript.pyannote[3058].end 18586.44284375
transcript.pyannote[3059].speaker SPEAKER_19
transcript.pyannote[3059].start 18587.16846875
transcript.pyannote[3059].end 18590.45909375
transcript.pyannote[3060].speaker SPEAKER_19
transcript.pyannote[3060].start 18590.98221875
transcript.pyannote[3060].end 18593.66534375
transcript.pyannote[3061].speaker SPEAKER_19
transcript.pyannote[3061].start 18594.10409375
transcript.pyannote[3061].end 18597.56346875
transcript.pyannote[3062].speaker SPEAKER_19
transcript.pyannote[3062].start 18598.89659375
transcript.pyannote[3062].end 18599.47034375
transcript.pyannote[3063].speaker SPEAKER_22
transcript.pyannote[3063].start 18598.91346875
transcript.pyannote[3063].end 18600.02721875
transcript.pyannote[3064].speaker SPEAKER_19
transcript.pyannote[3064].start 18599.99346875
transcript.pyannote[3064].end 18602.15346875
transcript.pyannote[3065].speaker SPEAKER_22
transcript.pyannote[3065].start 18602.08596875
transcript.pyannote[3065].end 18602.77784375
transcript.pyannote[3066].speaker SPEAKER_19
transcript.pyannote[3066].start 18603.16596875
transcript.pyannote[3066].end 18603.68909375
transcript.pyannote[3067].speaker SPEAKER_22
transcript.pyannote[3067].start 18603.68909375
transcript.pyannote[3067].end 18604.39784375
transcript.pyannote[3068].speaker SPEAKER_19
transcript.pyannote[3068].start 18604.38096875
transcript.pyannote[3068].end 18610.45596875
transcript.pyannote[3069].speaker SPEAKER_19
transcript.pyannote[3069].start 18610.72596875
transcript.pyannote[3069].end 18612.32909375
transcript.pyannote[3070].speaker SPEAKER_19
transcript.pyannote[3070].start 18612.80159375
transcript.pyannote[3070].end 18618.18471875
transcript.pyannote[3071].speaker SPEAKER_19
transcript.pyannote[3071].start 18618.89346875
transcript.pyannote[3071].end 18622.79159375
transcript.pyannote[3072].speaker SPEAKER_19
transcript.pyannote[3072].start 18623.11221875
transcript.pyannote[3072].end 18627.06096875
transcript.pyannote[3073].speaker SPEAKER_19
transcript.pyannote[3073].start 18628.02284375
transcript.pyannote[3073].end 18628.56284375
transcript.pyannote[3074].speaker SPEAKER_19
transcript.pyannote[3074].start 18628.79909375
transcript.pyannote[3074].end 18634.01346875
transcript.pyannote[3075].speaker SPEAKER_19
transcript.pyannote[3075].start 18634.19909375
transcript.pyannote[3075].end 18653.20034375
transcript.pyannote[3076].speaker SPEAKER_19
transcript.pyannote[3076].start 18654.24659375
transcript.pyannote[3076].end 18671.84721875
transcript.pyannote[3077].speaker SPEAKER_24
transcript.pyannote[3077].start 18673.56846875
transcript.pyannote[3077].end 18676.38659375
transcript.pyannote[3078].speaker SPEAKER_19
transcript.pyannote[3078].start 18676.47096875
transcript.pyannote[3078].end 18679.13721875
transcript.pyannote[3079].speaker SPEAKER_24
transcript.pyannote[3079].start 18679.18784375
transcript.pyannote[3079].end 18680.58846875
transcript.pyannote[3080].speaker SPEAKER_19
transcript.pyannote[3080].start 18679.86284375
transcript.pyannote[3080].end 18684.48659375
transcript.pyannote[3081].speaker SPEAKER_24
transcript.pyannote[3081].start 18683.01846875
transcript.pyannote[3081].end 18683.67659375
transcript.pyannote[3082].speaker SPEAKER_24
transcript.pyannote[3082].start 18684.80721875
transcript.pyannote[3082].end 18689.70096875
transcript.pyannote[3083].speaker SPEAKER_24
transcript.pyannote[3083].start 18691.10159375
transcript.pyannote[3083].end 18692.65409375
transcript.pyannote[3084].speaker SPEAKER_19
transcript.pyannote[3084].start 18691.42221875
transcript.pyannote[3084].end 18692.92409375
transcript.pyannote[3085].speaker SPEAKER_19
transcript.pyannote[3085].start 18693.93659375
transcript.pyannote[3085].end 18696.09659375
transcript.pyannote[3086].speaker SPEAKER_24
transcript.pyannote[3086].start 18695.65784375
transcript.pyannote[3086].end 18699.85971875
transcript.pyannote[3087].speaker SPEAKER_19
transcript.pyannote[3087].start 18696.46784375
transcript.pyannote[3087].end 18698.96534375
transcript.pyannote[3088].speaker SPEAKER_19
transcript.pyannote[3088].start 18700.07909375
transcript.pyannote[3088].end 18703.23471875
transcript.pyannote[3089].speaker SPEAKER_19
transcript.pyannote[3089].start 18703.99409375
transcript.pyannote[3089].end 18704.34846875
transcript.pyannote[3090].speaker SPEAKER_19
transcript.pyannote[3090].start 18705.05721875
transcript.pyannote[3090].end 18721.30784375
transcript.pyannote[3091].speaker SPEAKER_19
transcript.pyannote[3091].start 18721.96596875
transcript.pyannote[3091].end 18729.84659375
transcript.pyannote[3092].speaker SPEAKER_19
transcript.pyannote[3092].start 18730.21784375
transcript.pyannote[3092].end 18732.69846875
transcript.pyannote[3093].speaker SPEAKER_19
transcript.pyannote[3093].start 18733.47471875
transcript.pyannote[3093].end 18734.92596875
transcript.pyannote[3094].speaker SPEAKER_19
transcript.pyannote[3094].start 18735.53346875
transcript.pyannote[3094].end 18737.91284375
transcript.pyannote[3095].speaker SPEAKER_19
transcript.pyannote[3095].start 18738.57096875
transcript.pyannote[3095].end 18739.49909375
transcript.pyannote[3096].speaker SPEAKER_19
transcript.pyannote[3096].start 18740.07284375
transcript.pyannote[3096].end 18742.62096875
transcript.pyannote[3097].speaker SPEAKER_19
transcript.pyannote[3097].start 18743.22846875
transcript.pyannote[3097].end 18745.21971875
transcript.pyannote[3098].speaker SPEAKER_19
transcript.pyannote[3098].start 18745.52346875
transcript.pyannote[3098].end 18751.07534375
transcript.pyannote[3099].speaker SPEAKER_19
transcript.pyannote[3099].start 18751.09221875
transcript.pyannote[3099].end 18751.10909375
transcript.pyannote[3100].speaker SPEAKER_19
transcript.pyannote[3100].start 18751.19346875
transcript.pyannote[3100].end 18756.55971875
transcript.pyannote[3101].speaker SPEAKER_19
transcript.pyannote[3101].start 18757.18409375
transcript.pyannote[3101].end 18763.54596875
transcript.pyannote[3102].speaker SPEAKER_19
transcript.pyannote[3102].start 18763.83284375
transcript.pyannote[3102].end 18767.15721875
transcript.pyannote[3103].speaker SPEAKER_19
transcript.pyannote[3103].start 18767.98409375
transcript.pyannote[3103].end 18770.09346875
transcript.pyannote[3104].speaker SPEAKER_19
transcript.pyannote[3104].start 18770.80221875
transcript.pyannote[3104].end 18779.77971875
transcript.pyannote[3105].speaker SPEAKER_19
transcript.pyannote[3105].start 18779.91471875
transcript.pyannote[3105].end 18785.04471875
transcript.pyannote[3106].speaker SPEAKER_19
transcript.pyannote[3106].start 18785.56784375
transcript.pyannote[3106].end 18787.54221875
transcript.pyannote[3107].speaker SPEAKER_19
transcript.pyannote[3107].start 18788.13284375
transcript.pyannote[3107].end 18789.78659375
transcript.pyannote[3108].speaker SPEAKER_19
transcript.pyannote[3108].start 18789.80346875
transcript.pyannote[3108].end 18789.82034375
transcript.pyannote[3109].speaker SPEAKER_24
transcript.pyannote[3109].start 18789.82034375
transcript.pyannote[3109].end 18790.83284375
transcript.pyannote[3110].speaker SPEAKER_19
transcript.pyannote[3110].start 18790.49534375
transcript.pyannote[3110].end 18794.39346875
transcript.pyannote[3111].speaker SPEAKER_19
transcript.pyannote[3111].start 18794.57909375
transcript.pyannote[3111].end 18795.38909375
transcript.pyannote[3112].speaker SPEAKER_24
transcript.pyannote[3112].start 18794.68034375
transcript.pyannote[3112].end 18798.91596875
transcript.pyannote[3113].speaker SPEAKER_19
transcript.pyannote[3113].start 18797.78534375
transcript.pyannote[3113].end 18800.75534375
transcript.pyannote[3114].speaker SPEAKER_19
transcript.pyannote[3114].start 18802.12221875
transcript.pyannote[3114].end 18832.90221875
transcript.pyannote[3115].speaker SPEAKER_19
transcript.pyannote[3115].start 18833.17221875
transcript.pyannote[3115].end 18835.65284375
transcript.pyannote[3116].speaker SPEAKER_19
transcript.pyannote[3116].start 18837.10409375
transcript.pyannote[3116].end 18838.65659375
transcript.pyannote[3117].speaker SPEAKER_19
transcript.pyannote[3117].start 18839.07846875
transcript.pyannote[3117].end 18850.04721875
transcript.pyannote[3118].speaker SPEAKER_00
transcript.pyannote[3118].start 18843.01034375
transcript.pyannote[3118].end 18843.43221875
transcript.pyannote[3119].speaker SPEAKER_19
transcript.pyannote[3119].start 18850.26659375
transcript.pyannote[3119].end 18851.21159375
transcript.pyannote[3120].speaker SPEAKER_19
transcript.pyannote[3120].start 18852.24096875
transcript.pyannote[3120].end 18854.35034375
transcript.pyannote[3121].speaker SPEAKER_19
transcript.pyannote[3121].start 18854.60346875
transcript.pyannote[3121].end 18856.52721875
transcript.pyannote[3122].speaker SPEAKER_24
transcript.pyannote[3122].start 18855.59909375
transcript.pyannote[3122].end 18858.95721875
transcript.pyannote[3123].speaker SPEAKER_19
transcript.pyannote[3123].start 18857.84346875
transcript.pyannote[3123].end 18858.34971875
transcript.pyannote[3124].speaker SPEAKER_19
transcript.pyannote[3124].start 18858.61971875
transcript.pyannote[3124].end 18883.67909375
transcript.pyannote[3125].speaker SPEAKER_19
transcript.pyannote[3125].start 18883.96596875
transcript.pyannote[3125].end 18889.11284375
transcript.pyannote[3126].speaker SPEAKER_19
transcript.pyannote[3126].start 18889.53471875
transcript.pyannote[3126].end 18892.18409375
transcript.pyannote[3127].speaker SPEAKER_19
transcript.pyannote[3127].start 18892.72409375
transcript.pyannote[3127].end 18894.39471875
transcript.pyannote[3128].speaker SPEAKER_19
transcript.pyannote[3128].start 18894.69846875
transcript.pyannote[3128].end 18896.35221875
transcript.pyannote[3129].speaker SPEAKER_19
transcript.pyannote[3129].start 18896.67284375
transcript.pyannote[3129].end 18897.71909375
transcript.pyannote[3130].speaker SPEAKER_19
transcript.pyannote[3130].start 18898.15784375
transcript.pyannote[3130].end 18898.64721875
transcript.pyannote[3131].speaker SPEAKER_19
transcript.pyannote[3131].start 18899.17034375
transcript.pyannote[3131].end 18901.49909375
transcript.pyannote[3132].speaker SPEAKER_19
transcript.pyannote[3132].start 18901.80284375
transcript.pyannote[3132].end 18905.09346875
transcript.pyannote[3133].speaker SPEAKER_19
transcript.pyannote[3133].start 18905.53221875
transcript.pyannote[3133].end 18910.56096875
transcript.pyannote[3134].speaker SPEAKER_19
transcript.pyannote[3134].start 18910.74659375
transcript.pyannote[3134].end 18933.57846875
transcript.pyannote[3135].speaker SPEAKER_22
transcript.pyannote[3135].start 18933.88221875
transcript.pyannote[3135].end 18934.28721875
transcript.pyannote[3136].speaker SPEAKER_03
transcript.pyannote[3136].start 18938.75909375
transcript.pyannote[3136].end 18942.82596875
transcript.pyannote[3137].speaker SPEAKER_03
transcript.pyannote[3137].start 18950.57159375
transcript.pyannote[3137].end 18952.96784375
transcript.pyannote[3138].speaker SPEAKER_26
transcript.pyannote[3138].start 18952.71471875
transcript.pyannote[3138].end 18954.04784375
transcript.pyannote[3139].speaker SPEAKER_03
transcript.pyannote[3139].start 18953.10284375
transcript.pyannote[3139].end 18953.18721875
transcript.pyannote[3140].speaker SPEAKER_03
transcript.pyannote[3140].start 18953.23784375
transcript.pyannote[3140].end 18953.27159375
transcript.pyannote[3141].speaker SPEAKER_03
transcript.pyannote[3141].start 18953.35596875
transcript.pyannote[3141].end 18953.42346875
transcript.pyannote[3142].speaker SPEAKER_03
transcript.pyannote[3142].start 18953.65971875
transcript.pyannote[3142].end 18956.68034375
transcript.pyannote[3143].speaker SPEAKER_26
transcript.pyannote[3143].start 18956.39346875
transcript.pyannote[3143].end 18959.43096875
transcript.pyannote[3144].speaker SPEAKER_26
transcript.pyannote[3144].start 18960.71346875
transcript.pyannote[3144].end 18969.84284375
transcript.pyannote[3145].speaker SPEAKER_24
transcript.pyannote[3145].start 18960.76409375
transcript.pyannote[3145].end 18961.10159375
transcript.pyannote[3146].speaker SPEAKER_26
transcript.pyannote[3146].start 18970.07909375
transcript.pyannote[3146].end 18976.72784375
transcript.pyannote[3147].speaker SPEAKER_26
transcript.pyannote[3147].start 18976.99784375
transcript.pyannote[3147].end 18979.29284375
transcript.pyannote[3148].speaker SPEAKER_26
transcript.pyannote[3148].start 18979.74846875
transcript.pyannote[3148].end 18988.20284375
transcript.pyannote[3149].speaker SPEAKER_26
transcript.pyannote[3149].start 18988.62471875
transcript.pyannote[3149].end 18993.16409375
transcript.pyannote[3150].speaker SPEAKER_26
transcript.pyannote[3150].start 18993.67034375
transcript.pyannote[3150].end 19000.94346875
transcript.pyannote[3151].speaker SPEAKER_26
transcript.pyannote[3151].start 19001.38221875
transcript.pyannote[3151].end 19003.59284375
transcript.pyannote[3152].speaker SPEAKER_26
transcript.pyannote[3152].start 19003.96409375
transcript.pyannote[3152].end 19016.45159375
transcript.pyannote[3153].speaker SPEAKER_29
transcript.pyannote[3153].start 19014.08909375
transcript.pyannote[3153].end 19014.24096875
transcript.pyannote[3154].speaker SPEAKER_26
transcript.pyannote[3154].start 19017.26159375
transcript.pyannote[3154].end 19019.52284375
transcript.pyannote[3155].speaker SPEAKER_26
transcript.pyannote[3155].start 19020.97409375
transcript.pyannote[3155].end 19022.61096875
transcript.pyannote[3156].speaker SPEAKER_24
transcript.pyannote[3156].start 19023.21846875
transcript.pyannote[3156].end 19024.24784375
transcript.pyannote[3157].speaker SPEAKER_24
transcript.pyannote[3157].start 19024.63596875
transcript.pyannote[3157].end 19025.27721875
transcript.pyannote[3158].speaker SPEAKER_26
transcript.pyannote[3158].start 19024.77096875
transcript.pyannote[3158].end 19028.38221875
transcript.pyannote[3159].speaker SPEAKER_26
transcript.pyannote[3159].start 19032.33096875
transcript.pyannote[3159].end 19036.78596875
transcript.pyannote[3160].speaker SPEAKER_01
transcript.pyannote[3160].start 19038.28784375
transcript.pyannote[3160].end 19042.70909375
transcript.pyannote[3161].speaker SPEAKER_26
transcript.pyannote[3161].start 19039.57034375
transcript.pyannote[3161].end 19039.72221875
transcript.pyannote[3162].speaker SPEAKER_01
transcript.pyannote[3162].start 19043.01284375
transcript.pyannote[3162].end 19044.41346875
transcript.pyannote[3163].speaker SPEAKER_01
transcript.pyannote[3163].start 19044.93659375
transcript.pyannote[3163].end 19047.75471875
transcript.pyannote[3164].speaker SPEAKER_26
transcript.pyannote[3164].start 19047.58596875
transcript.pyannote[3164].end 19047.85596875
transcript.pyannote[3165].speaker SPEAKER_01
transcript.pyannote[3165].start 19047.85596875
transcript.pyannote[3165].end 19050.03284375
transcript.pyannote[3166].speaker SPEAKER_01
transcript.pyannote[3166].start 19050.53909375
transcript.pyannote[3166].end 19050.58971875
transcript.pyannote[3167].speaker SPEAKER_26
transcript.pyannote[3167].start 19050.58971875
transcript.pyannote[3167].end 19054.75784375
transcript.pyannote[3168].speaker SPEAKER_01
transcript.pyannote[3168].start 19050.60659375
transcript.pyannote[3168].end 19050.97784375
transcript.pyannote[3169].speaker SPEAKER_24
transcript.pyannote[3169].start 19054.75784375
transcript.pyannote[3169].end 19054.92659375
transcript.pyannote[3170].speaker SPEAKER_26
transcript.pyannote[3170].start 19054.97721875
transcript.pyannote[3170].end 19055.02784375
transcript.pyannote[3171].speaker SPEAKER_24
transcript.pyannote[3171].start 19055.02784375
transcript.pyannote[3171].end 19055.14596875
transcript.pyannote[3172].speaker SPEAKER_26
transcript.pyannote[3172].start 19055.14596875
transcript.pyannote[3172].end 19056.02346875
transcript.pyannote[3173].speaker SPEAKER_24
transcript.pyannote[3173].start 19056.02346875
transcript.pyannote[3173].end 19062.92534375
transcript.pyannote[3174].speaker SPEAKER_26
transcript.pyannote[3174].start 19061.23784375
transcript.pyannote[3174].end 19061.82846875
transcript.pyannote[3175].speaker SPEAKER_24
transcript.pyannote[3175].start 19062.97596875
transcript.pyannote[3175].end 19063.95471875
transcript.pyannote[3176].speaker SPEAKER_26
transcript.pyannote[3176].start 19063.16159375
transcript.pyannote[3176].end 19063.88721875
transcript.pyannote[3177].speaker SPEAKER_26
transcript.pyannote[3177].start 19063.95471875
transcript.pyannote[3177].end 19068.78096875
transcript.pyannote[3178].speaker SPEAKER_24
transcript.pyannote[3178].start 19068.78096875
transcript.pyannote[3178].end 19069.82721875
transcript.pyannote[3179].speaker SPEAKER_26
transcript.pyannote[3179].start 19069.57409375
transcript.pyannote[3179].end 19090.27971875
transcript.pyannote[3180].speaker SPEAKER_26
transcript.pyannote[3180].start 19091.15721875
transcript.pyannote[3180].end 19096.74284375
transcript.pyannote[3181].speaker SPEAKER_26
transcript.pyannote[3181].start 19098.27846875
transcript.pyannote[3181].end 19104.03284375
transcript.pyannote[3182].speaker SPEAKER_24
transcript.pyannote[3182].start 19104.04971875
transcript.pyannote[3182].end 19104.06659375
transcript.pyannote[3183].speaker SPEAKER_26
transcript.pyannote[3183].start 19104.06659375
transcript.pyannote[3183].end 19105.90596875
transcript.pyannote[3184].speaker SPEAKER_26
transcript.pyannote[3184].start 19106.15909375
transcript.pyannote[3184].end 19117.16159375
transcript.pyannote[3185].speaker SPEAKER_00
transcript.pyannote[3185].start 19110.24284375
transcript.pyannote[3185].end 19110.46221875
transcript.pyannote[3186].speaker SPEAKER_00
transcript.pyannote[3186].start 19111.01909375
transcript.pyannote[3186].end 19111.60971875
transcript.pyannote[3187].speaker SPEAKER_26
transcript.pyannote[3187].start 19117.75221875
transcript.pyannote[3187].end 19120.36784375
transcript.pyannote[3188].speaker SPEAKER_26
transcript.pyannote[3188].start 19120.55346875
transcript.pyannote[3188].end 19127.75909375
transcript.pyannote[3189].speaker SPEAKER_26
transcript.pyannote[3189].start 19128.02909375
transcript.pyannote[3189].end 19133.42909375
transcript.pyannote[3190].speaker SPEAKER_26
transcript.pyannote[3190].start 19133.71596875
transcript.pyannote[3190].end 19140.34784375
transcript.pyannote[3191].speaker SPEAKER_26
transcript.pyannote[3191].start 19140.80346875
transcript.pyannote[3191].end 19168.64721875
transcript.pyannote[3192].speaker SPEAKER_26
transcript.pyannote[3192].start 19168.83284375
transcript.pyannote[3192].end 19175.44784375
transcript.pyannote[3193].speaker SPEAKER_26
transcript.pyannote[3193].start 19175.83596875
transcript.pyannote[3193].end 19177.84409375
transcript.pyannote[3194].speaker SPEAKER_26
transcript.pyannote[3194].start 19178.24909375
transcript.pyannote[3194].end 19202.07659375
transcript.pyannote[3195].speaker SPEAKER_26
transcript.pyannote[3195].start 19202.38034375
transcript.pyannote[3195].end 19202.56596875
transcript.pyannote[3196].speaker SPEAKER_24
transcript.pyannote[3196].start 19203.00471875
transcript.pyannote[3196].end 19209.40034375
transcript.pyannote[3197].speaker SPEAKER_26
transcript.pyannote[3197].start 19209.04596875
transcript.pyannote[3197].end 19210.42971875
transcript.pyannote[3198].speaker SPEAKER_24
transcript.pyannote[3198].start 19210.07534375
transcript.pyannote[3198].end 19211.37471875
transcript.pyannote[3199].speaker SPEAKER_26
transcript.pyannote[3199].start 19211.37471875
transcript.pyannote[3199].end 19211.71221875
transcript.pyannote[3200].speaker SPEAKER_24
transcript.pyannote[3200].start 19211.47596875
transcript.pyannote[3200].end 19211.49284375
transcript.pyannote[3201].speaker SPEAKER_24
transcript.pyannote[3201].start 19211.71221875
transcript.pyannote[3201].end 19223.45721875
transcript.pyannote[3202].speaker SPEAKER_26
transcript.pyannote[3202].start 19211.72909375
transcript.pyannote[3202].end 19211.74596875
transcript.pyannote[3203].speaker SPEAKER_26
transcript.pyannote[3203].start 19214.02409375
transcript.pyannote[3203].end 19214.12534375
transcript.pyannote[3204].speaker SPEAKER_26
transcript.pyannote[3204].start 19218.00659375
transcript.pyannote[3204].end 19218.10784375
transcript.pyannote[3205].speaker SPEAKER_22
transcript.pyannote[3205].start 19218.10784375
transcript.pyannote[3205].end 19218.49596875
transcript.pyannote[3206].speaker SPEAKER_24
transcript.pyannote[3206].start 19224.48659375
transcript.pyannote[3206].end 19247.03159375
transcript.pyannote[3207].speaker SPEAKER_24
transcript.pyannote[3207].start 19247.31846875
transcript.pyannote[3207].end 19247.57159375
transcript.pyannote[3208].speaker SPEAKER_26
transcript.pyannote[3208].start 19248.01034375
transcript.pyannote[3208].end 19260.83534375
transcript.pyannote[3209].speaker SPEAKER_24
transcript.pyannote[3209].start 19261.94909375
transcript.pyannote[3209].end 19267.51784375
transcript.pyannote[3210].speaker SPEAKER_26
transcript.pyannote[3210].start 19264.34534375
transcript.pyannote[3210].end 19265.22284375
transcript.pyannote[3211].speaker SPEAKER_26
transcript.pyannote[3211].start 19267.51784375
transcript.pyannote[3211].end 19267.78784375
transcript.pyannote[3212].speaker SPEAKER_24
transcript.pyannote[3212].start 19267.78784375
transcript.pyannote[3212].end 19267.80471875
transcript.pyannote[3213].speaker SPEAKER_26
transcript.pyannote[3213].start 19267.80471875
transcript.pyannote[3213].end 19268.59784375
transcript.pyannote[3214].speaker SPEAKER_24
transcript.pyannote[3214].start 19268.59784375
transcript.pyannote[3214].end 19270.28534375
transcript.pyannote[3215].speaker SPEAKER_26
transcript.pyannote[3215].start 19268.61471875
transcript.pyannote[3215].end 19271.71971875
transcript.pyannote[3216].speaker SPEAKER_24
transcript.pyannote[3216].start 19272.12471875
transcript.pyannote[3216].end 19276.09034375
transcript.pyannote[3217].speaker SPEAKER_24
transcript.pyannote[3217].start 19276.36034375
transcript.pyannote[3217].end 19283.11034375
transcript.pyannote[3218].speaker SPEAKER_24
transcript.pyannote[3218].start 19283.24534375
transcript.pyannote[3218].end 19294.12971875
transcript.pyannote[3219].speaker SPEAKER_29
transcript.pyannote[3219].start 19283.32971875
transcript.pyannote[3219].end 19283.36346875
transcript.pyannote[3220].speaker SPEAKER_26
transcript.pyannote[3220].start 19294.41659375
transcript.pyannote[3220].end 19332.53721875
transcript.pyannote[3221].speaker SPEAKER_00
transcript.pyannote[3221].start 19304.27159375
transcript.pyannote[3221].end 19304.94659375
transcript.pyannote[3222].speaker SPEAKER_24
transcript.pyannote[3222].start 19314.12659375
transcript.pyannote[3222].end 19315.54409375
transcript.pyannote[3223].speaker SPEAKER_24
transcript.pyannote[3223].start 19318.36221875
transcript.pyannote[3223].end 19319.25659375
transcript.pyannote[3224].speaker SPEAKER_24
transcript.pyannote[3224].start 19319.99909375
transcript.pyannote[3224].end 19320.50534375
transcript.pyannote[3225].speaker SPEAKER_26
transcript.pyannote[3225].start 19333.33034375
transcript.pyannote[3225].end 19333.75221875
transcript.pyannote[3226].speaker SPEAKER_26
transcript.pyannote[3226].start 19334.07284375
transcript.pyannote[3226].end 19341.07596875
transcript.pyannote[3227].speaker SPEAKER_24
transcript.pyannote[3227].start 19341.07596875
transcript.pyannote[3227].end 19341.81846875
transcript.pyannote[3228].speaker SPEAKER_26
transcript.pyannote[3228].start 19341.81846875
transcript.pyannote[3228].end 19342.15596875
transcript.pyannote[3229].speaker SPEAKER_24
transcript.pyannote[3229].start 19342.56096875
transcript.pyannote[3229].end 19372.86846875
transcript.pyannote[3230].speaker SPEAKER_26
transcript.pyannote[3230].start 19350.03659375
transcript.pyannote[3230].end 19350.96471875
transcript.pyannote[3231].speaker SPEAKER_26
transcript.pyannote[3231].start 19351.58909375
transcript.pyannote[3231].end 19351.94346875
transcript.pyannote[3232].speaker SPEAKER_26
transcript.pyannote[3232].start 19356.58409375
transcript.pyannote[3232].end 19359.04784375
transcript.pyannote[3233].speaker SPEAKER_26
transcript.pyannote[3233].start 19372.64909375
transcript.pyannote[3233].end 19384.34346875
transcript.pyannote[3234].speaker SPEAKER_24
transcript.pyannote[3234].start 19374.80909375
transcript.pyannote[3234].end 19374.85971875
transcript.pyannote[3235].speaker SPEAKER_24
transcript.pyannote[3235].start 19376.10846875
transcript.pyannote[3235].end 19376.44596875
transcript.pyannote[3236].speaker SPEAKER_24
transcript.pyannote[3236].start 19379.38221875
transcript.pyannote[3236].end 19381.20471875
transcript.pyannote[3237].speaker SPEAKER_26
transcript.pyannote[3237].start 19384.83284375
transcript.pyannote[3237].end 19403.29409375
transcript.pyannote[3238].speaker SPEAKER_24
transcript.pyannote[3238].start 19399.88534375
transcript.pyannote[3238].end 19399.90221875
transcript.pyannote[3239].speaker SPEAKER_03
transcript.pyannote[3239].start 19399.90221875
transcript.pyannote[3239].end 19402.51784375
transcript.pyannote[3240].speaker SPEAKER_03
transcript.pyannote[3240].start 19404.55971875
transcript.pyannote[3240].end 19405.43721875
transcript.pyannote[3241].speaker SPEAKER_03
transcript.pyannote[3241].start 19405.79159375
transcript.pyannote[3241].end 19405.85909375
transcript.pyannote[3242].speaker SPEAKER_03
transcript.pyannote[3242].start 19408.79534375
transcript.pyannote[3242].end 19411.22534375
transcript.pyannote[3243].speaker SPEAKER_08
transcript.pyannote[3243].start 19421.18159375
transcript.pyannote[3243].end 19423.84784375
transcript.pyannote[3244].speaker SPEAKER_03
transcript.pyannote[3244].start 19423.84784375
transcript.pyannote[3244].end 19424.47221875
transcript.pyannote[3245].speaker SPEAKER_03
transcript.pyannote[3245].start 19429.55159375
transcript.pyannote[3245].end 19430.10846875
transcript.pyannote[3246].speaker SPEAKER_22
transcript.pyannote[3246].start 19430.10846875
transcript.pyannote[3246].end 19430.12534375
transcript.pyannote[3247].speaker SPEAKER_08
transcript.pyannote[3247].start 19430.34471875
transcript.pyannote[3247].end 19436.18346875
transcript.pyannote[3248].speaker SPEAKER_24
transcript.pyannote[3248].start 19437.48284375
transcript.pyannote[3248].end 19438.54596875
transcript.pyannote[3249].speaker SPEAKER_24
transcript.pyannote[3249].start 19438.91721875
transcript.pyannote[3249].end 19441.09409375
transcript.pyannote[3250].speaker SPEAKER_08
transcript.pyannote[3250].start 19441.19534375
transcript.pyannote[3250].end 19443.03471875
transcript.pyannote[3251].speaker SPEAKER_08
transcript.pyannote[3251].start 19443.49034375
transcript.pyannote[3251].end 19444.75596875
transcript.pyannote[3252].speaker SPEAKER_08
transcript.pyannote[3252].start 19445.41409375
transcript.pyannote[3252].end 19460.68596875
transcript.pyannote[3253].speaker SPEAKER_08
transcript.pyannote[3253].start 19461.71534375
transcript.pyannote[3253].end 19468.71846875
transcript.pyannote[3254].speaker SPEAKER_08
transcript.pyannote[3254].start 19469.14034375
transcript.pyannote[3254].end 19481.59409375
transcript.pyannote[3255].speaker SPEAKER_29
transcript.pyannote[3255].start 19475.67096875
transcript.pyannote[3255].end 19476.37971875
transcript.pyannote[3256].speaker SPEAKER_08
transcript.pyannote[3256].start 19482.33659375
transcript.pyannote[3256].end 19486.52159375
transcript.pyannote[3257].speaker SPEAKER_08
transcript.pyannote[3257].start 19486.67346875
transcript.pyannote[3257].end 19505.64096875
transcript.pyannote[3258].speaker SPEAKER_08
transcript.pyannote[3258].start 19506.18096875
transcript.pyannote[3258].end 19513.90971875
transcript.pyannote[3259].speaker SPEAKER_08
transcript.pyannote[3259].start 19514.17971875
transcript.pyannote[3259].end 19547.62596875
transcript.pyannote[3260].speaker SPEAKER_08
transcript.pyannote[3260].start 19548.68909375
transcript.pyannote[3260].end 19560.90659375
transcript.pyannote[3261].speaker SPEAKER_24
transcript.pyannote[3261].start 19562.56034375
transcript.pyannote[3261].end 19563.20159375
transcript.pyannote[3262].speaker SPEAKER_08
transcript.pyannote[3262].start 19563.52221875
transcript.pyannote[3262].end 19564.19721875
transcript.pyannote[3263].speaker SPEAKER_24
transcript.pyannote[3263].start 19563.80909375
transcript.pyannote[3263].end 19566.00284375
transcript.pyannote[3264].speaker SPEAKER_08
transcript.pyannote[3264].start 19564.65284375
transcript.pyannote[3264].end 19564.82159375
transcript.pyannote[3265].speaker SPEAKER_08
transcript.pyannote[3265].start 19566.23909375
transcript.pyannote[3265].end 19571.53784375
transcript.pyannote[3266].speaker SPEAKER_24
transcript.pyannote[3266].start 19571.18346875
transcript.pyannote[3266].end 19571.62221875
transcript.pyannote[3267].speaker SPEAKER_08
transcript.pyannote[3267].start 19571.62221875
transcript.pyannote[3267].end 19571.75721875
transcript.pyannote[3268].speaker SPEAKER_24
transcript.pyannote[3268].start 19573.32659375
transcript.pyannote[3268].end 19575.97596875
transcript.pyannote[3269].speaker SPEAKER_08
transcript.pyannote[3269].start 19575.41909375
transcript.pyannote[3269].end 19578.60846875
transcript.pyannote[3270].speaker SPEAKER_24
transcript.pyannote[3270].start 19579.60409375
transcript.pyannote[3270].end 19580.07659375
transcript.pyannote[3271].speaker SPEAKER_24
transcript.pyannote[3271].start 19580.92034375
transcript.pyannote[3271].end 19588.58159375
transcript.pyannote[3272].speaker SPEAKER_08
transcript.pyannote[3272].start 19588.44659375
transcript.pyannote[3272].end 19589.74596875
transcript.pyannote[3273].speaker SPEAKER_24
transcript.pyannote[3273].start 19589.00346875
transcript.pyannote[3273].end 19609.06784375
transcript.pyannote[3274].speaker SPEAKER_08
transcript.pyannote[3274].start 19591.19721875
transcript.pyannote[3274].end 19591.56846875
transcript.pyannote[3275].speaker SPEAKER_08
transcript.pyannote[3275].start 19596.42846875
transcript.pyannote[3275].end 19596.61409375
transcript.pyannote[3276].speaker SPEAKER_00
transcript.pyannote[3276].start 19596.61409375
transcript.pyannote[3276].end 19596.64784375
transcript.pyannote[3277].speaker SPEAKER_00
transcript.pyannote[3277].start 19597.91346875
transcript.pyannote[3277].end 19599.02721875
transcript.pyannote[3278].speaker SPEAKER_22
transcript.pyannote[3278].start 19599.02721875
transcript.pyannote[3278].end 19599.87096875
transcript.pyannote[3279].speaker SPEAKER_24
transcript.pyannote[3279].start 19609.30409375
transcript.pyannote[3279].end 19633.19909375
transcript.pyannote[3280].speaker SPEAKER_00
transcript.pyannote[3280].start 19622.34846875
transcript.pyannote[3280].end 19622.71971875
transcript.pyannote[3281].speaker SPEAKER_24
transcript.pyannote[3281].start 19633.51971875
transcript.pyannote[3281].end 19638.27846875
transcript.pyannote[3282].speaker SPEAKER_24
transcript.pyannote[3282].start 19638.76784375
transcript.pyannote[3282].end 19645.12971875
transcript.pyannote[3283].speaker SPEAKER_08
transcript.pyannote[3283].start 19641.41721875
transcript.pyannote[3283].end 19641.77159375
transcript.pyannote[3284].speaker SPEAKER_08
transcript.pyannote[3284].start 19645.18034375
transcript.pyannote[3284].end 19648.70721875
transcript.pyannote[3285].speaker SPEAKER_08
transcript.pyannote[3285].start 19649.58471875
transcript.pyannote[3285].end 19660.24971875
transcript.pyannote[3286].speaker SPEAKER_08
transcript.pyannote[3286].start 19660.68846875
transcript.pyannote[3286].end 19675.21784375
transcript.pyannote[3287].speaker SPEAKER_08
transcript.pyannote[3287].start 19675.62284375
transcript.pyannote[3287].end 19685.46096875
transcript.pyannote[3288].speaker SPEAKER_08
transcript.pyannote[3288].start 19685.59596875
transcript.pyannote[3288].end 19701.81284375
transcript.pyannote[3289].speaker SPEAKER_24
transcript.pyannote[3289].start 19702.90971875
transcript.pyannote[3289].end 19704.00659375
transcript.pyannote[3290].speaker SPEAKER_24
transcript.pyannote[3290].start 19704.19221875
transcript.pyannote[3290].end 19708.41096875
transcript.pyannote[3291].speaker SPEAKER_24
transcript.pyannote[3291].start 19708.76534375
transcript.pyannote[3291].end 19709.64284375
transcript.pyannote[3292].speaker SPEAKER_24
transcript.pyannote[3292].start 19709.98034375
transcript.pyannote[3292].end 19716.42659375
transcript.pyannote[3293].speaker SPEAKER_22
transcript.pyannote[3293].start 19715.66721875
transcript.pyannote[3293].end 19715.97096875
transcript.pyannote[3294].speaker SPEAKER_00
transcript.pyannote[3294].start 19715.97096875
transcript.pyannote[3294].end 19716.03846875
transcript.pyannote[3295].speaker SPEAKER_24
transcript.pyannote[3295].start 19716.59534375
transcript.pyannote[3295].end 19717.43909375
transcript.pyannote[3296].speaker SPEAKER_24
transcript.pyannote[3296].start 19717.87784375
transcript.pyannote[3296].end 19730.85471875
transcript.pyannote[3297].speaker SPEAKER_00
transcript.pyannote[3297].start 19725.08346875
transcript.pyannote[3297].end 19725.45471875
transcript.pyannote[3298].speaker SPEAKER_00
transcript.pyannote[3298].start 19726.46721875
transcript.pyannote[3298].end 19726.90596875
transcript.pyannote[3299].speaker SPEAKER_24
transcript.pyannote[3299].start 19731.05721875
transcript.pyannote[3299].end 19738.92096875
transcript.pyannote[3300].speaker SPEAKER_24
transcript.pyannote[3300].start 19739.05596875
transcript.pyannote[3300].end 19742.36346875
transcript.pyannote[3301].speaker SPEAKER_24
transcript.pyannote[3301].start 19742.65034375
transcript.pyannote[3301].end 19743.61221875
transcript.pyannote[3302].speaker SPEAKER_24
transcript.pyannote[3302].start 19743.98346875
transcript.pyannote[3302].end 19760.94284375
transcript.pyannote[3303].speaker SPEAKER_08
transcript.pyannote[3303].start 19761.34784375
transcript.pyannote[3303].end 19779.64034375
transcript.pyannote[3304].speaker SPEAKER_08
transcript.pyannote[3304].start 19781.22659375
transcript.pyannote[3304].end 19782.86346875
transcript.pyannote[3305].speaker SPEAKER_24
transcript.pyannote[3305].start 19783.36971875
transcript.pyannote[3305].end 19783.87596875
transcript.pyannote[3306].speaker SPEAKER_24
transcript.pyannote[3306].start 19784.17971875
transcript.pyannote[3306].end 19786.47471875
transcript.pyannote[3307].speaker SPEAKER_24
transcript.pyannote[3307].start 19786.98096875
transcript.pyannote[3307].end 19788.29721875
transcript.pyannote[3308].speaker SPEAKER_08
transcript.pyannote[3308].start 19788.14534375
transcript.pyannote[3308].end 19795.41846875
transcript.pyannote[3309].speaker SPEAKER_08
transcript.pyannote[3309].start 19795.80659375
transcript.pyannote[3309].end 19797.96659375
transcript.pyannote[3310].speaker SPEAKER_24
transcript.pyannote[3310].start 19797.61221875
transcript.pyannote[3310].end 19801.51034375
transcript.pyannote[3311].speaker SPEAKER_08
transcript.pyannote[3311].start 19801.51034375
transcript.pyannote[3311].end 19806.52221875
transcript.pyannote[3312].speaker SPEAKER_24
transcript.pyannote[3312].start 19806.31971875
transcript.pyannote[3312].end 19808.47971875
transcript.pyannote[3313].speaker SPEAKER_24
transcript.pyannote[3313].start 19808.56409375
transcript.pyannote[3313].end 19809.98159375
transcript.pyannote[3314].speaker SPEAKER_08
transcript.pyannote[3314].start 19810.03221875
transcript.pyannote[3314].end 19812.91784375
transcript.pyannote[3315].speaker SPEAKER_24
transcript.pyannote[3315].start 19812.91784375
transcript.pyannote[3315].end 19813.03596875
transcript.pyannote[3316].speaker SPEAKER_08
transcript.pyannote[3316].start 19813.03596875
transcript.pyannote[3316].end 19813.15409375
transcript.pyannote[3317].speaker SPEAKER_08
transcript.pyannote[3317].start 19813.42409375
transcript.pyannote[3317].end 19815.61784375
transcript.pyannote[3318].speaker SPEAKER_08
transcript.pyannote[3318].start 19816.61346875
transcript.pyannote[3318].end 19817.37284375
transcript.pyannote[3319].speaker SPEAKER_24
transcript.pyannote[3319].start 19816.64721875
transcript.pyannote[3319].end 19819.63409375
transcript.pyannote[3320].speaker SPEAKER_24
transcript.pyannote[3320].start 19820.47784375
transcript.pyannote[3320].end 19823.81909375
transcript.pyannote[3321].speaker SPEAKER_08
transcript.pyannote[3321].start 19823.66721875
transcript.pyannote[3321].end 19840.60971875
transcript.pyannote[3322].speaker SPEAKER_08
transcript.pyannote[3322].start 19841.89221875
transcript.pyannote[3322].end 19857.67034375
transcript.pyannote[3323].speaker SPEAKER_08
transcript.pyannote[3323].start 19857.70409375
transcript.pyannote[3323].end 19857.78846875
transcript.pyannote[3324].speaker SPEAKER_08
transcript.pyannote[3324].start 19857.87284375
transcript.pyannote[3324].end 19919.01096875
transcript.pyannote[3325].speaker SPEAKER_08
transcript.pyannote[3325].start 19919.75346875
transcript.pyannote[3325].end 19935.46409375
transcript.pyannote[3326].speaker SPEAKER_24
transcript.pyannote[3326].start 19936.27409375
transcript.pyannote[3326].end 19945.60596875
transcript.pyannote[3327].speaker SPEAKER_08
transcript.pyannote[3327].start 19936.30784375
transcript.pyannote[3327].end 19936.47659375
transcript.pyannote[3328].speaker SPEAKER_08
transcript.pyannote[3328].start 19938.01221875
transcript.pyannote[3328].end 19938.09659375
transcript.pyannote[3329].speaker SPEAKER_24
transcript.pyannote[3329].start 19946.14596875
transcript.pyannote[3329].end 19948.47471875
transcript.pyannote[3330].speaker SPEAKER_24
transcript.pyannote[3330].start 19949.03159375
transcript.pyannote[3330].end 19962.04221875
transcript.pyannote[3331].speaker SPEAKER_22
transcript.pyannote[3331].start 19949.92596875
transcript.pyannote[3331].end 19950.24659375
transcript.pyannote[3332].speaker SPEAKER_08
transcript.pyannote[3332].start 19962.04221875
transcript.pyannote[3332].end 19964.47221875
transcript.pyannote[3333].speaker SPEAKER_24
transcript.pyannote[3333].start 19962.05909375
transcript.pyannote[3333].end 19962.07596875
transcript.pyannote[3334].speaker SPEAKER_24
transcript.pyannote[3334].start 19964.45534375
transcript.pyannote[3334].end 19966.05846875
transcript.pyannote[3335].speaker SPEAKER_24
transcript.pyannote[3335].start 19966.85159375
transcript.pyannote[3335].end 19967.93159375
transcript.pyannote[3336].speaker SPEAKER_08
transcript.pyannote[3336].start 19968.03284375
transcript.pyannote[3336].end 19978.47846875
transcript.pyannote[3337].speaker SPEAKER_24
transcript.pyannote[3337].start 19968.69096875
transcript.pyannote[3337].end 19969.07909375
transcript.pyannote[3338].speaker SPEAKER_24
transcript.pyannote[3338].start 19977.90471875
transcript.pyannote[3338].end 19980.21659375
transcript.pyannote[3339].speaker SPEAKER_08
transcript.pyannote[3339].start 19979.60909375
transcript.pyannote[3339].end 19981.17846875
transcript.pyannote[3340].speaker SPEAKER_24
transcript.pyannote[3340].start 19981.17846875
transcript.pyannote[3340].end 19992.06284375
transcript.pyannote[3341].speaker SPEAKER_08
transcript.pyannote[3341].start 19982.02221875
transcript.pyannote[3341].end 19982.47784375
transcript.pyannote[3342].speaker SPEAKER_08
transcript.pyannote[3342].start 19984.85721875
transcript.pyannote[3342].end 19985.83596875
transcript.pyannote[3343].speaker SPEAKER_29
transcript.pyannote[3343].start 19985.83596875
transcript.pyannote[3343].end 19985.88659375
transcript.pyannote[3344].speaker SPEAKER_08
transcript.pyannote[3344].start 19986.46034375
transcript.pyannote[3344].end 19986.76409375
transcript.pyannote[3345].speaker SPEAKER_29
transcript.pyannote[3345].start 19986.76409375
transcript.pyannote[3345].end 19986.89909375
transcript.pyannote[3346].speaker SPEAKER_08
transcript.pyannote[3346].start 19987.96221875
transcript.pyannote[3346].end 19987.97909375
transcript.pyannote[3347].speaker SPEAKER_29
transcript.pyannote[3347].start 19987.97909375
transcript.pyannote[3347].end 19988.38409375
transcript.pyannote[3348].speaker SPEAKER_29
transcript.pyannote[3348].start 19991.53971875
transcript.pyannote[3348].end 19991.92784375
transcript.pyannote[3349].speaker SPEAKER_29
transcript.pyannote[3349].start 19992.04596875
transcript.pyannote[3349].end 19992.45096875
transcript.pyannote[3350].speaker SPEAKER_24
transcript.pyannote[3350].start 19992.61971875
transcript.pyannote[3350].end 20010.77721875
transcript.pyannote[3351].speaker SPEAKER_29
transcript.pyannote[3351].start 19995.52221875
transcript.pyannote[3351].end 19996.01159375
transcript.pyannote[3352].speaker SPEAKER_29
transcript.pyannote[3352].start 19996.97346875
transcript.pyannote[3352].end 19997.51346875
transcript.pyannote[3353].speaker SPEAKER_08
transcript.pyannote[3353].start 20010.87846875
transcript.pyannote[3353].end 20039.31284375
transcript.pyannote[3354].speaker SPEAKER_24
transcript.pyannote[3354].start 20039.31284375
transcript.pyannote[3354].end 20044.27409375
transcript.pyannote[3355].speaker SPEAKER_24
transcript.pyannote[3355].start 20044.52721875
transcript.pyannote[3355].end 20055.39471875
transcript.pyannote[3356].speaker SPEAKER_08
transcript.pyannote[3356].start 20055.15846875
transcript.pyannote[3356].end 20058.73596875
transcript.pyannote[3357].speaker SPEAKER_24
transcript.pyannote[3357].start 20058.73596875
transcript.pyannote[3357].end 20059.27596875
transcript.pyannote[3358].speaker SPEAKER_03
transcript.pyannote[3358].start 20062.78596875
transcript.pyannote[3358].end 20063.59596875
transcript.pyannote[3359].speaker SPEAKER_03
transcript.pyannote[3359].start 20063.96721875
transcript.pyannote[3359].end 20067.52784375
transcript.pyannote[3360].speaker SPEAKER_03
transcript.pyannote[3360].start 20067.98346875
transcript.pyannote[3360].end 20071.13909375
transcript.pyannote[3361].speaker SPEAKER_03
transcript.pyannote[3361].start 20071.69596875
transcript.pyannote[3361].end 20074.80096875
transcript.pyannote[3362].speaker SPEAKER_03
transcript.pyannote[3362].start 20076.01596875
transcript.pyannote[3362].end 20077.88909375
transcript.pyannote[3363].speaker SPEAKER_03
transcript.pyannote[3363].start 20078.41221875
transcript.pyannote[3363].end 20080.75784375
transcript.pyannote[3364].speaker SPEAKER_03
transcript.pyannote[3364].start 20081.09534375
transcript.pyannote[3364].end 20082.54659375
transcript.pyannote[3365].speaker SPEAKER_03
transcript.pyannote[3365].start 20082.76596875
transcript.pyannote[3365].end 20084.26784375
transcript.pyannote[3366].speaker SPEAKER_03
transcript.pyannote[3366].start 20084.58846875
transcript.pyannote[3366].end 20086.12409375
transcript.pyannote[3367].speaker SPEAKER_03
transcript.pyannote[3367].start 20086.52909375
transcript.pyannote[3367].end 20091.03471875
transcript.pyannote[3368].speaker SPEAKER_03
transcript.pyannote[3368].start 20091.35534375
transcript.pyannote[3368].end 20092.99221875
transcript.pyannote[3369].speaker SPEAKER_03
transcript.pyannote[3369].start 20093.34659375
transcript.pyannote[3369].end 20094.20721875
transcript.pyannote[3370].speaker SPEAKER_03
transcript.pyannote[3370].start 20094.94971875
transcript.pyannote[3370].end 20097.68346875
transcript.pyannote[3371].speaker SPEAKER_03
transcript.pyannote[3371].start 20098.08846875
transcript.pyannote[3371].end 20099.94471875
transcript.whisperx[0].start 1639.352
transcript.whisperx[0].end 1643.739
transcript.whisperx[0].text 報告委員會出席委員人數11人已足法定人數請主席宣布開會
transcript.whisperx[1].start 1646.052
transcript.whisperx[1].end 1672.97
transcript.whisperx[1].text 好現在開會請議事人員宣讀上次會議議事錄立法院第十一屆第四會期社會福利及衛生環境委員會第八次全體委員會議議事錄時間一百二十四年十一月五日星期三九時三分至十五時十六分地點群憲樓八零一會議室出席委員陳委員昭姿等十五人列席委員羅委員廷維等十六人列席官員環境部部長彭啟明等相關人員主席廖兆吉委員韋祥
transcript.whisperx[2].start 1673.65
transcript.whisperx[2].end 1689.358
transcript.whisperx[2].text 報告事項宣讀上次會議議事錄決定確定邀請環境部部長經濟部內政部農業部交通部行政院公共工程委員會就非法棄置到城市採礦檢討環境部環境管理署執法痛點與城市採礦推動策略進行專題報告並被質詢
transcript.whisperx[3].start 1692.8
transcript.whisperx[3].end 1708.103
transcript.whisperx[3].text 本日會議由環境部部長報告後委員陳昭資等17人提出質詢軍經環境部部長農業部次長黃昭清經濟部主任秘書莊明池及內政部國土管理署總工程司由袁順暨各相關主管等及其答覆
transcript.whisperx[4].start 1708.624
transcript.whisperx[4].end 1736.716
transcript.whisperx[4].text 委員如現已所提書面諮詢列入記錄刊登公報決定一報告及詢答完畢二委員諮詢未及答覆或請補充資料者請相關機關於二週內書面答覆委員另要求期限者從期鎖定討論事項繼續審查噪音管制法第二條第26條及第28條條文修正草案計九案及審查噪音管制法第二條第26條及第28條條文修正草案計三案本次會議由委員提出修正動議二案
transcript.whisperx[5].start 1737.756
transcript.whisperx[5].end 1764.511
transcript.whisperx[5].text 決議一 噪音管制法第二條第二十六條及第二十八條條文修正草案等十二案審查完略內容如審查結果並案擬據審查報告提報院會討論 院會討論時由廖兆及委員韋翔補充說明不需交黨團協商二 本法案相關立法說明授權行政單位提供審查結果第二條 趙委員 牛許廷等二十五人委員廖韋翔等十六人提案通過
transcript.whisperx[6].start 1765.672
transcript.whisperx[6].end 1782.329
transcript.whisperx[6].text 第26條 趙委員 羅明才等20人提案及盧憲 及委員盧憲一 陳昭資 廖偉祥 牛許廷等4人所提修正動議修正通過第28條 趙委員 羅廷維等17人提案修正通過通過附帶決議一項 宣讀完畢好 請問委員會 上次議事錄有錯誤或遺漏之處
transcript.whisperx[7].start 1789.946
transcript.whisperx[7].end 1815.553
transcript.whisperx[7].text 沒有 那就意思就確定 謝謝 那本會議一成為邀請勞動部部長列席報告業務概況並備質詢那現在介紹在場委員及列席官員第一位是陳昭志陳委員林月琦林委員王振旭王委員初期官員是勞動部部長洪森翰
transcript.whisperx[8].start 1818.767
transcript.whisperx[8].end 1839.494
transcript.whisperx[8].text 勞動力發展署署長黃玲玉勞工保險局局長白立珍勞動基金運用局局長蘇玉清職業安全衛生署署長林益棠還有勞動及職業安全衛生研究所所長王厚誠莊規司司長莊美娟勞動關係司司長王厚偉勞動保險司司長陳美女
transcript.whisperx[9].start 1848.608
transcript.whisperx[9].end 1858.532
transcript.whisperx[9].text 勞動扶持退休師 司長黃維生勞動條件級就業評審師 司長黃奇亞勞動法務司 司長傅惠芝秘書處 處長丁玉珍人事處 處長江碧玲政風處 處長周志信會計處 處長林美信
transcript.whisperx[10].start 1877.822
transcript.whisperx[10].end 1894.531
transcript.whisperx[10].text 統計處處長梅家園資訊處副處長曾斐瑜還有傳統法人職業災害預防及重建中心執行長李伯昌好 接下來請勞動部洪部長來做報告
transcript.whisperx[11].start 1906.99
transcript.whisperx[11].end 1929.058
transcript.whisperx[11].text 主席 各位委員先進 包括各位記者朋友大家好今天很榮幸在本會請提出這個業務報告所以今天報告的內容主要會分為三個部分將就整體的勞動情勢跟近期的重點業務還有本年度施政計劃執行內容及展望來進行報告首先從整體的勞動情勢來分析
transcript.whisperx[12].start 1929.938
transcript.whisperx[12].end 1956.764
transcript.whisperx[12].text 那就劳动参与的概况在114年度1至9月劳动人力人数达到1200万是1202万4000人叫前一年同期增加26000人劳动力参与率年提升0.11个百分点就人数116点1111162点1万人叫同期增加3万人失业率下降0.04个百分点
transcript.whisperx[13].start 1957.523
transcript.whisperx[13].end 1971.336
transcript.whisperx[13].text 那勞動參與率的部分女性為52.05%男性為67.20%男女差距較同期率略增0.04個百分點那薪資概況分析經常性薪資114年1-9月較113年同期增加3%為47751元
transcript.whisperx[14].start 1980.525
transcript.whisperx[14].end 1991.611
transcript.whisperx[14].text 接著就本部進行推動幾項重點工作進行說明為因應美國關稅政策我們持續主動訪視工會建立管道就可能受衝擊關稅衝擊的產業和工會團體持續主動的訪視和收集意見並陸續提出
transcript.whisperx[15].start 1997.074
transcript.whisperx[15].end 2021.084
transcript.whisperx[15].text 各項協助勞工朋友的措施包括強化公安定措施減班休息再充電計劃支持受影響企業規劃辦理訓練支援青年就業計劃以及9月30號發布的勞工就業通計劃近期我國也因為天然災害造成人民重大損害因此本部立刻啟動災後就業協助措施不僅提供臨時就業機會
transcript.whisperx[16].start 2022.564
transcript.whisperx[16].end 2044.465
transcript.whisperx[16].text 协助灾区民众安置更投入职训与防护工作以实际行动支持灾区重建防护工作颁布因应灾后石棉屋瓦浪板拆除清理作业危害预防处理原则并购置个人防护包发送灾区作业人员使用同时设立灾后重建防护指挥所
transcript.whisperx[17].start 2045.413
transcript.whisperx[17].end 2070.51
transcript.whisperx[17].text 防护服务站以及职业安全卫生辅导团主动深入灾区办理实棉拆除危害预防辅导及提供咨询协助而社会高度关注的职场霸凌问题本部除了修正发布执行职务遭受不法侵害预防指引的第4版那来强化雇主调查及处理机制提供事业单位定定预防计划并具以执行之外
transcript.whisperx[18].start 2071.294
transcript.whisperx[18].end 2089.335
transcript.whisperx[18].text 为了完善职场霸凌的申诉调查已经处于机制以及强化保护劳工身心健康我们在职安法增订了职场霸凌防治专章并经贵人会审议完据后续我们会积极研修相关附属法规以规划配套措施等以配合法令公布执行
transcript.whisperx[19].start 2090.095
transcript.whisperx[19].end 2104.226
transcript.whisperx[19].text 另一方面因應就業服務法第46條修正放寬80歲免貧推動降低重症家庭衝擊配套措施為了避免市場供需失衡導致器重則輕的現象加劇自114年8月1號起本部與衛福部建立
transcript.whisperx[20].start 2105.7
transcript.whisperx[20].end 2126.983
transcript.whisperx[20].text 重症加勤申请看护移工分流制度采取跨部会合作轻重分流且重症优先之处理机制令本部也同步扩大重症对象多元免贫认定资格落实检证辩明而为使青壮年劳工谭姓育儿照顾不离职本部也推动育婴留庭照顾谭姓化的新制
transcript.whisperx[21].start 2127.483
transcript.whisperx[21].end 2145.61
transcript.whisperx[21].text 薪資內容主要為育嬰留職停薪以日申請以及家庭照顧假以小時計那正在辦理相應的制度與措施預計在115年1月1號上路此外我們也規劃辦理勞工生育補助方案本國籍
transcript.whisperx[22].start 2146.553
transcript.whisperx[22].end 2164.129
transcript.whisperx[22].text 女性老保被保险人生育可请领老保生育给付加计生育补助合计每胎10万元双生以上依比例增给预计于115年1月1号开办实施那为了保障外送人权益本部借由跨部会合作的机会
transcript.whisperx[23].start 2164.844
transcript.whisperx[23].end 2181.258
transcript.whisperx[23].text 推动外送员权益保障及外送平台管理研拟专法与规范并由各部会依权责分工就外送员消费者合作商家及外送平台的各方权益义务与保障及管理将尽速完成相关法制作业
transcript.whisperx[24].start 2181.718
transcript.whisperx[24].end 2201.11
transcript.whisperx[24].text 而有关推动跨国劳动力精进方案在本国劳工优先外国人权益保障的原则之下以本国劳工加薪为前提增加移工名额放宽留用资深移工并精进旅宿及商港码头业引进外国技术能力的措施同时也将设跨国劳动力延展中心来强化政府的效能
transcript.whisperx[25].start 2201.81
transcript.whisperx[25].end 2231.014
transcript.whisperx[25].text 这些近期推动的重点工作与民众切身权益密切相关本部以谨慎务实的态度研理对策体察民情苦民所苦并积极推动各项解决措施致力回应民众需求那接下来也向各位委员报告114年的施政内容与展望有关最低工资本部已经在114年9月26号召开最低工资审议会由劳资学政四方委员共同讨论决定从115年1月1号起
transcript.whisperx[26].start 2231.909
transcript.whisperx[26].end 2258.069
transcript.whisperx[26].text 每月最低工资由28590元调整至29500元调升910元调幅3.18%每小时由最低工资190元调升到196元那本次的调升预估有247万名劳工受惠那在推动友善职场环境维护工作平权方面持续补助企业设置补给入室
transcript.whisperx[27].start 2258.789
transcript.whisperx[27].end 2278.566
transcript.whisperx[27].text 托兒設施或措施並補助企業推動工作生活平衡措施共同協助企業支持員工平衡工作與家庭照顧而為加強宣導職場平權消除懷孕歧視本部也透過與衛福部的合作提供孕媽咪懷孕歧視相關資訊與申訴窗口
transcript.whisperx[28].start 2281.741
transcript.whisperx[28].end 2303.758
transcript.whisperx[28].text 运用多元方式提升雇主禁止怀孕就业歧视的法尊能力在攸关劳工权益的劳保及退休金制度方面我们持续检讨与修正相关法规落实年金法制以保障劳工朋友的保险给付权益同时为稳定维持基金税位除了借由拨补和多元基金投资运用外
transcript.whisperx[29].start 2304.659
transcript.whisperx[29].end 2331.808
transcript.whisperx[29].text 并依据疫后特别条例额外编列300亿元的特别预算役注自109年起总计7年编列5070亿元截至114年9月底劳工保险基金累存余额为1兆2484亿余元未来政府将持续办理拨补来确保制度的稳健运作而劳退救治的足额提拨率已达99.39%
transcript.whisperx[30].start 2334.969
transcript.whisperx[30].end 2340.658
transcript.whisperx[30].text 勞動基金投資方面截至124年9月勞動基金運用規模為7兆4399億元累積收益數達3兆6387億元
transcript.whisperx[31].start 2349.489
transcript.whisperx[31].end 2368.317
transcript.whisperx[31].text 為了提升勞動力參與在促進就業與人才培育方面本部針對不同族群推動多元措施例如婦女在就業計劃強化運用自主訓練獎勵在就業獎勵雇主工時調整獎勵等獎勵措施並持續落實中高齡者及高齡者就業促進法而
transcript.whisperx[32].start 2369.077
transcript.whisperx[32].end 2395.275
transcript.whisperx[32].text 青年就业方案的推动统合了11个部会的资源本部推动包括工作岗位训练初次循职青年稳定就业等措施另一方面我们也透过多元资讯管道提升劳工的就业技能并配合国家重点产业发展办理重点产业人才职训同时11月我国将主办第三届的亚洲技能竞赛届时将有28个国家超过300名的选手参加
transcript.whisperx[33].start 2398.977
transcript.whisperx[33].end 2417.036
transcript.whisperx[33].text 在强化延揽外国人才方面近期将配合国发会揽才专法的修正持续协助延揽外国专业人才来台另外也持续推动移工留才九用方案此外本部将增设直接聘雇联合服务中心分据点来辨明
transcript.whisperx[34].start 2418.16
transcript.whisperx[34].end 2447.078
transcript.whisperx[34].text 方便民众就近办理并简化聘雇流程来提升用工的效率接着在促进劳资合作方面本部也希望能够建构稳定稳健和谐的劳资关系包括透过补助和奖励鼓励工会积极办理教育训练强化劳工专业智能和劳动权益意识以及推动团体协约的签订此外为了协助经济弱势还有劳工争议诉讼期间的生活安定我们也延长中高龄者中高龄者和高龄者
transcript.whisperx[35].start 2447.52
transcript.whisperx[35].end 2472.382
transcript.whisperx[35].text 与身心障碍必要的生活费用辅助期间以降低劳工诉讼的障碍并推动劳动教育向下扎根来提升青年选址对劳动权益的认识而本部为策进职场减灾保障工作者的安全与健康除了加强营造工作场所源头管理外也强化营造工程减灾机制我们更更新了户外作业热危害预防指引
transcript.whisperx[36].start 2472.882
transcript.whisperx[36].end 2484.281
transcript.whisperx[36].text 避免工作者因高氣溫環境發生職業障礙同時持續輔導中小企業提升安全衛生措施透過大廠帶小廠的方式來提升安全衛生合作
transcript.whisperx[37].start 2485.453
transcript.whisperx[37].end 2511.268
transcript.whisperx[37].text 管理的績效那在健全職業傷害防治及職災個案主動服務上已於22個地方政府配置47名的職災勞工專業服務人員那以及22名的重建行政協助人員提供個別化的深度服務另外從115年1月起辦理職災勞工及家屬的法律權益協助方案從職災發生後
transcript.whisperx[38].start 2512.789
transcript.whisperx[38].end 2536.187
transcript.whisperx[38].text 及提供职灾原因初步分析专业律师协助陪同和解与调解到诉讼辅助等完整的法律资源职灾移工亦包含全程的同意协助确保职灾劳工及家属能够获得应有的补偿与赔偿那重整来说劳工部的施政核心还是要让劳工朋友基本生活有保障
transcript.whisperx[39].start 2537.948
transcript.whisperx[39].end 2550.281
transcript.whisperx[39].text 職場環境更友善就業機會更多元社會安全網更穩固那透過這樣的努力構築出一個更具韌性和前瞻性的勞動體系最後也謝謝今天各位委員的指教也希望各位委員持續給我們建議謝謝
transcript.whisperx[40].start 2558.223
transcript.whisperx[40].end 2586.996
transcript.whisperx[40].text 好有關本次會議各項書面資料均列入記錄刊登公報那現在開始做詢答做一下宣告第一本會委員詢答時間6加2分鐘列席委員4加1分鐘10點半截止發言登記委員如果有書面質詢請於3月前提出預計不受理暫定10點30分休息10分鐘原則上11點30分處理臨時提案10點半截止收件現在請登記第一位委員陳昭芝從委員來做發言
transcript.whisperx[41].start 2592.747
transcript.whisperx[41].end 2606.825
transcript.whisperx[41].text 謝謝主席 我想在質詢之前我想向服務本組的議事人員蔡豐汝女士表達哀悼之意她在星期天過世我祝福她往生淨土 得享永恆安樂謝謝主席 那有請洪部長有請部長
transcript.whisperx[42].start 2614.239
transcript.whisperx[42].end 2632.042
transcript.whisperx[42].text 陳委員早 部長早 剛剛您的報告當中因為有提到薪資的部分那你念的平均薪資沒有念到中位數薪資 你知道這兩個字數字向來差了將近一萬塊所以我主張我們在醫學上也都是用中位數來表達 因為有些人極端的數字會影響這個判讀
transcript.whisperx[43].start 2633.744
transcript.whisperx[43].end 2653.484
transcript.whisperx[43].text 這讓大家民眾的感受會是比較靠近那第二個就是生育補助部分也是一樣當陳時中政委公佈的時候他說一胎十萬大家都一胎十萬好像可能會有感也不見得會有感可是事實上不是那您剛剛念的是對的只是說他是補助至十萬本來就有兩個月的補助津貼
transcript.whisperx[44].start 2654.205
transcript.whisperx[44].end 2668.311
transcript.whisperx[44].text 所以我覺得政府在做這個不管是你覺得福利式的或是說一個惠民式的一個措施我覺得要講清楚因為誤解是更不好您剛剛是念對啦但是我是說政委在公佈的時候不是這樣的標題都是10萬塊
transcript.whisperx[45].start 2671.453
transcript.whisperx[45].end 2689.531
transcript.whisperx[45].text 我想在當時在這個生育給付加上生育補助其實這個是好事啦我只是說有時候讓民眾的感覺要真實一點部長謝謝你那兩週前行政院通過勞動部的一個跨國勞動力精進方案那我今天想跟部長討論一下這個方案的執行
transcript.whisperx[46].start 2690.692
transcript.whisperx[46].end 2712.921
transcript.whisperx[46].text 跨國勞動力的這個精進方案其中有一個政策就是製造業每加薪一位兩千元本勞兩千元那就可以增加一位移工的這個名額那這項政策是希望同時能夠舒緩低薪還有缺工的一個問題出發點非常好但是這個執行細節上我覺得還是要小心恐怕有時候會有一些本末倒時問題請問部長
transcript.whisperx[47].start 2714.301
transcript.whisperx[47].end 2729.971
transcript.whisperx[47].text 假如企業為了增加移工名額做了表面的加薪增加本薪2000元但原本的工作獎金或福利卻減少了或是取消了請問勞動部會允許嗎如果企業這麼做你還會同意給他新的移工名額嗎
transcript.whisperx[48].start 2731.513
transcript.whisperx[48].end 2758.799
transcript.whisperx[48].text 我想我們基本上我們就是希望企業能夠落實加薪尤其是我要強調這個是給相對低薪的本國勞工加薪我們知道那如果企業有相關的這些不誠實的規避的行為或者是就像說這個假加薪的這個狀況的話我想我們就會取消他的名額你們可以查核嗎你們有辦法查核嗎如何去認定可以嗎你們查核得到嗎我們通過勞保資料可以
transcript.whisperx[49].start 2760.588
transcript.whisperx[49].end 2778.565
transcript.whisperx[49].text 你們如果說有辦法查核 那是最好的我們希望這是一個實質的 實質下薪那這個政策也提到增額的那個移工期滿續聘必須幫本國勞工再次的加薪如果要續聘 請問這個再次的加薪薪資是多少 有規定嗎其實一樣 也就是說 我跟委員說明
transcript.whisperx[50].start 2785.545
transcript.whisperx[50].end 2806.938
transcript.whisperx[50].text 基本上比方說你如果幫10個本國勞工加薪2000塊你可以取得10個移工的名額但是在續聘的時候要維持這10個名額你還必須要再加薪一次就是一樣是10個本國勞工再加薪一次那才能夠保持這10個名額
transcript.whisperx[51].start 2807.398
transcript.whisperx[51].end 2833.054
transcript.whisperx[51].text 部長現在很清楚 謝謝你那這個方案跨國勞動力經濟方案還有另外一個政策是放寬外國技術人力的流用上限這應該是這個移工留才久用方案的一個延伸但是從2022年到現在移工團體認為這是失敗為什麼呢因為本來是希望說自身移工那他可以升階到這個中階技術人才技術人力長期留在台灣但是三年半了
transcript.whisperx[52].start 2833.914
transcript.whisperx[52].end 2840.415
transcript.whisperx[52].text 部長 李鑑哲升中間移工僅佔男女移工總數的百分比多好您知道嗎目前5萬多人
transcript.whisperx[53].start 2841.291
transcript.whisperx[53].end 2869.423
transcript.whisperx[53].text 4.5個Percent這5萬多人就很少嘛 百分之4.5對 您知道那這個不到一成的轉換率那明顯應該無法達到這個流財的目標那過去也有一些移工因為他們要身為這個中介人力的時候需要繳交更高的仲介費而且部分仲介甚至趁此去哄抬那個收費所以部長對於這麼低的轉換率還有這個仲介可能從中剝削勞動部知道嗎你們怎麼處理這件事
transcript.whisperx[54].start 2870.503
transcript.whisperx[54].end 2885.626
transcript.whisperx[54].text 先跟委員說明其實的確很多中小企業他的那個可能中小型的工廠他用的移工數比較少所以他們都來跟我們反映他們想要把它轉成中階技術人力已經到達那個原本25%的天花板了
transcript.whisperx[55].start 2886.997
transcript.whisperx[55].end 2896.06
transcript.whisperx[55].text 就是他們還想要再轉更多可是因為達到已經達到25%的天花板了所以就限制住他們能夠轉換的數字所以這是為什麼我們把它打開我們現在把這就是為什麼我們把這25%打開的原因
transcript.whisperx[56].start 2902.102
transcript.whisperx[56].end 2930.803
transcript.whisperx[56].text 那當然接下來針對仲介費因為現在國際上面都非常非常關注仲介費的這個問題我們會在整體的強迫勞動整體的來思考裡面包括我想這幾天大家也知道我們會做相關的法規的檢討裡面希望能夠更大程度的去面對這個事情我再請教你一個問題因為這個移工團體一直訴求的廢除這個攔領移工工作的年限請問你們的想法是什麼有往這個方向去做的可能性嗎
transcript.whisperx[57].start 2931.243
transcript.whisperx[57].end 2948.049
transcript.whisperx[57].text 其實的確現在我們為什麼在這次的方案裡面更加的重視這個外國技術人力其實很重要包括外國技術人力的權利因為透過外國技術人力的工作年限是沒有限制的那我們也希望把這個通道打得更開
transcript.whisperx[58].start 2950.51
transcript.whisperx[58].end 2956.577
transcript.whisperx[58].text 那部長勞動部明年就是說要在這個菲律賓設置這個跨國勞動力延展中心那我就請教這個是好事那我請教部長為什麼選擇菲律賓是基於什麼評估是原能力人力供應市場關係外交還是外交考量還有另外就是說在做選擇的時候有沒有跟其他的東南亞國家做一個比較麻煩部長
transcript.whisperx[59].start 2974.073
transcript.whisperx[59].end 2988.181
transcript.whisperx[59].text 第一個先謝謝委員的肯定那我們其實要設置延展中心其中一個很重要的目的其實就是希望能夠強化這個國對國的職聘的能量大家期待很久
transcript.whisperx[60].start 2989.722
transcript.whisperx[60].end 3008.308
transcript.whisperx[60].text 那這也是我們很實質的作為那第一個當然也有考慮菲律賓目前跟我們的外交關係是很好的那也包括其實菲律賓也一直有來跟我們表達希望大家在人才上面能夠有更多的合作所以我們也在這個理由之下菲律賓現在是
transcript.whisperx[61].start 3009.008
transcript.whisperx[61].end 3027.894
transcript.whisperx[61].text 先做的選擇第一個選擇是菲律賓但是我們也在評估其他的選擇也不只現菲律賓我想請教這個延攬中心招募對象是中階技術還是一般的初階的藍營移工因為我看到預算書你們的目標是15000人那主要又放在哪些產業
transcript.whisperx[62].start 3029.319
transcript.whisperx[62].end 3053.335
transcript.whisperx[62].text 其實因為我們這次開放的旅宿業的技術人力跟三崗碼頭的技術人力其實他們會透過延展中心進來但是延展中心也會協助蘭嶺移工的職聘所以蘭嶺移工的職聘跟中階技術人力的這個相關的引進都會透過我們的延展中心來擴大協助的能量
transcript.whisperx[63].start 3054.015
transcript.whisperx[63].end 3083.315
transcript.whisperx[63].text 部長您剛剛提到了好不容易聽到一個國對國的這個職聘那我還是要問請教如果他們進來後會有仲介介入嗎那在菲律賓會不會被收取這個仲介費我的意思說因為如果你要去設個海外延攬中心的話那我們應該要保護這個勞工在母國或在臺灣都不要再有仲介業者穿梭其中不然就失去你在海外設立這個延攬中心的這個意義你有做過這個部分的考量嗎或是管理
transcript.whisperx[64].start 3083.655
transcript.whisperx[64].end 3103.828
transcript.whisperx[64].text 跟文說明的確現在我說國際上也非常非常關注這個仲介費相關的問題那我們會一步一步來做檢討那包括國外包括國內但是我想我們這一次的計劃的內容是很明確的我們往前跨了一步
transcript.whisperx[65].start 3104.989
transcript.whisperx[65].end 3117.832
transcript.whisperx[65].text 部長因為要聽到您的一個勞動部長講說國對國的執聘是不容易的那我還是請教之前問過你那個Giant巨大他被指控強迫勞動也被美國發出這個戰扣令請問目前的進度是什麼有解除了嗎
transcript.whisperx[66].start 3119.131
transcript.whisperx[66].end 3140.355
transcript.whisperx[66].text 還解除了嗎跟委員說明因為當然這個現在巨大公司也正在跟美國的CPP他們在做直接的討論還在努力直接討論就目前我們看到巨大公司也做出了改善的承諾部長我先確定一下就是說他是不是違反勞動的勞動法令還是另外一個我們剛剛你談到的仲介費問題這兩個都有嗎我先確認一下
transcript.whisperx[67].start 3144.978
transcript.whisperx[67].end 3161.72
transcript.whisperx[67].text 確實 因為勞動部去檢查說沒有啊沒有違反那個台中市勞工局去檢查說沒有那我就說勞動法令這是等一下我再跟你稍微討論一下仲介費因為本來就很容易被國外嘛歐美國家認為這個仲介費就是剝削勞工我想你現在也知情了嘛瞭解這樣的事情我不是現在才知情
transcript.whisperx[68].start 3162.24
transcript.whisperx[68].end 3182.738
transcript.whisperx[68].text 好謝謝你很久之前關心勞工就知道了那現在有自行車的大廠說台灣的法規這是天家雜誌報導移工可以自行因為我們的法規有明定移工可以自行負擔一定比例的仲介費保險啊這個裡面包括機票仲介費保險等等但是歐美期待是零付費所以我的意思是說排除那個一般的我們所謂勞檢這個不合格台灣的法規跟不上國際的要求因為我們允許
transcript.whisperx[69].start 3187.722
transcript.whisperx[69].end 3210.324
transcript.whisperx[69].text 所以企業界覺得他們按照台灣的法規去做可是會被可能在國際上會被懲罰所以這個問題就落在這個勞動部身上了他即使合規和我們勞檢但是他因為還有這個仲介費的部分跟我們說明我們第一個我們會先來做一個行動的指引來跟經濟部一起合作輔導企業但是我們同時也正進行法規的盤點
transcript.whisperx[70].start 3211.986
transcript.whisperx[70].end 3239.813
transcript.whisperx[70].text 那我們也會在輔導的同時來去檢討那這個法規跟國際要求上面之間是不是還存在著落差那是不是要來後續在什麼樣的期程之下來去思考要不要做檢討甚至改善謝謝您今天的那個回答因為您今天就是有談得很清楚你知道你先做指引但我們知道指引是行政行政的指引它是沒有約束力的那你剛剛有提到說在法規面你要盤點就是往法規面走
transcript.whisperx[71].start 3240.293
transcript.whisperx[71].end 3267.746
transcript.whisperx[71].text 我们当然会做法规会往法规面盘但的确因为台湾的中小企业比较多那所以其实我们也会需要考虑到不同规模之间的调试能力16家企业其实也被点名吧对所以我跟你说因为台湾的企业的规模从大到小有很多所以也必须帮比较小型的企业去设想他可能需要的调试的能力据了解我图片上贝寇要在这个总这个供应链有2.7兆哦
transcript.whisperx[72].start 3270.307
transcript.whisperx[72].end 3282.333
transcript.whisperx[72].text 2.7兆這麼多 所以部長這個腳步要快要用這樣的方式來 影響太大了好 謝謝部長 謝謝主席好 謝謝陳偉 謝謝部長接下來請林月琴委員來做選擇主席麻煩洪部長 請部長
transcript.whisperx[73].start 3303.871
transcript.whisperx[73].end 3325.64
transcript.whisperx[73].text 林委員好部長早 首先還是要感謝你因為我們上次質詢針對關稅有被中高齡備份五星假的這個課題你已經啟動讓每個月僱主都通報上來來讓掌握到備份五星假真的先首先先感謝很快的來關心到我們的中高齡備份五星假的問題那
transcript.whisperx[74].start 3329.319
transcript.whisperx[74].end 3347.825
transcript.whisperx[74].text 部長你應該也知道最近我們的交委會有在處理高溫價的一個議題那看起來將高溫會納入到災害的一個天氣那勞動部在去年8月的時候也修正職業安全衛生設施規則
transcript.whisperx[75].start 3350.598
transcript.whisperx[75].end 3366.639
transcript.whisperx[75].text 高氣溫的作業熱跟危害的預防指引想先問部長目前的修正對高溫下勞工是不是真的有幫助我想其實我們在當時7月的修正的這個
transcript.whisperx[76].start 3368.171
transcript.whisperx[76].end 3389.341
transcript.whisperx[76].text 高溫熱危害的指引裡面吼那其實更明確的對於這個高溫的風險做出了分類吼那如果尤其是他如果是第四級的話其實雇主就是有義務如果進入到第四第四級的風險情境的話雇主就是有義務要提出預防的做法那如果沒有做的話這個我們的檢察員是可以開罰的
transcript.whisperx[77].start 3390.621
transcript.whisperx[77].end 3408.387
transcript.whisperx[77].text 是 可是我們從衛福部的資料大概也可以看到就是熱傷害的個案從2021年423人已經增到2024年的7月的時候已經1204人了成長大概三倍那顯示現在的指引模式可能沒有辦法有效真的是去降低這樣子一個熱傷害
transcript.whisperx[78].start 3410.067
transcript.whisperx[78].end 3432.418
transcript.whisperx[78].text 另外我也收到很多未成年勞動者反映許多長期曝曬的一個工作場所僱主跟勞工都不知道這些指引的內容那更別說有沒有執行了這也可能也反映了上述增加的數字也有可能存在是非常多的黑數而目前勞動部似乎也要朝向如何讓勞工工作空間
transcript.whisperx[79].start 3434.399
transcript.whisperx[79].end 3463.02
transcript.whisperx[79].text 避開熱危害而不是給假的一個模式那目前狀況你整個進度的狀態是如何而且如何確保部署可以執行到這些相關的規定且確實執行謝委員 曾子勳這個部分大概就是我們分為勞檢是一定會做的當然就是接下來就是宣導跟輔導那看起來我們這個宣導的層面還要再加強就是如何讓這個指引的內容讓一般的勞工
transcript.whisperx[80].start 3464.1
transcript.whisperx[80].end 3488.812
transcript.whisperx[80].text 知道說我們的一個一些防護也跟委員報告我們今年也開始提供這個勞工自營作業者他的中小企業勞工跟自營作業者他個人的防護像今年也九月份開始申請到目前為止也蠻多人來申請這個個人的這個風扇衣這個部分我們目前提供如果僱主跟勞工都不知道這些內容的話我會覺得那就是沒有辦法做到比較好的防護不過我建議在勞檢的時候當然剛剛成儒
transcript.whisperx[81].start 3491.431
transcript.whisperx[81].end 3509.137
transcript.whisperx[81].text 要加強宣導跟檢查可是對落實優良的企業是不是可以給予友善職場的認證或者是減稅誘因或者是對於違規者的明確裁罰跟公告這個我是覺得可以進一步來做研議那在部長我真過去針對於包含
transcript.whisperx[82].start 3509.677
transcript.whisperx[82].end 3537.696
transcript.whisperx[82].text 我們的家庭照顧假育嬰留庭假等多次質詢希望能夠有更彈性的制度如果小朋友因為高溫身體不適的話依照現行的制度那當然家長可以利用一年的一個56個小時的家庭照顧假明年新制上路的話也可以從原本的日記的一個調整成實際我要給部長先予以肯定確實彈性非常的多這也是我過去一直主張不過我覺得部內現在
transcript.whisperx[83].start 3540.358
transcript.whisperx[83].end 3557.078
transcript.whisperx[83].text 目前之前我们有提过国际照顾价的研究计划你们也在做了希望能参考国外的经验现在也开了很多场的专家学者会议也提出了对应的措施政策不知道下一步你的规划会是什么
transcript.whisperx[84].start 3558.41
transcript.whisperx[84].end 3572.849
transcript.whisperx[84].text 我想我们其实目前的确在今年9月我们公布的因为刘婷谈性话里面让大家可以一日来请30日那家庭照顾家也以时来请我们是认为我们可能先给因为
transcript.whisperx[85].start 3573.79
transcript.whisperx[85].end 3598.822
transcript.whisperx[85].text 確實台灣的中小企業蠻多的所以其實大家也會需要在這個情境下面有一個適應期其實我跟委員報告其實這兩個月我們是非常緊鑼密鼓的在找企業包括是企業的人資在讓他們了解我們這個措施其實要怎麼樣更簡正便民的執行用更簡化的程序的方法讓大家可以操作不會在申請上面造成過多的
transcript.whisperx[86].start 3599.822
transcript.whisperx[86].end 3623.226
transcript.whisperx[86].text 負擔所以這幾個月我們其實辦了很多場跟這些人資的夥伴尤其是不同產業人資的夥伴在辦的確我們是希望說也許這個做法這個彈性化的做法可以先上路一段時間當然後續是不是要再來做範圍上面的擴大當然我覺得我們也可以來評估跟演繹明年第一季是不是這個國際照顧價的研究計畫是不是可以完成報告
transcript.whisperx[87].start 3625.226
transcript.whisperx[87].end 3642.531
transcript.whisperx[87].text 應該是可以好那是不是一週內可以提供我一些相關的資料就是你這計劃進行好謝謝那再來我們就看到就針對育嬰留停假勞動部真的放寬了非常多的限制不過明天即將上路的卻還是沒有適用年齡當初我們還是希望比照國際有的是到
transcript.whisperx[88].start 3643.211
transcript.whisperx[88].end 3666.633
transcript.whisperx[88].text 到那個8歲可是你現在依然還是維持在現行的3歲而且是以日為單位而媒體報導說未來不排除擴大不然這部分你的考量會是什麼就是3歲以下那為什麼沒有擴大有在研議嗎未來有可能擴大嗎跟文文說明其實我們這次做了這樣子的突破這次的突破的幅度其實是蠻大的那
transcript.whisperx[89].start 3669.488
transcript.whisperx[89].end 3692.073
transcript.whisperx[89].text 的確會有一些中小企業他們跟我們表達其實這對於他們在比如說企業內部的管理跟排班上面也會有一些挑戰所以一樣是剛剛我們也是在思考說因為這一次的做法是透過還不用修模法的狀況先來做所以我們希望能夠讓我們的產業界有一段時間的
transcript.whisperx[90].start 3693.853
transcript.whisperx[90].end 3721.4
transcript.whisperx[90].text 調適跟適應那讓這樣以日請休的運營留庭的方式慢慢的摸索也熟悉能夠上手那在企業跟勞工之間的相關的權益那怎麼樣做到平衡而且能夠互相支持那到一個調適的階段後續那對於是不是剛才說要把年齡再提高或者是範圍再擴大我覺得如果尤其是他可能會涉及到法律上的修正的話那我覺得我們也可以來做這樣子的考慮
transcript.whisperx[91].start 3722.52
transcript.whisperx[91].end 3738.952
transcript.whisperx[91].text 再麻煩部長去做一些演繹因為我們還是期望能夠朝向真的幫助到家庭可是除了要照顧自己的孩子的話蠟燭另外一端就是年長者隨著超高齡社會的到來依照勞動部推估我們台灣的就業人口當中
transcript.whisperx[92].start 3739.312
transcript.whisperx[92].end 3761.864
transcript.whisperx[92].text 同時需要照顧他人的占五分之一 超過200萬人其中每年約18萬人因照顧而調整工時或者是請假甚至13.3萬人是因照顧而離職那這對於缺工又希望促進中高齡就業的社會來講無疑是個打擊針對這些影響 三明治的勞工勞動部有沒有什麼樣的一個應對政策
transcript.whisperx[93].start 3763.089
transcript.whisperx[93].end 3780.323
transcript.whisperx[93].text 跟跟委員說明第一個其實針對長照就是台灣台灣的勞工那是否家裡有長照的需求是不是要再做我們的職場制度或工時制度的調整部分其實我們有跟衛福部討論那當然因為現在衛福部
transcript.whisperx[94].start 3781.003
transcript.whisperx[94].end 3795.088
transcript.whisperx[94].text 他目前也正在規劃那後續已經要來執行所謂的長照3.0所以我們這部分會跟衛福部綜合來研議如果衛福部認為在長照3.0的政策之下是有需要在職場的制度上面做出一些相對應的
transcript.whisperx[95].start 3796.808
transcript.whisperx[95].end 3823.127
transcript.whisperx[95].text 調整然後來去因應台灣的長照需求的話當然我們也不排除跟衛福部一起在做這部分的討論但是重點是他還是要請衛福部這邊先做目前長照整體需求的評估因為這部分我們沒有在需求面這不是我們沒有辦法自己單獨完成這件事情可是在長照需求的評估完成有個很比較清楚的輪廓假如有需要職場制度的話那我想我們可以在一起來討論
transcript.whisperx[96].start 3823.993
transcript.whisperx[96].end 3845.024
transcript.whisperx[96].text 因為最實際案例是當老人就是住院就長輩住院出院前準備凡家後使用長照甚至聘僱移工之前都需要子女請假去安排所以每次安排時間大概20天到30天不等當然我們現在看到衛福部也一直在縮短這個準備時間可是這就像剛剛部長講的說未來老公
transcript.whisperx[97].start 3846.585
transcript.whisperx[97].end 3864.893
transcript.whisperx[97].text 衛福部如果確定的話那你這個家庭照顧假因為現在看到的只有7天以下就是用完因為根本不夠因為現在如果講20到30天如果搭配一年14天的特休的話加起來也才21天可能就是沒有辦法達到可是我們反觀看日本就是說
transcript.whisperx[98].start 3866.414
transcript.whisperx[98].end 3886.212
transcript.whisperx[98].text 他們的長期照顧的安排架裡邊針對於家中有長者安排的會給予一些彈性所以他們的育兒戒護修業法每一位長輩就是一生當中有93天的時間可以提供子女請假去做長照的一個準備
transcript.whisperx[99].start 3887.052
transcript.whisperx[99].end 3903.985
transcript.whisperx[99].text 當然包含南韓 德國跟法國有類似的制度當然我知道說我們現在一時要到達很難可是請問部長因為從2019年民間團體就在倡議至今那勞動部對長期照顧安排假有什麼規劃那短充期的目標 工作目標又是什麼
transcript.whisperx[100].start 3904.81
transcript.whisperx[100].end 3928.948
transcript.whisperx[100].text 就是其實就如同剛才跟委員說的就是說這部分我們真的會也需要衛福部這邊其實在他整體的長照政策的需求評估上面那來去做一個下一個階段的評估尤其是現在有長照3.0的政策那衛福部也一直跟我們說他們會把這相關很多的間隔的時間大幅的縮短那可能
transcript.whisperx[101].start 3930.709
transcript.whisperx[101].end 3945.815
transcript.whisperx[101].text 在未服務政策的目標下可能那個可能很多的那個時間的間隔的需求可能會跟過去是不太一樣可是他可能會需要他們在實施以後來去更清楚的去描繪這件事情我們比較能夠來評估是不是有這樣子的需求
transcript.whisperx[102].start 3946.595
transcript.whisperx[102].end 3961.26
transcript.whisperx[102].text 我是認為說如果目前當然我們沒辦法比照日本而且我覺得已經也大幅的針對於育兒的家庭已經有針對於那個前面剛剛提的已經有一些改變了那可不可以考慮一下
transcript.whisperx[103].start 3962
transcript.whisperx[103].end 3977.248
transcript.whisperx[103].text 一定比例的就說現在事實上我們的家庭照顧家事實上是無薪的那有沒有辦法事實上是有薪假然後由政府來負擔我們的僱主多餘的支出然後這樣子先做這樣的一個
transcript.whisperx[104].start 3978.148
transcript.whisperx[104].end 3993.775
transcript.whisperx[104].text 調整希望勞動部可以先做去考量因為我們當然沒辦法要求到30天甚至日本是到93天那有沒有辦法事實上先做這樣的一個考慮那請勞動部在一個月內是不是可以把研議的狀況提供給我們辦公室
transcript.whisperx[105].start 3994.363
transcript.whisperx[105].end 4017.493
transcript.whisperx[105].text 可以但我這邊但就直接的跟委員說因為如果家庭照顧家有心的話那不脫兩個方面要不就是企業支付薪資要不就是政府支付可是我們計算過如果是政府支出的話其實這需要非常大的財政的能力可能算起來是這個
transcript.whisperx[106].start 4021.254
transcript.whisperx[106].end 4046.489
transcript.whisperx[106].text 幾百億以上的中央政府的財政但現在中央政府的財政狀況難度是很高的所以我說先考量去研議因為畢竟現在家庭就在育兒跟照顧長輩夾殺當中事實上是非常辛苦的接下來一樣是關於假的議題前天勞動部有召開病假權入法的公聽會目的是要解決雇主
transcript.whisperx[107].start 4046.929
transcript.whisperx[107].end 4070.288
transcript.whisperx[107].text 可以能以病假來審查全勤獎金 晉升考核等不利待遇的手段變相來懲罰請假的一個員工 進而造成病假成為職場的一個風險扣年度的考積等不利待遇事實上大部分勞工會擔心的 所以往往會抱病去上班所以目前勞動部的修法的方向是什麼
transcript.whisperx[108].start 4072.797
transcript.whisperx[108].end 4098.071
transcript.whisperx[108].text 其實在這個長榮航空的這個事件之下其實各界都很關心勞工請病假權因為都不希望這個企業過度的運用管理制度讓員工不敢請病假只能抱病上班然後甚至影響到員工的健康權其實也會影響到很多的服務品質跟工作的成果
transcript.whisperx[109].start 4099.051
transcript.whisperx[109].end 4119.627
transcript.whisperx[109].text 所以我們其實在這個星期一其實我們就邀請我們相關的工會團體不只是全國性的工會其實有一些也是地方的工會很關心的工會也一起來那包括跟雇主團體一起來研商那我們就是希望接下來在病假保障的權利上病假權的法制化上面
transcript.whisperx[110].start 4120.367
transcript.whisperx[110].end 4143.03
transcript.whisperx[110].text 需要给予目前劳工在请病假的权利上面一定程度的保障至少一个合理的保障让我们的劳工至少在请病假的时候不会担心遭到企业不利的对待各种可能各种的不利的对待让大家不敢请休但我还要特别提醒就是修法是一定要修
transcript.whisperx[111].start 4144.023
transcript.whisperx[111].end 4161.544
transcript.whisperx[111].text 尤其是雇主利用不利待遇的一個手段那讓請假權成為一個被剝奪的對象可是除了立法我收到更多勞工反映的是即便是有法的保障雇主有沒有遵守法律有沒有有效的內部外部申訴機制其實是更重要的
transcript.whisperx[112].start 4162.265
transcript.whisperx[112].end 4186.102
transcript.whisperx[112].text 所以包含申請勞檢的時候有沒有發現實際的問題而非我們檢查形式上的設置卻沒有實際作用所以我希望勞動部也要注意到這一塊然後來做預防否則的話基本上沒有辦法達到所以最後就是希望你們真的要那個落實那個申訴機制還有增加我們的勞檢的強度不要做表面的公佈還要盡快啟動我們的
transcript.whisperx[113].start 4188.403
transcript.whisperx[113].end 4209.574
transcript.whisperx[113].text 企業的盡職調查以上我想我們不會我們不會是只會停在所謂做表面功夫尤其是我們可能這部分也會接下來如果制度修正以後也會需要有專案性的這個檢查讓企業在這方面把法尊給做起來我相信洪部長很關心勞工應該一定都能夠完成謝謝
transcript.whisperx[114].start 4216.604
transcript.whisperx[114].end 4218.866
transcript.whisperx[114].text 好謝謝謝謝部長接下來請陳秦威委員來做詢問謝謝主席我主席我想請洪部長謝謝來請部長
transcript.whisperx[115].start 4237.99
transcript.whisperx[115].end 4247.446
transcript.whisperx[115].text 陳委員長部長我今天本來是也要針對勞工政策提出很多具體的建議但今天想跟您說的是本席遇到了非常多的問題
transcript.whisperx[116].start 4249.284
transcript.whisperx[116].end 4273.879
transcript.whisperx[116].text 給你看這份公文是10月8號我們辦公室發文的關心花蓮災民的臨時工方案辦理狀況你們回復我們的是說10月15號就要回復因為我們關心災民的安置我們要看執行的成效我們要看監督的資源有沒有到位結果到現在都沒有回函這是第一份這是第一份第二份
transcript.whisperx[117].start 4274.878
transcript.whisperx[117].end 4288.387
transcript.whisperx[117].text 我們來看我希望在10月21號的時候發文索取供應鏈支持方案執行狀況那10月29號就應該回文的結果一樣是石沉大海
transcript.whisperx[118].start 4289.963
transcript.whisperx[118].end 4309.909
transcript.whisperx[118].text 再來第三份我是10月30號發文要求提供民間企業參與托育服務的統計數據那這個很簡單因為我本來就是一時很關心少子化育兒環境我需要知道數據我才知道為什麼托育政策做不到做不來11月7號就該回了
transcript.whisperx[119].start 4310.509
transcript.whisperx[119].end 4339.035
transcript.whisperx[119].text 那現在累積了三份公文完全沒有辦法回覆我幫你算了一下拖延的時間分別花連是35天供應鏈支持方案21天民間企業提供托育服務12天我想在這邊問到底是什麼原因因為我們也是根據立法院的職權行使法第45條的問政監督權來監督行政部門但是你們沒有不回就是不回
transcript.whisperx[120].start 4339.955
transcript.whisperx[120].end 4352.665
transcript.whisperx[120].text 你現在是可以告訴我一個日期什麼時候可以回嗎這樣好不好所以下週這幾份我們都會回文而且我也會請我們相關的單位到委員辦公室來說明
transcript.whisperx[121].start 4353.933
transcript.whisperx[121].end 4380.175
transcript.whisperx[121].text 我上次遇到這個狀況是環境部你知道上次風災有幾十片的光電板需要處理所以8月的時候他告訴我他會告訴我編片有序號然後會有一個清單9月沒辦法10月沒辦法3個月沒辦法結果果然11月才說真的找不回來了因為數量太大了我希望不是因為這樣子的問題我真心的希望不是因為這些數據是你沒有辦法提供的
transcript.whisperx[122].start 4380.655
transcript.whisperx[122].end 4408.215
transcript.whisperx[122].text 這些數據其實都我想這都沒什麼問題所以我們就下週所以你今天會押一週內這些東西我都可以有一個答案一週內我們提供然後我也會請我們相關的這個單位權責單位到委員辦公室說明那部長您現在可以告訴我就是未來我也想知道未來假使我跟您發文所資最晚是不會超過幾天我沒有辦法現在因為不同的資料可能不同的狀況
transcript.whisperx[123].start 4409.284
transcript.whisperx[123].end 4425.619
transcript.whisperx[123].text 但這些針對這些資料沒有沒有這些資料下禮拜就會給我們就可以給但是未來每個不同的資料會有不同的狀況那我也希望您來說明的時候可以告訴我說您看你針對這些資料你沒有什麼意義嘛可是為什麼會拖到35天也希望可以給我一個答案好嗎可以嗎好
transcript.whisperx[124].start 4429.892
transcript.whisperx[124].end 4453.594
transcript.whisperx[124].text 好再來我們看一下你在這個任性特別預算以及115年就業安定基金總共加起來編了21億是有關於青年就業的預算這當然不是一筆小數字所以我也認為這是勞動部認為關稅衝擊之下所需要的經費所以才會編列這些預算但我們來細細拆分一下
transcript.whisperx[125].start 4454.675
transcript.whisperx[125].end 4476.342
transcript.whisperx[125].text 我本席有蠻多朋友有去參加您去11月9號北學聯的交流活動所以當時你有宣傳說支援青年就業計畫這個最高祭出了4.8萬的補助然後已經有超過5000名的青年申請從9月開始上路以來那姑且先不論預算重疊
transcript.whisperx[126].start 4477.742
transcript.whisperx[126].end 4500.357
transcript.whisperx[126].text 因為你是一個原本計畫的加強版嗎也許勞動部認為有其預算的必要性但是呢我看了之前立法院的官方很多的審查意見喔對於勞動部推動這個的執行率是說非常的慘淡114年115年就業安定基金分別編列的4.32億4.03億執行率卻只有慘淡的13.76%
transcript.whisperx[127].start 4509.103
transcript.whisperx[127].end 4526.558
transcript.whisperx[127].text 我想算一下因為你說現在超過是五千名超過六千 從申請到你發下來還需要一點點時間我們來算一下 這都是你們自己的圖表我稍微看了一下 112年當然沒有最新的數據
transcript.whisperx[128].start 4527.799
transcript.whisperx[128].end 4546.82
transcript.whisperx[128].text 失業的青年大概是17.7萬如果你可以告訴我最新大概是幾萬也OK那當時的失業週數為19.6週也就是4到5個月那如果你說這個6000人或是5000人目前大概是3%的失業青年有收回到
transcript.whisperx[129].start 4548.618
transcript.whisperx[129].end 4574.275
transcript.whisperx[129].text 我在講是最後的核發人數這6000人是申請人數我不知道未來核發的比率是多少可是他幫助到的就是3%那我以你最高最高可以領到你講的48000元的話這已經是以這筆錢極大化的狀況也就是每一個人都達到這個條件總預算大概是要支出兩億四千萬元
transcript.whisperx[130].start 4574.995
transcript.whisperx[130].end 4590.206
transcript.whisperx[130].text 那得出來的質詢率大約是16%那依照你看起來任性計畫應該先走嘛任性計畫它給的補助是比較高的所以假使我是青年我一定是優先申請任性計畫而且你也是優先核發這個嘛
transcript.whisperx[131].start 4591.943
transcript.whisperx[131].end 4613.6
transcript.whisperx[131].text 你覺得有沒有可能114年的就業安定計畫預算是執行不完的依照這個進度我先跟委員說明其實比方說就像委員講到我們在11月9號去跟我們的這個大專的學生朋友在講這件事情的時候其實真的現場很多的同學不知道這個計畫
transcript.whisperx[132].start 4615.714
transcript.whisperx[132].end 4627.76
transcript.whisperx[132].text 那這也是為什麼我們其實當時在編列任性計畫的時候很希望能夠給我們比較充足的宣傳預算的原因可是後來這個宣傳預算直接被砍了半直接被砍了半我告訴你我們在這邊針對宣傳的方式已經講過好多遍我現在稍微提醒您一下之前我說您的這個圖卡都是我們人民因應其判的點擊率很差
transcript.whisperx[133].start 4645.089
transcript.whisperx[133].end 4663.784
transcript.whisperx[133].text 怎麼樣的然後你就說這個是我們小編焚膏忌鬼花自己的時間做出來的這個是不需要用到任何的宣傳費所以我們不用去追蹤他的追蹤數這個答案你也講過然後執行率不夠不好的時候你就說沒宣費被砍了這個我們在這個場景也講過
transcript.whisperx[134].start 4668.027
transcript.whisperx[134].end 4694.833
transcript.whisperx[134].text 我現在問你誰是使用網路最高的族群就是這個族群就是你說的最不需要你的小編就可以做出圖卡的這就是使用網路最高的族群我問你這個族群的人這個族群的人是不是知道有這樣子的福利自己都會去宣傳是吧連我都已經遇到北學聯的人回來告訴我說
transcript.whisperx[135].start 4696.613
transcript.whisperx[135].end 4725.973
transcript.whisperx[135].text 您的宣傳也不用錢啊您也可以自己拍影片啊不是嗎您在11月9號您在11月9號的宣傳就非常的好好 我跟你說我剛已經講過了我剛已經講過了你現在的任性計畫裡面其實是原本計畫的強化版我也看完了它的時間比較短然後它的費用多1000塊你的沒薰費本來就可以一併使用可是你卻把它怪罪在
transcript.whisperx[136].start 4727.013
transcript.whisperx[136].end 4749.49
transcript.whisperx[136].text 之後這個任性計畫裡面的媒體人任性計畫的媒體人也讓你編了根據在野黨之前寫的這2000這2000就是非跟就業計畫相關的所以這絕對不是你成效不好的藉口絕對不是你成效不好的藉口這個族群是你最容易用網路就approach的族群
transcript.whisperx[137].start 4750.01
transcript.whisperx[137].end 4776.849
transcript.whisperx[137].text 我們現在是想要好好來討論說為什麼你的執行率不夠好我們是一起來研究這個計劃很好啊我們兩個都很希望越多人領到越好不是嗎跟文說明第一個事情是我們認為這個計劃的執行率可能不是這樣算的他不是拿來去處理所有的這個現在沒有就業的年輕人的這個算法他的這個執行率的計算不是這樣那我們的確看到現在在這個計劃的在在
transcript.whisperx[138].start 4779.651
transcript.whisperx[138].end 4805.624
transcript.whisperx[138].text 年輕社群裡面其實接受度是很高的只要有講到他們一知道他要找工作就很希望能夠申請所以重點是怎麼讓年輕族群能夠知道因為我們發現在執行的過程裡面發現只要讓大家知道他有這個需求他申請的意願就高可是我們的關鍵是怎麼讓更多年輕的族群知道網路是一種方法沒有問題網路我們會直接宣傳我其實我個人我就已經宣傳好多波了
transcript.whisperx[139].start 4806.304
transcript.whisperx[139].end 4823.448
transcript.whisperx[139].text 我自己用我自己的臉書社群我就宣傳好多波了但是我們知道如果要讓更多的年輕朋友知道可能還需要更多的方法跟資源方法是一件事情可是沒有辦法全部都依賴我自己去到每一個學校裡面我先念一下114年勞動部加救安基金沒選費大約是2億元
transcript.whisperx[140].start 4828.889
transcript.whisperx[140].end 4831.751
transcript.whisperx[140].text 115年勞動部加救安基金沒宣費大約是一億三千萬元我今天不是來跟你炒沒宣費的我今天絕對不是來跟你炒沒宣費你自己的就經營的非常好靠你自己宣傳我覺得也可以宣傳很好我是很想知道裡面
transcript.whisperx[141].start 4844.958
transcript.whisperx[141].end 4861.216
transcript.whisperx[141].text 我們一起研究之前我們一直講婦女賽就業計畫你就很誠實的說啊你說後來這些上的課真的太多因此很多婦女非常有意願結果達不到門檻這也不是宣傳做的不好是因為它中間要上的課程太多所以我是來跟你討論第一
transcript.whisperx[142].start 4863.078
transcript.whisperx[142].end 4888.684
transcript.whisperx[142].text 你有沒有可能因為任性的執行率達不到全部做不完後來你原本編的救安基金裡面的會用不完有沒有這個可能這是我第一個要問的問題嘛我剛就已經問了嘛第二個問題就是說你覺得裡面有沒有什麼青年來申請的門檻我們可以調降的因為你之前就曾經官方被講執行率差這件事不是嗎
transcript.whisperx[143].start 4889.244
transcript.whisperx[143].end 4909.59
transcript.whisperx[143].text 跟委員說明第一個我其實覺得這件事情是大家可以是攤開來好好討論比方說之前委員關心婦女的那幾支計畫的確我們認為在裡面執行它的機制的過程有檢討的必要就是它是在執行的操作的門檻上面都有調整的必要這部分我想我們是很坦誠的
transcript.whisperx[144].start 4910.43
transcript.whisperx[144].end 4936.343
transcript.whisperx[144].text 所以我也想知道這邊有沒有你可以調整的在青年的這個執行率就我們目前執行的狀況看到的事情其實我們是把他的門檻有調整原本是要三個月現在我們把他調整成兩個月把三個月調整到兩個月那就我們目前知道在年輕人知道這個計劃他如果他要找工作的時候他知道這個反應的時候他其實他來申請的意願我認為是有一定高的意願的
transcript.whisperx[145].start 4937.244
transcript.whisperx[145].end 4945.839
transcript.whisperx[145].text 可是他有一定高的意願可是為什麼來申請的人數其實我們也認為可以更多但是現在最關鍵的事情是很多年前真的不知道
transcript.whisperx[146].start 4949.127
transcript.whisperx[146].end 4956.851
transcript.whisperx[146].text 沒關係在這個計畫裡面如果是機制有問題我們可以檢討機制我現在想要問你的是第一個問題你也還沒回答我我現在想要問你的是我看到了你把門檻調低了可見門檻就是一個很明顯的因素不然你不會把門檻調低嘛你門檻調低你把任性計畫的錢你如果花不完你救安基金會不會沒辦法還是你救安基金的條件也會跟著改
transcript.whisperx[147].start 4979.263
transcript.whisperx[147].end 4998.155
transcript.whisperx[147].text 這就是一個很好的答案你一直在扯沒宣費但實際上你就是調低了門檻不是嗎跟委員說我現在沒有一定只聚焦在沒宣費可是我只是要說我們認為我們自己判斷在這個計畫上面要讓更多年輕人來申請最重要的關鍵是要讓年輕人知道
transcript.whisperx[148].start 4999.176
transcript.whisperx[148].end 5014.23
transcript.whisperx[148].text 是要讓年限知道這個計畫其實也不會啊你只要告訴我說你調低了門檻以後來申請的人大幅增加多少就表示調低門檻有效啊不是嗎原本是三個月現在調低成兩個月因為在關稅期間我們認為可以把它調低成兩個月
transcript.whisperx[149].start 5017.333
transcript.whisperx[149].end 5030.722
transcript.whisperx[149].text 所以這就是最好的宣傳調低門檻就是最好的宣傳這是我們已經做的對啊 我知道嘛所以我在問你說任性計畫如果在沒有花完的前提是不是大家就不會再用到你原本編的救安基金的這個計畫就這麼簡單的問題耶
transcript.whisperx[150].start 5035.239
transcript.whisperx[150].end 5053.181
transcript.whisperx[150].text 我们现在的确是优先在用任性计划预算所以救援基金有没有可能就不会花完了吗有没有可能有可能用的金额会降低对所以好啊那我们之后我们就来比较这两个执行率有可能你不费炊灰之灵的执行率就提高了好吗我们到时候再拉数据出来看
transcript.whisperx[151].start 5053.641
transcript.whisperx[151].end 5071.163
transcript.whisperx[151].text 我們在這個計畫裡面是我們當然是非常希望把它執行率給再拉高但是的確在執行率計算上面可能不是指不會啊依照你剛剛講的說法其實你一調低馬上就很多人來拉你剛親口講出來的對但是沒有辦法再調得更低因為
transcript.whisperx[152].start 5072.604
transcript.whisperx[152].end 5089.149
transcript.whisperx[152].text 當你把從兩個月要再降低成一個月的時候他可能會產生一些其他最後我們就來攤開來看到底什麼才是關鍵最後我們再把他拉出來看那另外其他剛剛三個你欠我的公文我也在麻煩您可以盡快謝謝你謝謝部長好謝謝陳金輝委員發言接下來請王育明委員發言
transcript.whisperx[153].start 5101.195
transcript.whisperx[153].end 5104.297
transcript.whisperx[153].text 謝謝主席我們有請部長有請洪部長部長早部長早部長我要先跟你討論有關於這個冷氣安裝直栽的這個問題我不曉得你自己有沒有看到光是今年下半年已經連續發生四起這個工人因為安裝冷氣然後墜落死亡的案件
transcript.whisperx[154].start 5128.836
transcript.whisperx[154].end 5155.339
transcript.whisperx[154].text 這個如果跟過去相較起來這個頻率算是增加的很多因為如果從2020年累積到現在是有17件 17人死亡但是光今年的下半年就短短的有4件我不知道你們有沒有去分析為什麼今年下半年這麼密集有這麼多起的因為冷氣安裝而死亡是 我們有觀察到這個事情那至於相關的分析的原因我請我們署長來
transcript.whisperx[155].start 5156.755
transcript.whisperx[155].end 5181.431
transcript.whisperx[155].text 你們有一個一個個案去分析嗎是什麼原因跟委員報告其實冷氣安裝的部分最主要是這個墜落的一個災害那它主要的問題是發生在現在的大概安裝在舊有的建築物就現行的建築物的部分在當時規劃設計的時候沒有考慮到說它的安裝的一個路徑這部分就能源必須要到這個所謂建築物外
transcript.whisperx[156].start 5182.371
transcript.whisperx[156].end 5196.466
transcript.whisperx[156].text 這個部分雖然我們過去已經辦了幾乎每一年都要辦這個宣導會或是講習那看起來是現在這些安裝的這些員工他不曉得說如何去防護自己的安全是年輕的師傅嗎 還是有經驗
transcript.whisperx[157].start 5198.828
transcript.whisperx[157].end 5208.602
transcript.whisperx[157].text 都有 我們現在解決方式是說希望藉助他們的製造商跟通路商還有相關在實際從事電器安裝的這些職業工會我們一起來討論怎麼樣來訂定一個
transcript.whisperx[158].start 5215.03
transcript.whisperx[158].end 5234.046
transcript.whisperx[158].text 一步一步的做這個安全的一個步驟的一個作為指引現在有關於冷氣裝修安全作業有訂指引的新北桃園他們其實有訂但是現在中央其實是沒有一套指引但是光訂指引它其實有一個問題它沒有強制力
transcript.whisperx[159].start 5234.767
transcript.whisperx[159].end 5249.673
transcript.whisperx[159].text 那如果說高空作業安全現在已經爆發這麼多例了那你應該只是一個指引嗎還是應該是訂定標準因為事實上這個2023年立法院的法治局其實就有提出這個報告
transcript.whisperx[160].start 5251.494
transcript.whisperx[160].end 5265.645
transcript.whisperx[160].text 那針對這一點現在如果你們定的還是指引的話他會有的問題就是缺乏強制力他只是一個guideline不是一個原則跟我說明的確因為這樣子的
transcript.whisperx[161].start 5269.228
transcript.whisperx[161].end 5284.59
transcript.whisperx[161].text 安裝冷氣墜落的事件其實他跟我們很多的事業單位他有一個比較明確的現場不太一樣所以其實在執行上面的確現在我們看到很多公協會跟我們反映的事情是其實相關的法規不是沒有但是
transcript.whisperx[162].start 5286.172
transcript.whisperx[162].end 5302.09
transcript.whisperx[162].text 他们现在很欠缺的事情是他们想知道怎么样子去执行这件事情在工程上面的做法在安装上面的做法他们现在很欠缺这件事情所以我们也因为这样我们也看到这个趋势所以我们预计会在今年底来提出指引那应该是19号对不对19号就开会
transcript.whisperx[163].start 5302.871
transcript.whisperx[163].end 5327.023
transcript.whisperx[163].text 11月19號我們就會找相關的工協會一起來討論你們應該是標準不要再是指引因為你們自己的那個議題研析裡面其中有一個探討研析我們找到資料就是這上面的他已經明確指出來了應該要研議訂定具強制力的作業標準加以規範確保冷氣安裝作業的安全
transcript.whisperx[164].start 5327.703
transcript.whisperx[164].end 5345.396
transcript.whisperx[164].text 所以不再是指引 而且之前立法院法治局也希望你們訂定的是標準所以我覺得這個部分不要輕忽我希望這個勞動部 既然你們要訂我覺得就往標準的方向去訂定 這是你們自己的研議出來的結論
transcript.whisperx[165].start 5346.897
transcript.whisperx[165].end 5367.373
transcript.whisperx[165].text 跟我們說明我們會在年底的時候我們會提出一套整體的這個職業安全跟職災的減災的計劃我們去預計年底那這部分其實我們也把它放在我們整體的減災計劃其中部分因為我們的確看到這些安裝家庭的設備那你們標準什麼時候要訂定
transcript.whisperx[166].start 5370.598
transcript.whisperx[166].end 5394.566
transcript.whisperx[166].text 我們年底會來訂定相關其實其實我們的指引並不是單純他不就是這個指引其實他是有一定的有一定的規範效力的對有嗎有違反違反會有罰則嗎指引有罰則嗎有強制力嗎在法規上不是指引實際上就是法規規定裡面的怎麼樣做去符合法規嘛裡面按照指引還是會扣回法規你們有開罰過嗎
transcript.whisperx[167].start 5397.818
transcript.whisperx[167].end 5418.119
transcript.whisperx[167].text 跟委員報告 如果按照這樣表示你們有開罰過跟委員報告 其實現在會定這個再定一步操作是因為他的作業實際上是一般的勞檢是在民宅上一般是很難去找到說他在屋頂或在哪裡作業所以你的法規就應該要再更嚴格一點嘛讓他們就是必須按照你的標準來走嘛
transcript.whisperx[168].start 5418.479
transcript.whisperx[168].end 5448.279
transcript.whisperx[168].text 我覺得就是反向思考就是因為你沒有辦法去勞解所以你更需仰賴一個比較有強制力的法規來要求不管你是任何的人你到家裡去安裝這個也是保護他是保護我們工人的安全跟文說明第一個事情我們在這個議題上面會非常非常需要跟相關的工協會合作這是第一個第二件事情我們當然可以來評估怎麼把這個強制性提高的做法我想把強制性提高的做法我們可以評估
transcript.whisperx[169].start 5448.619
transcript.whisperx[169].end 5473.205
transcript.whisperx[169].text 但的確就像剛剛大家也講到的確實在這樣子的案場裡面勞檢員要直接到現場是比較困難的檢察員到現場是比較困難的到現場他可能已經走了你要強化你的SOP還有你的法令另外一個我希望要求的是我現在已經看到在實務上面因為有一些老師傅就是慢慢退但是新的人進來他不見得那麼的閒熟所以在實務現場其實有這種跟不上的
transcript.whisperx[170].start 5476.266
transcript.whisperx[170].end 5480.869
transcript.whisperx[170].text 那針對這種高風險行業又跟不上青黃不接的我覺得你們的這個相關的職業訓練就應該要去強化配合工協會他們怎麼樣去吸引就是有這樣專業的人進來要不然我很怕我不知道這四例有哪幾例是比較生熟的如果是生熟的更會有這樣的一個問題它對於各方面風險的預判它經驗不足
transcript.whisperx[171].start 5498.058
transcript.whisperx[171].end 5508.945
transcript.whisperx[171].text 如果又沒有一個比較明確的標準跟作業跟這個企業主這邊願意去協助他就是說一個好的職業完整的職業訓練再讓他從事這樣的工作我覺得這個可能都還會再出現所以我希望這個漏洞從訓練強化的角度你們也應該要去強化好不好是好當然我們這個可以跟工協會來合作包括相關的課程
transcript.whisperx[172].start 5520.353
transcript.whisperx[172].end 5548.531
transcript.whisperx[172].text 接下來我要問的是有關於外籍移工權益的問題因為前陣子有這個勞團到勞動部去抗議那他其中一個議題就是提到說這一個因為這家公司呢因為他的員工外籍移工只要懷孕然後就被遣返那這個議題已經不是新議題了2018年到2021年監察院當時就已經糾正過就是說當時的懷孕終止契約離境大概有8000多人
transcript.whisperx[173].start 5549.071
transcript.whisperx[173].end 5564.518
transcript.whisperx[173].text 解約比例六成六那現在呢勞團又再度指出這樣一個問題我要問這個部長的是那現在呢今年以來有多少的外籍移工因為懷孕提前終止契約離境人數有多少這個我們
transcript.whisperx[174].start 5568.206
transcript.whisperx[174].end 5594.555
transcript.whisperx[174].text 我們可能要再統計一下再提供你們平常都不掌握的喔這個數據 這個也是大議題啊這個數據我們可能 老闆已經去你們部裡抗議了你們這一題還沒有準備這個數據可能我們會再要再要再那1995接收到多少這樣的一個投訴就是這些數據我們我們下禮拜前提供下禮拜你們平常都沒有在做統計喔怎麼可以不統計呢這個也是一個重要的議題啊我們會來統計啦 對
transcript.whisperx[175].start 5597.952
transcript.whisperx[175].end 5620.568
transcript.whisperx[175].text 那什麼時候要給本席 什麼時候數字可以出來 應該下週下週好這個要給本席我希望這個部長你要注意這一個是涉及到已經是違反我們現行的這個法令但是實務上還是持續這樣子做這個應該要去檢討不應該再存在這樣的一個現象有數字了是不是有嗎 我們還那個數字並不是完整的數字好
transcript.whisperx[176].start 5628.14
transcript.whisperx[176].end 5644.666
transcript.whisperx[176].text 希望你們多重視這個議題如果在委員會上回答不出來表示不夠重視接下來就是有關於這個我們的企業是不是有涉及到強迫外籍移工勞動的問題喔我想之前的巨大的這個案件讓大家看到
transcript.whisperx[177].start 5645.647
transcript.whisperx[177].end 5664.54
transcript.whisperx[177].text 對企業的影響坦白講也是損失重大因為美方他是採取這個直接查扣貨品的方式喔那到目前為止你作為勞動部部長我們有解了嗎這一個部分應該要怎麼樣去解號因為現在被點名的還有17家的企業
transcript.whisperx[178].start 5665.14
transcript.whisperx[178].end 5683.662
transcript.whisperx[178].text 那會不會都遭遇到同樣的一個狀況我們要怎麼樣事先去預防就是避免這個企業有強迫勞動的情況怎麼去輔導要求他們改善要不然這個其實都是我們台灣的經濟損失也很大勞工的權益也受損這是雙輸的局面
transcript.whisperx[179].start 5684.082
transcript.whisperx[179].end 5701.057
transcript.whisperx[179].text 跟委員說我們會有幾個做法同時在進行第一個部分其實我們現在已經在研議相關的行動指引那這行動指引預計什麼時候出來我想應該也許明年年初或者是一月左右可以出來一月一月可以出來
transcript.whisperx[180].start 5702.096
transcript.whisperx[180].end 5721.322
transcript.whisperx[180].text 我們的行動的指引目前正在研議中當然這部分我們也在跟經濟部這邊在做相關的會同那我們也會跟經濟部這邊來研議其實一個對企業的輔導計畫這是第一點第二點是我們其實現在也同時在針對我們的法規的機制在進行盤點的檢討
transcript.whisperx[181].start 5723.883
transcript.whisperx[181].end 5739.691
transcript.whisperx[181].text 那我們也希望在這個輔導的過程裡面一步一步也了解我們企業目前的狀況然後跟目前要求尤其是跟目前國際的要求之間的落差的情況這部分沒做第三點很重要是我們其實現在其實也希望能夠擴大
transcript.whisperx[182].start 5742.473
transcript.whisperx[182].end 5759.16
transcript.whisperx[182].text 國對國執聘的量能因為尤其是在仲介費相關的議題上面我知道擴大執聘這個我們都非常讚但只是你們現在一直都這個量能一直都是無法放大所以我們其實現在也很重要是我們現在也在跟包括跟企業界
transcript.whisperx[183].start 5760.12
transcript.whisperx[183].end 5781.596
transcript.whisperx[183].text 包括跟來源的母國我們都會針對擴大職聘這邊來簽訂更進一步的MOU或者是希望讓更多的企業可以了解職聘也是他們可以選擇的一個做法因為的確現在國際的要求是認為這個企業如果讓移工來負擔仲介費的話就會陷入這個強迫勞動的疑慮
transcript.whisperx[184].start 5783.576
transcript.whisperx[184].end 5805.075
transcript.whisperx[184].text 所以要避免這個疑慮的話就變成企業可能未來在這些聘僱過程裡面需要更多的承擔那如果企業願意選擇職聘的話這部分也是可以降低他的成本跟支出的做法所以這幾個方面都是我們現在在因應強迫勞動的議題國際上面非常關注強迫勞動議題的時候我們其實很明確的因應的做法那我最近其實也跟很多的企業在做相關的座談
transcript.whisperx[185].start 5805.865
transcript.whisperx[185].end 5824.583
transcript.whisperx[185].text 好我希望這一個指引你要盡快出來你剛說是醫院嗎因為這件事情我認為對台灣整體是有傷害的有對於勞動人權我們形象的傷害有對於我們實質經濟出口的一個傷害所以這件事情因為你又是主責的部長我希望
transcript.whisperx[186].start 5825.043
transcript.whisperx[186].end 5843.33
transcript.whisperx[186].text 你這邊要多花一點心力我們希望我們跟外籍移工都是雙贏不要演變成現在這個企業遭受損失然後勞犬又受到傷害雙數的局面好不好謝謝好謝謝王育民委員發言那接下來請廖偉祥委員發言謝謝主席請洪部長
transcript.whisperx[187].start 5855.25
transcript.whisperx[187].end 5855.991
transcript.whisperx[187].text 有請洪部長部長好 部長好 部長辛苦
transcript.whisperx[188].start 5864.195
transcript.whisperx[188].end 5888.428
transcript.whisperx[188].text 部長我首先第一題想要請問一下對於勞保政府負最終支付責任入法的態度因為今年5月的時候你也在本委員會有宣誓兩大重點第一個是否認現狀撥補就是改革第二個是對於最終責任入法採開放態度並且你也有承諾說三個月內要研議出結果
transcript.whisperx[189].start 5889.088
transcript.whisperx[189].end 5909.676
transcript.whisperx[189].text 那兩週前也有執政黨的委員在問行政院長院長也說對於這個回應也說絕對不會讓國人恐慌那我想要請問部長就是對於你之前在這個5月多的說要研議你們研議的結果如何那對於入法態度又是如何我想其實因為現在朝野的委員都有針對這個議題的提案
transcript.whisperx[190].start 5910.296
transcript.whisperx[190].end 5936.444
transcript.whisperx[190].text 那我想我們對於委員會的審議我們會尊重這個審議的結果那我們基本上不會反對這件事情所以部長不反對入法所以如果說委員會有牌您就會也算是不反對就會支持這樣子我們基本上不會反對這個狀況我們會持開放的態度然後也會尊重委員會的審議對 部長因為你還是跟五個五月多的時候講的講法是一樣啦所以就是想要問再更明確一點可以嗎
transcript.whisperx[191].start 5937.404
transcript.whisperx[191].end 5951.662
transcript.whisperx[191].text 就是政府負最終責任是現在政策很明確的立場政策上很明確的立場所以對於對於入法的部分對於相關的法治法當然我們我們不會表達反對不反對好
transcript.whisperx[192].start 5953.171
transcript.whisperx[192].end 5969.873
transcript.whisperx[192].text 那其實跟五月的時候差不多但是您現在就是更等於是說更應該說態度上面更可以認為說假如委員會討論來排審來做這件事情的話勞動部的立場是不反對並且是可以配合往前推進入法這件事是嗎
transcript.whisperx[193].start 5971.553
transcript.whisperx[193].end 5997.733
transcript.whisperx[193].text 這就是我們目前政策的立場所以我們當然不會對這件事情進行反對好 謝謝部長那再來部長我也要問一下因為首先我也要謝謝部長其實前幾週我們在做這個外送平台相關專法討論的時候不管是專報 公聽會其實大家也都是正面的積極的態度我也感受到部長也有這個積極的態度但是本席要在這裡問請問一下你們的版本
transcript.whisperx[194].start 6001.996
transcript.whisperx[194].end 6026.476
transcript.whisperx[194].text 預計是什麼時候要預告我們希望這一兩週 這一兩週嗎可不可以再具體一點因為 這一週有機會嗎還是 更為說明因為我們其實真的在做最後的幾個利害相關方的意見的收整尤其是裡面涉及到很多法制性的文字所以因為就行政部門來說我們提出一個版本會需要比較
transcript.whisperx[195].start 6027.978
transcript.whisperx[195].end 6042.594
transcript.whisperx[195].text 會有一定的程序跟嚴謹謝謝部長我都尊重包括現在這些相關的條文的文字我自己也都在確認但因為今天禮拜三所以我認為可能應該會是在這一兩週所以最晚不會超過下個禮拜五就會預告對不對我希望是這樣子
transcript.whisperx[196].start 6043.735
transcript.whisperx[196].end 6070.552
transcript.whisperx[196].text 那我還是希望可以部長可以盡速一點如果最後這幾天確認一下我想這個也很多期待但是關於這個部分我們的同仁每天都為這件事情所以我特別這個表達這個我覺得是肯定也希望說我們可以再加速一點但是因為你也說到最後的階段所以我們再問一點細節的部分其實有關於這個部分我想大家最關心的其中之一是所謂最低報酬的部分
transcript.whisperx[197].start 6071.152
transcript.whisperx[197].end 6088.137
transcript.whisperx[197].text 那我想要請問一下部長你們目前的版本有沒有預計採什麼樣的方案究竟是最低的這個時薪薪資保障呢還是是所謂的每單三分之一最低基本工資的這個限制我想要請問還是有其他的方案
transcript.whisperx[198].start 6089.037
transcript.whisperx[198].end 6104.616
transcript.whisperx[198].text 這個部分我是想要追問一下因為其實這個是關鍵中的關鍵我想旁邊也都在點頭其實委員我們現在正在最後收斂就是針對這個部分因為每一個做法說實話這裡面沒有完美的做法每一個做法都有他的優點跟缺點
transcript.whisperx[199].start 6105.757
transcript.whisperx[199].end 6124.157
transcript.whisperx[199].text 都有点跟缺点就是刚才在讲到委员刚才讲到的几个保障的做法都有它的优点跟缺点所以我们也是在最后评估这个保障的做法的方向目前也是对所以我就是特别想问你们大概有没有什么方向就是说因为你在评估其实委员你问得很精准其实这就是我们现在为什么
transcript.whisperx[200].start 6125.098
transcript.whisperx[200].end 6138.565
transcript.whisperx[200].text 還需要一點點時間再去評估這個每一個優缺每個做法因為對於不同的外送員來說不同處境的外送員來說可能每一個做法都有不一樣的效果其實那我再進一步問一下
transcript.whisperx[201].start 6139.83
transcript.whisperx[201].end 6154.197
transcript.whisperx[201].text 那你們有沒有去真的很精準的計算因為有關於最低報酬的部分其實這個跟他在真正的成本譬如說外送員在做這個跑單的這個成本也有很大的關係對吧那你們有沒有去精準的計算
transcript.whisperx[202].start 6155.017
transcript.whisperx[202].end 6180.719
transcript.whisperx[202].text 包含他當然至少是外顯的成本那隱藏的成本當然也要算進去我想要請問你們有沒有去精準的計算他們現在的成本是多少我所謂外送員因為外送員的成本對 外送員的成本其實你各方的成本都要掌握啦你才知道說有沒有人不願意釋放利潤好 那我先針對外送員的部分你有沒有去掌握因為這跟你要訂哪一個方向也有很大的關係
transcript.whisperx[203].start 6181.44
transcript.whisperx[203].end 6206.605
transcript.whisperx[203].text 其實這部分因為交通部這邊因為針對比方說你機車 使用機車相對的成本 比如油耗或者是你要去做相關的維修這部分其實交通部有把它相對機車的成本給算出來那請問有沒有 你現在有沒有資料我們當然有啊但是詳細的數字交通部這邊有提供可不可以提供給本席辦公室因為我其實有精算了我大概提供給你們 假設是
transcript.whisperx[204].start 6208.385
transcript.whisperx[204].end 6222.581
transcript.whisperx[204].text 油耗燃油的費用我算起來一年他假設每日他是很用心全力的在跑好了高度的依賴者他一年下來燃油費可能是四萬五千八
transcript.whisperx[205].start 6223.322
transcript.whisperx[205].end 6238.927
transcript.whisperx[205].text 那再來保養費可能是一萬三千多其實這個還不含換輪胎可能是換機油的部分然後再來有折舊對不對這個機車的折舊費兩萬六千多那再來還有包含他的通訊費用然後以及他的設備費用
transcript.whisperx[206].start 6240.447
transcript.whisperx[206].end 6256.693
transcript.whisperx[206].text 還有他的勞保費用 健保費用然後還有強制險或者是意外險等等其實一年下來他的所有費用大約是11萬左右那11萬如果用全台的勞工時數來算
transcript.whisperx[207].start 6258.234
transcript.whisperx[207].end 6272.662
transcript.whisperx[207].text 你如果是除以2000個小時左右好了你要除以2030個也可以他其實每一個小時的成本就是五六十塊對不對所以你師長也在旁邊一直頻頻點頭他大概就是五六十塊每個小時他要跑就要負擔
transcript.whisperx[208].start 6273.923
transcript.whisperx[208].end 6292.613
transcript.whisperx[208].text 所以其實這個部分一定要有精準的掌握你才知道怎麼訂定所以我剛剛要表達的是這個意思另外還要精準的掌握平台它每一單是多少錢因為它每一單目前我以本席掌握的數據每一單大概是300塊可是它還會另外收配送費
transcript.whisperx[209].start 6293.553
transcript.whisperx[209].end 6315.721
transcript.whisperx[209].text 好所以其實我們現在要我特別要問部長這一塊就是因為現在可以感覺出來推到現在會有帶風向的狀況就是說我們要怎麼避免在推動因為我想這是朝野大家都有共識啊但你要怎麼避免在推動的過程中這個相關的平台就說我就是全力全部轉嫁給消費者這件事情部長你們有沒有什麼看法
transcript.whisperx[210].start 6317.247
transcript.whisperx[210].end 6343.333
transcript.whisperx[210].text 跟文說明第一個因為這個外送的這個事業這個數位平台的運作的狀況他其實涉及到了就像之前講到的四方所以我們其實在現在的專法裡面其實我們當然也是希望能夠去處理一方面是在四方的大家都講四方的平衡但是我們也知道在這裡面相對比較強勢的是平台
transcript.whisperx[211].start 6343.933
transcript.whisperx[211].end 6359.49
transcript.whisperx[211].text 最弱勢的是我認為最弱勢的是外送員沒錯那怎麼樣保障外送員的基本權益保障基本權益同時對於其他的包括消費者包括對合作商家他們的權益也透過定型化契約的方式去做予以一些
transcript.whisperx[212].start 6362.034
transcript.whisperx[212].end 6375.533
transcript.whisperx[212].text 部長這個我想我們都討論很多但是您現在講到這裡還是比較屬於大方向指引或是比較空泛一點但我相信你們既然到專法最後階段你們應該掌握更多的細節所以剛剛我有說到就是有關於
transcript.whisperx[213].start 6376.754
transcript.whisperx[213].end 6400.483
transcript.whisperx[213].text 剛剛的成本 外送員的成本以及外送平台他每一單到底多少錢我剛剛也提供給你本席我不是主管機關但是我也去研究國際上的資料所以我告訴你說可能以台灣來講他每一單Maybe是300塊還要再另外加配送費那你一定都要去掌握你才有辦法權衡我們有這個跟相關的主管機關其實他們也提供相關的數據所以部長我要跟你說一件事情就是我假設
transcript.whisperx[214].start 6401.303
transcript.whisperx[214].end 6426.27
transcript.whisperx[214].text 用一單300塊來簡單來算一下就是現在外送員會被加單所以他可能20分鐘會被送三單就要求他送三單可是他也有拿出這個相關的記錄結果他送了三單之後他只收到45塊好 那我就用數學算給你聽現在平均他跟台灣的店家收費的乘數可能是30%到35%所以他三單 我剛剛說一單假設平均是300塊好了就是900塊
transcript.whisperx[215].start 6427.671
transcript.whisperx[215].end 6439.564
transcript.whisperx[215].text 900塊如果他跟每一個商店抽了35%好了就算是30%好了也就多少 300塊嘛對不對他還有另外的配送費可是他最終只給了外送員可能是45塊 50塊
transcript.whisperx[216].start 6442.788
transcript.whisperx[216].end 6467.416
transcript.whisperx[216].text 所以我必須要跟部長特別今天要再特別講這個議題就是說我們在推動專法的時候你剛剛說要平衡四方利益嘛我想你也最擔心的就是說你推下去之後平台將所有的費用說我要提高這個消費者要負擔更多我相信你也有在擔心這個事所以我今天要告訴你的就是說為什麼要把這些東西算得很清楚推出來給社會大眾溝通就是說
transcript.whisperx[217].start 6468.669
transcript.whisperx[217].end 6489.47
transcript.whisperx[217].text 推下去之後照理說不可能平台應該也不可能全部都轉嫁到消費者身上我跟委員說明其實委員在上週公聽會的時候其實也有講到希望平台業者要提供相關的數據大家去做確認所以這時候也會有各種算法比方說委員也提供你花了心力去做的算法
transcript.whisperx[218].start 6491.13
transcript.whisperx[218].end 6512.775
transcript.whisperx[218].text 因為這關乎到運輸成本的部分所以運輸成本的部分交通部也會提供他相關的估算的方法來讓我們知道所以這裡面會有各種不同的算法我覺得彼此可能需要做一些確認謝謝 所以部長我也希望您可以提供相關的數據既然他們提供給您可不可以也提供給本席辦公室好不好那今天可不可以就今天下班前就先提供給本席辦公室你們現在手上有的相關資料
transcript.whisperx[219].start 6513.955
transcript.whisperx[219].end 6540.481
transcript.whisperx[219].text 明天 這一週我們提供這一週提供給本席好不好我們可以確認一下因為我其實研究了各國的案例我本席是蠻目前看起來蠻推薦的這個紐約的模式我覺得看起來是它既保有了彈性給平台它對於外送員又有基本的有效的時薪的保障那我建議說不曉得你們有沒有研究這個模式所以請你們可以去了解一下
transcript.whisperx[220].start 6541.38
transcript.whisperx[220].end 6563.56
transcript.whisperx[220].text 有跟委員說我們現在對這模式也非常熟悉那的確它在一定的保障下但是它的確也會有一些相應的配套比方說它也會遇到平台會設整體外送員的總量的管制其實有這種狀況所以我要跟委員說明的事情是其實目前我們看到的幾個保障的方向每個保障的方向都有它的優點缺點
transcript.whisperx[221].start 6565.097
transcript.whisperx[221].end 6591.909
transcript.whisperx[221].text 很難有一個一個保障的方向或一個保障的方案他是所有部分都是因為我們只能夠選最佳的對沒錯所以我們只能選最佳的可是因為對不同的外送甚至對不同情境他跑的比較少的或比較全職在跑的他可能對同時對一個部分的優缺點來說他的感受會不一樣所以這也是我們必須總體評估的一部分所以我剛才一直特別問你們現在往哪個方向去是是是好所以但是你們還是沒有回答本席不過沒關係請你們把
transcript.whisperx[222].start 6593.755
transcript.whisperx[222].end 6621.184
transcript.whisperx[222].text 你如果現在不方便講請你們把你們相關的數據和你們大概的方向我們可以給本席辦公室然後我們來討論如果相信我們朝野都希望這件事情有一個最佳解我們認為這個議題一定是需要朝野合作的然後需要有一個最佳解希望可以提供給本席辦公室好那再來呢我知道時間到了但是最後問一下有關於這個跨國勞動力精進方案
transcript.whisperx[223].start 6622.605
transcript.whisperx[223].end 6643.941
transcript.whisperx[223].text 我想要先請問一下部長本方案應該是希望可以提供加薪給勞工讓勞工可以加薪理論上是希望給本國籍的基層勞工加薪對吧對就是相對低薪的不是高薪的不是主管對是要低薪的是在比較是在企業的最在薪資的最低層的部分那我們會來確認跟檢視這部分
transcript.whisperx[224].start 6646.883
transcript.whisperx[224].end 6673.178
transcript.whisperx[224].text 謝謝我相信這樣這個基本上的政策目的也是希望這樣所以我們也希望讓基層勞工有感加薪然後加薪有感提升整體的薪資水準但是我也想要進一步問那你怎麼防止雇主以薪資結構調整的方式來避免實質加薪好譬如說他提高底薪但同時減少其他的津貼補助又或者是因為明年上路所以他現在預期他是不是有可能提早我說我就先
transcript.whisperx[225].start 6674.119
transcript.whisperx[225].end 6693.133
transcript.whisperx[225].text 我就先這個調薪下來然後未來再加薪回去有沒有可能發生這類的事情啊那發生了之後你們要怎麼去檢核查核跟文說明齁其實在整個企業的經營裡面他的薪資結構當然包括很多部分可是我想我們會透過
transcript.whisperx[226].start 6694.654
transcript.whisperx[226].end 6709.78
transcript.whisperx[226].text 比方說像我們的投保的勞保的資料來去做相關的檢核那如果我們發現他有這個假加薪或者是這種規避的做法的話當然我們就會去撤銷他的名額那第二個也是剛才委員在前一張其實有看到
transcript.whisperx[227].start 6710.78
transcript.whisperx[227].end 6726.041
transcript.whisperx[227].text 我們其實是對於他如果增加的名額在三年後他其實還是要針對一定的就是同樣等同的名額再加薪一次一樣是兩千塊那這個加薪的幅度的高或低其實這當然我們做了很多的討論
transcript.whisperx[228].start 6727.623
transcript.whisperx[228].end 6733.391
transcript.whisperx[228].text 因為如果也會有外界說那是不是有可能把這個加薪的幅度再高一點比方說我們現在2000塊有時候是不是要3000塊5000塊可是當3000塊5000塊的時候很可能這個會受到加薪的本國勞工就會變少
transcript.whisperx[229].start 6743.004
transcript.whisperx[229].end 6760.594
transcript.whisperx[229].text 甚至加薪的幅度更高的時候企業就會產生更高的去做某一種規避行為的誘因所以這裡面的確這個加薪的幅度也是我們反覆在討論怎麼樣是一個相對比較適當的幅度的做法但是我們另外也加了三年後還要再加一次的這樣的做法
transcript.whisperx[230].start 6761.414
transcript.whisperx[230].end 6787.228
transcript.whisperx[230].text 其實部長這個問題跟剛剛我們在討論所謂外送員專法這對於全面的盤點或數據的盤點也有蠻大的關係嘛譬如說各個產業嘛所以像你剛剛說的為什麼你訂的是2000塊不是5000塊你可能希望的是全面大家都可以更多人 更多人的勞工可以受到加薪嘛對不對 對所以我就想問因為其實還是有很多的民團在質疑勞動部有沒有全面詳細的盤點
transcript.whisperx[231].start 6789.289
transcript.whisperx[231].end 6811.637
transcript.whisperx[231].text 那請問你們現在盤點的有沒有很具體的相關數字可以提供給本席辦公室各個產業然後以及就是你們目前在做這個方案的時候你背後的數據支撐是什麼跟文說明其實如果從這張投影片其實大家我們可以看得出來我們在方案的時候很重要是本勞的權益優先其實過去在開放外籍移工的時候
transcript.whisperx[232].start 6812.797
transcript.whisperx[232].end 6830.274
transcript.whisperx[232].text 就會去做一定的成本的要求盡量避免可能會對於本國勞工的權益造成影響以前可能是叫做透過像extra這樣的做法就是他可能要多繳救安費的做法那現在其實我們提供的是有點像是另外一種extra他是利用幫本國勞工加薪的做法
transcript.whisperx[233].start 6831.155
transcript.whisperx[233].end 6848.59
transcript.whisperx[233].text 去取得多一点的名额当然我想我们其实这边也会设定查核的机制透过我们在劳保里面的资料去查核所以一样就是说如果发现是有规避行为或者是假加薪的话我们其实就会直接取消它这个名额
transcript.whisperx[234].start 6849.11
transcript.whisperx[234].end 6877.2
transcript.whisperx[234].text 好 謝謝部長我其實就是想要說因為做任何的政策你們我相信你們背後要有相關的數據做支撐所以希望部長可不可以也提供給本席辦公室你目前針對這個精進方案你們背後用什麼數據去支撐說你們想要這樣做包含著各個產業究竟缺多少工然後你這樣子加薪各產業受惠的多少我相信這個你們應該都有做精進的很詳細的數據分析可不可以提供給本席辦公室
transcript.whisperx[235].start 6877.62
transcript.whisperx[235].end 6893.924
transcript.whisperx[235].text 我們把我們怎麼樣去考慮這件事情的一些原則讓委員這邊可以知道 好 謝謝好 謝謝廖委長委員發言那委員會宣告在邱正軍委員詢答後休息10分鐘接下來請邱正軍委員發言主席好
transcript.whisperx[236].start 6906.38
transcript.whisperx[236].end 6936.117
transcript.whisperx[236].text 我等部長喝水 部長請 請部長謝謝邱委員部長好我想請問一下 你們今年有編預算9月說要去大陸 結果有去嗎後來有去嗎應該是沒有吧重規有沒有去 沒有沒去啊那你們今年就沒去 為什麼明年又編了呢又編了9月份要去啊
transcript.whisperx[237].start 6938.422
transcript.whisperx[237].end 6954.017
transcript.whisperx[237].text 其實這個每年編列這個預算並不是說每年就一定會有計劃會去明年是APEC明年會去 對所以你們也覺得說過去不會危險嘛這正常交流不會造成這個威脅會不會會不會擔心啊
transcript.whisperx[238].start 6956.479
transcript.whisperx[238].end 6973.928
transcript.whisperx[238].text 我們希望這個中國政府不應該把這個他們會反對你去嗎不會吧正常的交流上面對啊 他們會嗎應該不會吧所以你們才敢去啊不然你敢去嗎這其實都是我們認為其實它是可以創造
transcript.whisperx[239].start 6975.285
transcript.whisperx[239].end 6993.767
transcript.whisperx[239].text 台灣正常有序交流的一種做法所以當然我們這個希望中國應該要我們總統講說今天是沈伯陽這樣子國際交流的原則對啊 總統好像有講過說今天是沈伯陽 明年就是你所以我相信你是部長不會明知道有危險還讓同仁去嘛 對不對
transcript.whisperx[240].start 6994.588
transcript.whisperx[240].end 7021.905
transcript.whisperx[240].text 表示說正常交流我們還是可以說開大門走大路的我們希望一個對等有序的交流中國政府應該要秉持一個相對比較開放的心胸讓一個所以他現在反對你去嗎現在應該還沒有這樣子的表達還沒嗎現在沒有這樣的表達但我們希望一個正常有序對等的交流
transcript.whisperx[241].start 7022.816
transcript.whisperx[241].end 7043.655
transcript.whisperx[241].text 然後這個我講這個也沒別的意思就是說希望這個就是說本來也沒那麼嚴重不要用這種情緒這個勒索來嚇我們台灣人其實正常交流應該是沒有問題的那我們接下一題就是說在你們的預算裡面勞動資訊業務這個部分主要就是電腦相關設備跟資安對吧
transcript.whisperx[242].start 7047.931
transcript.whisperx[242].end 7070.669
transcript.whisperx[242].text 應該是那113年決算你們大概花了1000多萬那114年就是今年編列的1400萬元到了明年115年你們編列的這個預算大概8700多萬 暴增6.2倍的原因是什麼部長你都不知道
transcript.whisperx[243].start 7073.5
transcript.whisperx[243].end 7098.412
transcript.whisperx[243].text 這邊跟委員補充一下就是我們原本在勞動業務的共通性的那些資訊原本我們是放在就業安定基金費裡面那因為後來重新檢討之後決定這些比較跟就業安定基金相關比較沒有直接關係的就往公務員所以你這些錢要做什麼一樣也是在維運整個勞動業務的共同資訊平台
transcript.whisperx[244].start 7101.013
transcript.whisperx[244].end 7124.748
transcript.whisperx[244].text 那是什麼東西你可以講清楚一點嗎其實狀況是這樣就是因為過去其實相關的支出其實是用救安基金在支出可是我們從今年初從去年底開始檢討救安基金的使用以後我們就認為有些如果可以用公務預算支出的就盡量的移到公務預算支出所以我們去跟族種去爭取
transcript.whisperx[245].start 7125.871
transcript.whisperx[245].end 7149.283
transcript.whisperx[245].text 一些其實應該其他部會每一年都有大概六七千七八千萬的這個預算要去換電腦比方說很多系統不要違法雇主的查詢因為在勞動這邊其實有很多相關的資訊系統必須去做維護更新甚至大家對於很多的揭露有更多的現在有更多的要求部長你們你們這樣做我當然是贊成就是說你們不應該在就就按機會這個基金裡面來動用這些錢
transcript.whisperx[246].start 7152.364
transcript.whisperx[246].end 7180.564
transcript.whisperx[246].text 那你把編列出來 這八千多萬那我覺得你每年在編列八千多萬元的這個部分呢應該是構置什麼防火牆啊 文書軟體啊資料庫軟體更新 這樣吧是這樣嗎也不止也不止 還買什麼東西就是包括系統的所以你們有細項嗎你們有細項嗎我們可以還是整包 一包就是八千七百多萬不是不是不是不要像買福袋一樣 裡面什麼都有啊
transcript.whisperx[247].start 7183.906
transcript.whisperx[247].end 7201.996
transcript.whisperx[247].text 這個治安的問題很嚴重治安沒有把它當作福袋我是覺得當然啦這個賬戶越清楚越好治安的工作要做得扎實不是靠像福袋不要買了就一直撈就有那部長那我再問你這幾天你們召開這個不是我問別的好了就你召開這個
transcript.whisperx[248].start 7204.345
transcript.whisperx[248].end 7212.416
transcript.whisperx[248].text 勞動力政策的諮商小組會議同時決定要打開製造業跟一般營造業的移工限制確定要這樣做嗎
transcript.whisperx[249].start 7215.52
transcript.whisperx[249].end 7238.047
transcript.whisperx[249].text 我們其實這次打開的主要是針對技術人力的上限就是我們把技術人力原本25%的上限然後把它打開我看到你的兩個都是移工的政策重大鬆綁不只是調整配額 直接會改變產業用工的結構除了這場會議之外 你們還做了哪些具體的評估
transcript.whisperx[250].start 7239.645
transcript.whisperx[250].end 7263.934
transcript.whisperx[250].text 呃 現在委員你在簡報上面其實這是針對營造業這是針對那時候7月的時候那時候應該是丹納斯颱風那在台南造成很大的這個很多的 你們是因為災後重建嘛對不對 當時所以營造業的部分是如果營造業業者下的移工投入到災後重建的話他如果需要增加名額的話不受這15000名的限制所以不受嘛 那你現在你要打開放多少
transcript.whisperx[251].start 7265.154
transcript.whisperx[251].end 7280.506
transcript.whisperx[251].text 這個其實要看是要看營造業或者是目的世界主管其實應該是說我看了你們今年的這個來統計結算到9月那大概是9000多人申請大概是有9000多個名額那你的上限是15000
transcript.whisperx[252].start 7281.787
transcript.whisperx[252].end 7304.395
transcript.whisperx[252].text 一萬五嗎那你就還沒達到啊還沒達到標那你的意思為什麼要去又要跳過這個機制來跟我們說明一萬五的名額是我們已經開放的對但是確實之前有那目前是9680的對之前因為之前我們一直跟這個國土署在討論怎麼讓這個一萬五的名額能夠更有效的運用
transcript.whisperx[253].start 7305.68
transcript.whisperx[253].end 7325.128
transcript.whisperx[253].text 那但是現在在討論的災後的同路的名額跟這一萬五的名額比較是兩件事情也就是說那我請問部長假如這個災後重建是不可能持續在做嗎不是永久都有嗎那如果災後之後就是他這個災後重建完成之後那這些一共怎麼辦
transcript.whisperx[254].start 7326.807
transcript.whisperx[254].end 7355.335
transcript.whisperx[254].text 當然就會留下來但是這也是我們希望能夠給當初願意幫忙災後重建的營造廠的一個誘因因為其實在這個重建過程裡面需要很多營造廠來協助因為你災後重建完成之後你們又把它留下來嘛那乾脆就不要用災後來當幌子嘛對不對委員這絕對不是幌子那你用因為如果沒有投入災後重建的業者的話就沒有辦法享有這個可能這個天花板的調整
transcript.whisperx[255].start 7356.275
transcript.whisperx[255].end 7374.323
transcript.whisperx[255].text 所以他們我現在的重點是在說你現在讓他進來了進來之後你又讓他回到一般的勞工一般的製造業或者是其他地方去嘛對不對你會讓他留下來因為沒有那麼多災後重建啊跟委員說明他其實他如果做完災後重建以後這個營造廠他還是要有工程啊
transcript.whisperx[256].start 7377.845
transcript.whisperx[256].end 7390.225
transcript.whisperx[256].text 所以他就可以繼續做那他如果這個工程他不是災後不是因為災後重建所以都可以做就對了那你幹嘛不直接開放就讓這些營造業能夠申請
transcript.whisperx[257].start 7393.513
transcript.whisperx[257].end 7418.368
transcript.whisperx[257].text 跟委員說明目前其實我們已經開放1.5萬人那現在我們是鼓勵當初願意投入到災後重建這有公益性質的協助的工作的營造廠讓他們在名額上面有多一點的我覺得這個是多此一舉直接從那邊來管理這樣會不會比較好因為我擔心說你這個等於是你用這個災區重建當成長期鬆綁的一個藉口
transcript.whisperx[258].start 7419.388
transcript.whisperx[258].end 7444.51
transcript.whisperx[258].text 那到時候你這個一萬五千人如果申請已經達標了那後來又利用這個然後一直無限上綱嗎那這個就沒完沒了委員這個在區的重建在這個在區重建的工作其實它需要的工程量跟它需要的勞動力量真的比較大所以我們用這個方式我是不反對你們去開放這個但是還是要做限制不要說這個臨時開放變成永久使用
transcript.whisperx[259].start 7445.271
transcript.whisperx[259].end 7457.135
transcript.whisperx[259].text 我們會做一定的把控對啊 我覺得你們辦法還是要定出來我們會做一定的把控但是這個打開的措施你這邊開一個口這邊又開一個到時候兩個都這個打開的措施比較是為了讓
transcript.whisperx[260].start 7460.123
transcript.whisperx[260].end 7489.283
transcript.whisperx[260].text 營造廠能夠願意投入到再去重建有多一點的誘因當初的利益是在這件事情上面的最後一個啦你們說的政策是要幫本國有一個政策就是說幫本國勞工加薪結果是一個本國勞工加薪2000塊你們就可以多申請一個移工這樣是嗎你們的方法是這樣嗎要看哪個行業目前是在製造業部分是幫製造業嗎一幫一個本國相對低薪的勞工加薪的話他可以取得多一個就兩天就可以了是不是對那為什麼是兩天
transcript.whisperx[261].start 7490.664
transcript.whisperx[261].end 7515.346
transcript.whisperx[261].text 第一個我們也評估過要不要其他更高的金額怎麼評估的但是第一個我們認為這2000的我覺得很奇怪為什麼要2000塊如果高一點的話可能會讓願意去為本勞工加薪的企業的人數會在減少所以我們是主要那未來你們怎麼去督促怎麼去監督這些業者我們會確認在我們的系統裡面去確認有確實加到本勞的加薪以後
transcript.whisperx[262].start 7516.127
transcript.whisperx[262].end 7540.286
transcript.whisperx[262].text 你才能夠我們才會給他名額的合法會不會他們表面上加了之後然後呢加班費啊津貼什麼獎金都壓下來的話呢如果我們去查核如果假加薪的狀況的話對這種變相的你們怎麼去查如果我們透過我們的系統去查核查到之後咧如果他有假加薪的狀況下我們就會取消他的名額有沒有法則我們就目前說就是用取消名額的方式就取消那這樣大家不會啪抓到再說嗎不是這樣嗎
transcript.whisperx[263].start 7543.895
transcript.whisperx[263].end 7556.262
transcript.whisperx[263].text 會停止兩年申請我覺得這個政策要明確啦好不好讓大家能好做事好 謝謝部長好 謝謝邱委員 謝謝部長那我們現在休息十分鐘 謝謝
transcript.whisperx[264].start 8313.052
transcript.whisperx[264].end 8320.624
transcript.whisperx[264].text 好 各位同仁請各位同仁官員請請就座好不好
transcript.whisperx[265].start 8322.068
transcript.whisperx[265].end 8348.422
transcript.whisperx[265].text 我是不是請我們圖委員還有我們這個勞動部相關的官員我們能不能起立一下好不好就是剛剛早上有特別從委員提到就是胃環委員會在此超過25年的我們這個蔡鋒如科員因病來過世畢竟她在立法院也在胃環盡心盡力所以是不是我們一起來
transcript.whisperx[266].start 8349.653
transcript.whisperx[266].end 8356.243
transcript.whisperx[266].text 為他禱告 也默哀一分鐘表示對他這幾年來的這樣的一個投入跟付出謝謝 我們現在開始
transcript.whisperx[267].start 8422.981
transcript.whisperx[267].end 8432.304
transcript.whisperx[267].text 好 謝謝大家 我們希望大家的意念讓他可以無怪無礙 一路好走 謝謝接下來請突巡局委員來做詢問好 謝謝主席 那麻煩請我們勞動部洪部長還有勞發署黃署長還有署長
transcript.whisperx[268].start 8458.679
transcript.whisperx[268].end 8481.013
transcript.whisperx[268].text 土委好好 洪部長因為最近我們在臉書社團有看到一個具名的貼文那針對這個當事人描述他透過我們台中的某仲介來聘用家庭看護移工來照顧家裡中風的長者那他在看到這個
transcript.whisperx[269].start 8482.438
transcript.whisperx[269].end 8500.449
transcript.whisperx[269].text 他聘用的家庭看護移工他履歷中有載名他是有經驗的照顧照護工作長者有照護工作經驗的那後來他實際聘用之後他發現這個聘用的家庭看護移工
transcript.whisperx[270].start 8501.86
transcript.whisperx[270].end 8527.025
transcript.whisperx[270].text 照顾能力跟卫生观念都很差而且也没有能力为病患备餐后来询问过这个家庭看护乙工之后这个乙工也亲口承认他这个照顾经验照护经验是印尼仲介方编造伪造的事实上他完全没有经验也是第一次出国第一次做看护
transcript.whisperx[271].start 8527.825
transcript.whisperx[271].end 8551.191
transcript.whisperx[271].text 那後來當事人在協調廢聘跟賠償損失的協調過程中最後問這個仲介負責人他說他是轉達印尼仲介方的履歷他並沒有能力去核實 他只是推薦所以最後這仲介方也只同意
transcript.whisperx[272].start 8552.273
transcript.whisperx[272].end 8578.947
transcript.whisperx[272].text 退還他當初的仲介費27000塊那對於這履歷不實所造成他造戶成本完全沒有處理那在這60天到90天的空窗期當事人勢必要去花更多高額的錢去請這個台籍看護那後來據我們了解這一家仲介公司其實在
transcript.whisperx[273].start 8580.322
transcript.whisperx[273].end 8608.257
transcript.whisperx[273].text 我們的評鑑裡面我們勞動部的評鑑裡面它五年都是最高分的A級還有兩年還是GU列為免評那其中在顧客服務裡面它幾乎是拿滿分那我想請問一下部長那像發生這樣子的事情它的履歷偽造編造不實造成我們當事人他這些的損失
transcript.whisperx[274].start 8609.98
transcript.whisperx[274].end 8628.588
transcript.whisperx[274].text 那到底是誰的責任是跟委員說明有關這個仲介提供不實資料的部分依照救福法第40條第一項第8款可以大聲一點嗎好像太小聲依照就業服務法第40條第一項第8款
transcript.whisperx[275].start 8630.612
transcript.whisperx[275].end 8651.355
transcript.whisperx[275].text 對於接受委任辦理聘僱外國人之申請許可招募引進或管理事項提供不實資料的部分我們是可以處罰的依照第65條我們的罰環可以處30到100萬那這是罰環的部分那行政處罰的部分我們也可以視況處以停業跟最重可以到廢止
transcript.whisperx[276].start 8652.426
transcript.whisperx[276].end 8667.079
transcript.whisperx[276].text 所以其實對於仲介所提供這個履歷不實他是有罰款的那為什麼我們台灣這個仲介說他說這是印尼仲介提供給他的他沒有辦法核實他也沒有辦法處理
transcript.whisperx[277].start 8668.48
transcript.whisperx[277].end 8689.829
transcript.whisperx[277].text 他只是負責轉介 負責推薦那是這樣子的嗎有關這個部分我想我們依照這樣的個案我們都會交由地方政府去查查那如果查查確實他的資料是提供不實資料的時候我想我們會有後續的處分所以其實我們本身裡面是有這個罰則的是可以處理的那我想請問一下如果這個案例這個過程是事實那到底是
transcript.whisperx[278].start 8690.97
transcript.whisperx[278].end 8717.302
transcript.whisperx[278].text 台灣仲介方有責任嘛他只是把仲介費推完就沒事了嗎如果說海外的仲介也有過失那原則上我們對海外仲介也有管理我們也會處以一部分的停止或是撤銷他的認可那像說台灣這邊的仲介他只是推薦轉介他沒有核實的義務是這樣子嗎我想可能這個還是要就個案事實去做釐清看責任的歸屬是哪一方
transcript.whisperx[279].start 8718.482
transcript.whisperx[279].end 8733.36
transcript.whisperx[279].text 对啊所以刚委员有提到说有关雇主的损失那因为基本上这是属于民事契约所以雇主一样可以向劳工提出求偿所以我觉得我们劳动部尤其劳发组这边要看一下因为我们检视你们
transcript.whisperx[280].start 8734.461
transcript.whisperx[280].end 8755.761
transcript.whisperx[280].text 私立就業服務機構從事跨國人力仲介服務品質評鑑指標裡面針對顧客服務的這個項目裡面並沒有要求仲介必須查核移工的履歷提供正確的訊息所以難怪在你們評鑑裡面它在顧客服務幾乎是快滿分
transcript.whisperx[281].start 8757.422
transcript.whisperx[281].end 8778.019
transcript.whisperx[281].text 還有在勞發署提供的外勞與仲介契約僱主與仲介委任契約的範本裡面也沒有要求外勞有義務提供真實履歷或者仲介有核實外勞履歷的義務條款所以契約裡面也沒有這個條款你們評鑑裡面也沒有要求他們要這樣去做
transcript.whisperx[282].start 8779.308
transcript.whisperx[282].end 8804.706
transcript.whisperx[282].text 報告委員基本上這是基本法尊那KPI可能會針對需要在特別強化的部分去做核分加減分那委員的指教的部分我想我們目前也正在針對評鑑指標全面的在進行檢討那剛剛之前也有委員提到說這個評鑑的指標可能沒有辦法做出良誘之間的這個範這個這個篩略所以我想我們會針對評鑑的部分
transcript.whisperx[283].start 8807.89
transcript.whisperx[283].end 8828.602
transcript.whisperx[283].text 所以這邊我也跟部長來講一下那針對你看我們剛剛看他從評鑑裡面也沒有你們的契約裡面也沒有所以我希望勞動部跟勞發署一定重視一下針對應該從評鑑還有我們的定期化契約裡面是不是要去做一個適度的修正因為我相信這絕對不是個案
transcript.whisperx[284].start 8830.303
transcript.whisperx[284].end 8857.179
transcript.whisperx[284].text 因為據我們所知發生很多類似的情況所以是不是應該要再加強這些的規範避免類似的狀況再發生是的 謝謝委員好 那請我們部長還有署長再多幫忙好 這已經我相信這絕對不是個案了是好 那再接下來要為我們桃園市針對我們缺工 缺了很多客運司機來請命那
transcript.whisperx[285].start 8861.407
transcript.whisperx[285].end 8883.749
transcript.whisperx[285].text 針對我們客運業開放橋外生留台擔任駕駛這一部分其實不是桃園市缺工缺駕駛據我們了解全台的公共客運缺司機已經成為事實那尤其桃園市本期的選區其實都是屬於比較偏鄉那後來
transcript.whisperx[286].start 8886.82
transcript.whisperx[286].end 8902.909
transcript.whisperx[286].text 他們為了要增加客運的班次才發現不是不增加有經費 有車子 可是沒有司機那很多偏鄉都仰賴這個公車公共客運所以這個沒有司機已經造成很大的困擾
transcript.whisperx[287].start 8903.729
transcript.whisperx[287].end 8921.547
transcript.whisperx[287].text 那後來我們也了解其實勞動部本來在今年初有公告要開放橋外生留台從事客運駕駛工作可是後來臨時又在五月喊卡好像是擔心橋外生的語言能力是否足以擔任客運駕駛
transcript.whisperx[288].start 8922.788
transcript.whisperx[288].end 8939.564
transcript.whisperx[288].text 那這邊我也跟部長來說明一下據我跟桃園市政府溝通了解過桃園市政府說其實針對這一部分他已經全套的培訓方案都已經出來了那針對小客車駕駛的駕照他持有要兩年
transcript.whisperx[289].start 8940.205
transcript.whisperx[289].end 8959.294
transcript.whisperx[289].text 然後這橋外生畢業前要取得華語文能力檢定基礎級資格的大士橋生然後經過客運業者面試之後隨即可以參加授訓及就業培訓的計畫而且馬上給他薪水高達五萬元所以
transcript.whisperx[290].start 8960.074
transcript.whisperx[290].end 8976.716
transcript.whisperx[290].text 基本上這部分他們報名上已經確實有這些人也不會說有外界擔心橋外生語言能力不足而衍生執行服務的風險那針對我們桃園市交通局他說目前
transcript.whisperx[291].start 8978.151
transcript.whisperx[291].end 9006.086
transcript.whisperx[291].text 他開放僑生已經預先報名就等中央頒布修正法案他就可以縮短人力補充的時程待法令頒布之後就能馬上加入授訓的行列那所以針對這部分勞動部是不是可以研議針對若干的縣市先開放試行舉辦也就是我們試點的概念是不是這部分部長可以幫忙解決
transcript.whisperx[292].start 9007.106
transcript.whisperx[292].end 9034.369
transcript.whisperx[292].text 缺司机的问题因为这些相关的这个业务那开放与否其实是会需要目的事业主管机关来向劳动部申请那因为刚刚委员在讲到很多部分因为大家之所以讨论到他的原能力有个部分就是要去处理大家会很在意这个交通安全上面的问题或运输安全上的问题所以之前我们也跟交通部这边去讨论也就是说意思是说
transcript.whisperx[293].start 9036.15
transcript.whisperx[293].end 9055.396
transcript.whisperx[293].text 如果今天就像剛剛有這樣子需求的業者他可以跟交通部這邊來提出那跟交通部一起來討論那到底用什麼方式那可以來確認他的在交通安全上面的語言的能力或者相關風險上面的管理風險上面的避免的這個狀況那
transcript.whisperx[294].start 9057.837
transcript.whisperx[294].end 9079.64
transcript.whisperx[294].text 再來向勞動部這邊來提出申請所以我剛有跟部長這邊說明因為你們那時候喊咖的原因就是說擔心橋外生的語言能力是否足以擔任客運的駕駛跟委員說明當初是因為確實外界有這樣的聲音那這個聲音主要是因為是不是大家會說這個語言方面的能力或者是
transcript.whisperx[295].start 9080.481
transcript.whisperx[295].end 9105.939
transcript.whisperx[295].text 可能它相關因為確實運輸業尤其是司機它其實涉及到是運輸跟交通安全上面的問題它甚至會比小客車它的在開大的遊覽車它的挑戰也再高一點所以怎麼樣去確認在交通安全上面的風險那這個部分會需要可能相關有需求的業者跟交通部這邊來討論因為
transcript.whisperx[296].start 9107.26
transcript.whisperx[296].end 9122.661
transcript.whisperx[296].text 勞動部這邊不太有辦法能夠去主管交通安全要怎麼把關的部分所以這部分基本上剛剛也跟部長報告其實相關的疑慮他們已經有提出解決的方案對 但是我說這部分可能要跟目的世界主管機關再去討論
transcript.whisperx[297].start 9123.362
transcript.whisperx[297].end 9149.89
transcript.whisperx[297].text 交通部勞動部然後假設今天桃園市政府說其實他已經預先報名人已經準備好他配套也做好可是因為他可能要跟目的還是要去跟目的事業主管機關去做這部分的提出所以演繹好到時候再由目的事業主管機關來向勞動部來提出申請好那如果有機會的話就我們就用4點4半的方式來做不像我們還是因為涉及到安全的問題大家都會比較謹慎所以這還是要請交通部也要幫忙
transcript.whisperx[298].start 9150.811
transcript.whisperx[298].end 9166.669
transcript.whisperx[298].text 對 因為交安的部分真的這不是勞工部可以很專業能夠好 那時間問題那我再簡單快速問一下因為我們目前也是缺工的問題啦針對救福法規規定藍領外勞三年工作許可
transcript.whisperx[299].start 9167.17
transcript.whisperx[299].end 9191.69
transcript.whisperx[299].text 其實這從民國86年修正到現在已經大概有30年我們現在接到很多工商團體倡議是不是這三年續聘的機制目前很難符合產業缺工的問題是不是可以把這個三年的時間延長延長到四年那也可以減少雇主到期續聘的行政成本
transcript.whisperx[300].start 9192.27
transcript.whisperx[300].end 9218.948
transcript.whisperx[300].text 也可以適度調整延長工作許可的時間對於移工、故工我們覺得都是有利的那這部分是不是有機會來調整來延長跟文說明的確在這個許可期間的延限部分坦白說不同的出發點就有不同的看法可能從工商界來說比較希望拉長可是從勞工團體的角度移工團體的角度希望縮短
transcript.whisperx[301].start 9220.117
transcript.whisperx[301].end 9235.68
transcript.whisperx[301].text 可是現在很確實 其實你看我們去工廠工商團體很多真的很確實都是缺工非常嚴重對 所以我表達的意思是說確實這邊各種不同的出發點利害相關方會有不同的看法
transcript.whisperx[302].start 9236.894
transcript.whisperx[302].end 9261.845
transcript.whisperx[302].text 所以這個企業界希望拉長但是老公主管團體希望縮短對 那你去評估一下因為我們看一下109年監察院的調查報告其實超過三年以上停留台灣的移工其實已經超過58%而且這是五年前的數據而且我們再看超過六年以上的移工其實也將近四分之一所以其實這個
transcript.whisperx[303].start 9263.466
transcript.whisperx[303].end 9287.6
transcript.whisperx[303].text 移工的需求真的已經是長期的趨勢那我們這30年前修正的我是建議我們來研議看是不是有機會能夠延長解決目前工商團體這很嚴重缺工的問題這真的因為這個議題比方說也會有一些國際上面的組織其實他們反而是希望我們要縮短
transcript.whisperx[304].start 9288.953
transcript.whisperx[304].end 9311.379
transcript.whisperx[304].text 好 那部長我這邊提出來也是幫我們工商團體來提出所以我是說這個事情的確大家會有看法上面方向上不一樣的狀況因為現在缺工真的很嚴重希望這個部長來研議一下缺工的問題是不是可以朝著這方面來比較需要綜合的思考啦但是的確不同的角色不同利害相關方的期待是不同的
transcript.whisperx[305].start 9312.839
transcript.whisperx[305].end 9327.229
transcript.whisperx[305].text 我們請勞動部針對這部分來幫我們衡量評估一下看有沒有機會從這部分來加強改善好 謝謝接下來請黃國昌委員謝謝主席 有請勞動部部長
transcript.whisperx[306].start 9343.348
transcript.whisperx[306].end 9368.57
transcript.whisperx[306].text 黃委員長部長好為了要照顧很多三明治的家庭特別是像我這樣子的年紀在社會上面非常多我們的舊職的中年人為了讓他們比較好的能夠照顧長者我們在上次修舊輔法的時候針對80歲以上免罷生量表這個是在2024年
transcript.whisperx[307].start 9370.812
transcript.whisperx[307].end 9389.714
transcript.whisperx[307].text 總統大選的時候不管是侯友宜市長還是柯文哲主席都提出來的政見對我們而言在選舉的時候提的政見就是要兌現所以我們在2024年年底的時候我們就推動修了就業服務法八十歲以上免八是量表
transcript.whisperx[308].start 9390.802
transcript.whisperx[308].end 9418.468
transcript.whisperx[308].text 那個時候 今年7月25號在大罷免投票前一天你在你的臉書上面延遲的批判了本院所通過的三度通過的救福法勞動部發聲明說深感遺憾重症家庭照顧權益會受到犧牲說會產生十數萬的缺口現在新法上路到現在產生的缺口有多少
transcript.whisperx[309].start 9420.723
transcript.whisperx[309].end 9433.639
transcript.whisperx[309].text 就目前這個部分目前產生的缺口有多少因為修新法而會增加的這個聘僱的量大概是一萬好那產生的缺口有多少
transcript.whisperx[310].start 9435.18
transcript.whisperx[310].end 9461.831
transcript.whisperx[310].text 目前其實當然會有幾個方面就是第一個當然會增加的量第二件事情是確實現在在這個很多重症家庭的看護他們重症家庭來跟我們反映現在看護所以你認為說器重則輕的現象有發生我們也做出因應沒有 器重則輕的現象是不是有發生我們要盡量的讓它不要發生我們也做出了配套是 那所以有發生嗎在我們做出配套以後希望能夠盡量減緩
transcript.whisperx[311].start 9464.124
transcript.whisperx[311].end 9486.529
transcript.whisperx[311].text 我前兩天看到媒體做了非常深入的報導這個報導是我很佩服的報導一個代子願意花這麼長的時間深入針對公共政策 修法以及現在的家庭面對的事情進行深度的報導這在台灣目前的媒體圈非常罕見我高度肯定
transcript.whisperx[312].start 9487.609
transcript.whisperx[312].end 9515.995
transcript.whisperx[312].text 我看了這個報道了以後他上面說了到目前為止有多8000名的長者提出申請遠遠低於預期也沒有看見看護移工器重就輕的現象來東部原本的推估有10萬人可能會聘請會造成現在的看護移工出現缺額的問題等等按照這個媒體他所做的調查報導完全沒有發生
transcript.whisperx[313].start 9517.215
transcript.whisperx[313].end 9530.841
transcript.whisperx[313].text 針對這件事情 部長你會不會覺得當初勞動部有勞動部的政策立場 我同意但是你當初在罷罷免以前的臉書發文的時候是怎麼在抹黑在野黨立委的
transcript.whisperx[314].start 9532.182
transcript.whisperx[314].end 9559.01
transcript.whisperx[314].text 跟委員說明第一件你要撤回你的估計嗎還是你認為你的估計是正確的跟委員說明我分幾個層次講第一件事情是我們確實為了舊法46法的修法以後我們其實是做了六個方案的配套措施就是希望要建立減少期中責欠所以我們當然是希望期中責欠的狀況是能夠減少的這也是為什麼我們要花這麼多心力來設計配套方案的原因
transcript.whisperx[315].start 9560.194
transcript.whisperx[315].end 9577.204
transcript.whisperx[315].text 所以在新法之下藉由配套方案的設計器重責輕不會發生嘛對不對我們認為我們希望它能夠降低對嘛這個就是我講的重點啦可是委員我要說勞動部有勞動部的立場你在大罷免的前夕發文抹黑在野黨的立委危言聳聽
transcript.whisperx[316].start 9578.843
transcript.whisperx[316].end 9606.832
transcript.whisperx[316].text 最後媒體調查出來的結果就不是這個樣子啊但是如果你仔細看我其實當時的發文我是針對一件事情沒有關係啦你的發文社會大眾都可以去看我今天只要求我今天只要求一件事我今天只要求一件事我今天只要求一件事針對舊福法新法上路以後到目前你們採行的配套
transcript.whisperx[317].start 9608.066
transcript.whisperx[317].end 9634.504
transcript.whisperx[317].text 你們所看到的衝擊提一份報告給本委員會可以嗎這沒有問題好 需要多久應該一個禮拜可以吧一個月一個月 好 給你一個月下一個問題2023年民進黨因為連續多起性騷案件被吃案當年引發軒然大波促成性平三法的修法那次的修法新增了
transcript.whisperx[318].start 9635.625
transcript.whisperx[318].end 9659.218
transcript.whisperx[318].text 對最高負責人或僱用人為職場性騷擾行為必須要加以處罰我相信2023年走過那段時間大家都很心痛國會也動起來了修法現在我們所看到的個案是有一家公司老婆掛董事長老公掛董事結果老公去性騷擾5名
transcript.whisperx[319].start 9661.109
transcript.whisperx[319].end 9679.675
transcript.whisperx[319].text 外籍的作業員遭到新北市勞工局裁罰裁罰10萬元 老實講我覺得是太輕了啦但當初法律也只有定1萬到100萬他可能看公司的size但我老實說只裁罰10萬元是太輕了但我現在非常驚訝的是什麼
transcript.whisperx[320].start 9680.675
transcript.whisperx[320].end 9693.104
transcript.whisperx[320].text 我們當初國會修了法要杜絕這樣的行為新北市勞工局也罰了只罰了10萬塊罰了10萬塊以後人家溯源到勞動部被撤銷這怎麼回事
transcript.whisperx[321].start 9694.363
transcript.whisperx[321].end 9708.868
transcript.whisperx[321].text 好 跟委員說明其實因為這個案子其實我們內部也做很多的研議所以我們是希望接下來我們其實也做了一些法規上面的修訂也請專家學者來討論我們現在分兩個部分第一個 針對現行法的規定不好意思 請你針對問題回答我問題還沒有問完是 第一個
transcript.whisperx[322].start 9713.05
transcript.whisperx[322].end 9738.173
transcript.whisperx[322].text 你說你進行研議嘛研議是空的嘛所以我要問具體的嘛第一個 依照現行法的規定依照現行法的規定勞動部現在的這個訴願決定你們覺得是正確還是不正確的依照現行法的規定是正確還不正確的所以你們認為依照現行法的規定把原處分撤銷是正確的
transcript.whisperx[323].start 9739.48
transcript.whisperx[323].end 9762.621
transcript.whisperx[323].text 好 那現在問題來了所以是當初立法出了問題是不是因為你現在 如果按照你說的依照現行法的規定新北市勞工局裁罰10萬塊那個性騷擾外籍勞工的那一個董事也就是董事長的勞工去性騷擾外籍的作業員10萬塊
transcript.whisperx[324].start 9764.503
transcript.whisperx[324].end 9784.962
transcript.whisperx[324].text 新北市勞工局所做的那個處分是違法的而勞動部把那個處分給撤銷掉依照現行法的規定你剛剛說你們覺得是正確的那我現在問題來了環節出在哪裡環節出在上一屆國會修這個性平三法的時候沒有修好嗎
transcript.whisperx[325].start 9786.135
transcript.whisperx[325].end 9786.655
transcript.whisperx[325].text 這個我知道了
transcript.whisperx[326].start 9806.084
transcript.whisperx[326].end 9835.673
transcript.whisperx[326].text 我沒有要你解釋你現行法怎麼解釋的所以下一個是所以我的問題來了嘛依照現行法的規定如果勞動部撤銷原處分是正確的那是不是現行法也就是上一屆國會修這個法的時候出了問題是嗎我跟委員報告上次修的時候有一個與其職務相當之人所以現在勞動部我們的單位是在與其職務相當之人要納入實際負責所以要再推動修法嗎是的
transcript.whisperx[327].start 9836.033
transcript.whisperx[327].end 9855.624
transcript.whisperx[327].text 那上次那個與其職務相當之仁是在立法過程當中被刪除嗎沒有刪除啊就保留這樣子的文字啊所以我們現在那我就聽不懂啦如果要保留這樣子的文字的話那你又說現在勞動部的撤銷處分是正確的我就聽不懂啦
transcript.whisperx[328].start 9856.896
transcript.whisperx[328].end 9886.216
transcript.whisperx[328].text 跟委員補充報告因為現行的規定裡面對於實際負責人沒有說的很清楚所以我們的溯源會溯源委員在做個案的時候會依照現在我們還沒有很明確的說實際負責人要納入母法上面的最高負責人先停一下 實際負責人沒有納入母法裡面的負責人這件事情問題出在法規的層次還是出在行政命令的層次
transcript.whisperx[329].start 9887.557
transcript.whisperx[329].end 9908.136
transcript.whisperx[329].text 我們現在法制作業上面認為在細則或者是解釋令上面是可以處理的對啊 這個就是我的問題啦我現在分兩個區塊如果是立法不當 那立法者負責嘛按照責任政治的ABC啊立法不當 立法者負責嘛
transcript.whisperx[330].start 9909.161
transcript.whisperx[330].end 9921.615
transcript.whisperx[330].text 那如果是立了法以後下面的行政不管是授權的命令職權的命令解釋的函式是行政機關要負責嗎剛剛你們說那是因為現行的規定規範的不明確我為什麼問的問題要問這麼具體
transcript.whisperx[331].start 9928.042
transcript.whisperx[331].end 9955.929
transcript.whisperx[331].text 這樣我們才可以在責任政治下面去追究權責嘛現行的規定規範的不清楚那剛剛按照黃琦雅司長的回覆也就是在行政命令或是相關規則的解釋上面規範的不清楚 對嗎是嗎所以跟委員說明這是我剛才說我們其實已經在啟動要來修訂相關細則把責任負責人納入在相關的作業今天如果出現了
transcript.whisperx[332].start 9957.596
transcript.whisperx[332].end 9983.232
transcript.whisperx[332].text 這個公司的董事實際上面在指揮在控制這些外籍勞工的人發生性騷擾的行為竟然沒有辦法裁罰而他所出現的原因是勞動部當初就對於法律所授權要定義那個負責任的範圍定義不明讓他逃掉了該被處罰這件事情誰要負責
transcript.whisperx[333].start 9984.173
transcript.whisperx[333].end 9998.589
transcript.whisperx[333].text 所以這是為什麼我們現在想要修訂的原因啊對嘛 我還是回到洪部長的邏輯嘛在民主政治的ABC下面國會立錯了法造成了負面效應選民要究責國會嘛
transcript.whisperx[334].start 10000.495
transcript.whisperx[334].end 10023.781
transcript.whisperx[334].text 行政機關該做的解釋沒有好好做解釋產生了漏洞讓該處罰的人沒有受處罰按照民主政治責任政治的ABC則要負責所以這是為什麼我說行政部門有必要有責任來面對現在的這個細則的狀況應該予以修訂對只要修訂就好了嘛也沒有人需要負責啊所以我一開始就講這個啊對啊我的邏輯還是一樣啊
transcript.whisperx[335].start 10027.813
transcript.whisperx[335].end 10046.005
transcript.whisperx[335].text 只要修訂就好啦反正勞動部也沒有人要負責嘛我有說錯嗎我們當然要把該修訂的符合法規上面的應該把它修訂清楚我覺得這事情這是我們這幾個月都在進行的工作OK 好好 謝謝接下來請王振旭委員來做詢問
transcript.whisperx[336].start 10060.889
transcript.whisperx[336].end 10087.179
transcript.whisperx[336].text 謝謝主席有請洪部長部長好今天是勞動部的業務報告看到您準備這麼完整的相關的業務報告包括早上的口頭報告真的非常謝謝回想在113年11月25日您匆匆忙忙的上陣
transcript.whisperx[337].start 10088.9
transcript.whisperx[337].end 10113.172
transcript.whisperx[337].text 那個時候在很短的時間裡面被賦予這個重責大任當然壓力很大大家其實也都有一些安心不過將近一年來看你很匆匆容容游刃有餘的來應對相關的議題真的非常佩服那也很感謝在這段時間包括部長還有所有同仁針對相關的勞動議題做非常深入的研究那也
transcript.whisperx[338].start 10114.693
transcript.whisperx[338].end 10131.441
transcript.whisperx[338].text 體勞動朋友解決很多問題當然還是有很多問題必須要大家共同來努力包括今天的主題之一就是引進這個跨國的勞動力如何能夠有更多更完整的這個政策配套這個就是今天希望跟部長一起來討論的地方
transcript.whisperx[339].start 10133.536
transcript.whisperx[339].end 10157.626
transcript.whisperx[339].text 那完善這個移工的政策配套我相信大家從您的口頭報告裡面也知道行政院在10月30號有公告相關跨國勞動力的精進方案這裡面有四大方案其實主要還是聚焦在三個部分一個就是製造業的部分如果能夠幫這個本國的勞工加薪的情形下呢是可以
transcript.whisperx[340].start 10158.426
transcript.whisperx[340].end 10184.508
transcript.whisperx[340].text 來增加這個移工的名額那第二個主要方案就是希望能夠放寬外國技術人力流用的上限包括如果說這些技術人才在台灣已經過一段時間的話可以能夠把它全數的轉任到技術人力來不過也希望整體的總員工的百分比不要超過50%那第三個部分就是有關於旅宿業跟這個商港碼頭業
transcript.whisperx[341].start 10186.309
transcript.whisperx[341].end 10205.215
transcript.whisperx[341].text 希望能夠引進相關的外國技術人才能夠讓整個工作在運作可以持續的來精進當然這個百分比也不要超過10%這個是已經公告的那也持續在執行了一個相關的政策方案
transcript.whisperx[342].start 10205.875
transcript.whisperx[342].end 10233.767
transcript.whisperx[342].text 另外賴總統其實也希望能夠持續推動12歲以下一個孩子的家庭能夠可以申請到外籍的幫傭來協助整個家庭的照顧如果是雙薪家庭的話就沒有後顧之憂當然這個部分行政院還在持續的研議當中希望年底之前能夠有相關的政策跟配套可以讓國人進一步的了解
transcript.whisperx[343].start 10234.207
transcript.whisperx[343].end 10256.842
transcript.whisperx[343].text 那這部分可不可以先請部長稍微說明一下有關的進度跟一般的狀況其實針對外籍幫中的政策那包括是不是要調整現有開放的幅度那這部分的政策我們目前在依照行政院的指示在幾個原則下面那這還在做相關的評估
transcript.whisperx[344].start 10257.782
transcript.whisperx[344].end 10279.003
transcript.whisperx[344].text 是的確因為我們知道同樣是12歲以下如果是一般的兒童正常的成長的壓力跟如果照顧是一個罕病的兒童可能帶來的壓力其實是不太一樣所以這部分可能在研議的過程裡面需要有更多的討論那也希望這個配套可以讓它更完整
transcript.whisperx[345].start 10279.463
transcript.whisperx[345].end 10294.243
transcript.whisperx[345].text 未來在做這些政策改善的同時讓社會在有這個好的政策的執行之下有更好的一些服務的讓民眾更好的感受
transcript.whisperx[346].start 10295.685
transcript.whisperx[346].end 10319.606
transcript.whisperx[346].text 再過來其實我們是要看一連串的數據這個是我們目前針對移工看來的一些影響我們從民國100年到113年引進移工的在台人數從42萬增加到82萬增加了將近一倍4年的移工隨著移工的人數增加以後
transcript.whisperx[347].start 10320.347
transcript.whisperx[347].end 10335.323
transcript.whisperx[347].text 也從3萬3增加到9萬 這個增加了兩倍多就是從3萬變成到9萬所以這個失聯移工的比例從7.9%增加到11%增加到將近3.多個Percent
transcript.whisperx[348].start 10338.306
transcript.whisperx[348].end 10359.614
transcript.whisperx[348].text 那受雇的人數如果相較於這個外勞跟本勞的這個比例的話也從5.1%增加到8.7%那這些人數的成長其實是都非常的可觀那如果我們現在的這個移工政策持續這樣執行的話我們也可以理解未來引進移工人數會持續的增加
transcript.whisperx[349].start 10360.635
transcript.whisperx[349].end 10377.854
transcript.whisperx[349].text 持续增加的同时如果依照这个比例的成长我们的失联移工人数也相对会持续的增加那这个相关的这些失联的移工不管他是在医疗的部分或者是社会安全的影响
transcript.whisperx[350].start 10378.935
transcript.whisperx[350].end 10407.16
transcript.whisperx[350].text 所帶來衝擊應該也會逐漸的讓我們的民眾會替社會擔心這個是我們所看到的這個相關的問題所以如果能夠有相關的這個政策配套這是要麻煩部長這邊要多費心的部分那因為再過來民團會擔心就是說在引進這個跨國勞動力的同時有三個部分必須要持續的來加強注意
transcript.whisperx[351].start 10407.66
transcript.whisperx[351].end 10431.11
transcript.whisperx[351].text 第一個就是那到底在持續的擴張這個移工人數的時候到底有沒有一個整體的規劃甚至有沒有可能會定一個總額我們也了解它常常這個總額的數字大家會有相關的一些討論比如說我們在第5有關於這個就業福華第52條裡面就要求
transcript.whisperx[352].start 10432.33
transcript.whisperx[352].end 10452.843
transcript.whisperx[352].text 引進的這個總人數呢必須要設定一個警戒的指標才能夠讓民眾可以安心來了解那這個部分需要有中央主管機關來邀請勞工 僱主還有學者代表來協商這是有關於這個整體規劃跟人數總額的部分
transcript.whisperx[353].start 10453.325
transcript.whisperx[353].end 10478.168
transcript.whisperx[353].text 那第二個其實民團也會很擔心目前台中的巨大工業公司被美國政府因為有可能會強迫勞動的風險之下來發布了這個戰扣令那這個對台灣的形象其實是影響蠻大的這個部分如果我們除去引進勞工的過程裡面有需要更注意的部分
transcript.whisperx[354].start 10479.049
transcript.whisperx[354].end 10503.531
transcript.whisperx[354].text 第三個地方就是如何避免造成本國勞工的低薪因為之前我們引進勞工是原則上是補充性的原則而不是替代性原則萬一我們引進來有更多的替代性的話會不會造成本地勞工低薪的狀況無法改善這三部分不知道目前部長有哪一些可以提供給大家參考的好
transcript.whisperx[355].start 10504.131
transcript.whisperx[355].end 10528.211
transcript.whisperx[355].text 跟王委員說明因為王委員還有很多勞工團體很關注這部分針對這個我們在警戒指標部分其實在我們今年11月7號的時候這個政策小組討論裡面其實有檢視了我們在113年的這個警戒指標跟112年的數據那這一次我們其實看到在19項這個產業跟社福是有這樣的指標裡面其實16項是有正向的
transcript.whisperx[356].start 10530.373
transcript.whisperx[356].end 10552.934
transcript.whisperx[356].text 三項是持平的狀況所以針對這個警戒指標的部分我們其實還是很密切的在關注這些事情來作為我們在政策判斷上面的依據這是第一點那第二點其實這一次我們的確也考慮了現在大家都越來越關注的強迫勞動的這個議題所以剛剛其實王阿元講一個在一開始都講一個說我們目前聚焦在前三項方案其實不是
transcript.whisperx[357].start 10553.755
transcript.whisperx[357].end 10578.469
transcript.whisperx[357].text 我們是四項方案都聚焦而且最後一項方案也就是提高政府的角色跟功能其實做起來的挑戰不比前三項來的低而且會花的心力可能是更大的那我們也是藉由提高政府的角色跟功能的這樣子的能量希望能夠盡量來比方說來提高職聘的量能也就是可以來因應現在強迫勞動
transcript.whisperx[358].start 10580.97
transcript.whisperx[358].end 10601.442
transcript.whisperx[358].text 這個勞動人權風險的這個狀況其實這也是我們在為什麼這麼強調那個方案一個很重要的原因在這個地方他其實也是應對強迫勞動很重要的一個具體的做法這樣子那第三點是針對如何不要避免本國勞動基金我們正是因為不希望造成本國勞動基金所以我們在這次的方案設計裡面有幾個
transcript.whisperx[359].start 10603.683
transcript.whisperx[359].end 10631.799
transcript.whisperx[359].text 重點第一個是我們希望這個名額的增加都可以要以本國勞工加薪的前提本國勞工要加薪作為前提這是第一點第二點其實我們在這次的方案裡面也非常著重是在外國技術人力上面外國技術人力跟藍領移工不同的地方是外國技術人力是需要設置薪資的門檻的也包括需要設置這個包括可能技能或語言的要求的
transcript.whisperx[360].start 10632.299
transcript.whisperx[360].end 10652.179
transcript.whisperx[360].text 那透過外國技術人力他設置薪資門檻跟語言要求這幾件事情就是希望盡量來減少對於本國勞工的權益包括尤其是造成更不希望造成低薪的這個狀況來發生所以這幾個點也是在我們這次方案設計裡面非常非常關注的點所以我們才做這樣子方案的規劃
transcript.whisperx[361].start 10653.3
transcript.whisperx[361].end 10677.128
transcript.whisperx[361].text 是好謝謝部長這麼完整的說話一方面可以讓國家更進步的同時也讓我們的勞工朋友知道政府努力的方向所以針對今天這樣的主題有相關的這個配套包括失聯的移工的這些醫療代帳的部分要怎麼做進一步的處理這部分也要麻煩部長
transcript.whisperx[362].start 10680.029
transcript.whisperx[362].end 10706.276
transcript.whisperx[362].text 這邊跟衛福部持續的來關照第二個部分就是如何避免高齡跟幼童照顧上發生器重則輕的困擾這部分也是一個希望部長來關照的重點那另外就是是否會跟促進中高齡跟女性就業政策造成一些衝突這個其實我們也知道目前我們努力的方向如果有衝突的話那有什麼好的配套
transcript.whisperx[363].start 10706.936
transcript.whisperx[363].end 10727.69
transcript.whisperx[363].text 最後一項就是能不能考慮相關政策在調整的時候這些就業安定費是不是也能夠透過不同的需求之下做適當的調配這個部分可不可以兩個月如果有相關的這些書面報告的話可以讓委員會還有辦公室來做參考
transcript.whisperx[364].start 10728.01
transcript.whisperx[364].end 10745.808
transcript.whisperx[364].text 可以確實汪元說的其實移工的政策環環相扣介紹的層面其實很多然後都必須綜合性的考慮所以這些點我們其實我想我們都會納入再更深入的考量那我們會來我們一份報告讓汪元這邊來參考
transcript.whisperx[365].start 10747.409
transcript.whisperx[365].end 10773.022
transcript.whisperx[365].text 好那最後再利用一點點的時間跟部長來討論一下有關受庇護人的保障措施其實部長在擔任委員的時候也非常關心這個議題目前還是有數十位的這些因為法規的限制依法申請拘留而預期兩年沒有做完做好決定這個難民相關的權益是希望能夠透過我們勞動部這邊有一個適當的含釋讓這些
transcript.whisperx[366].start 10776.064
transcript.whisperx[366].end 10801.204
transcript.whisperx[366].text 因為他們本國出現了哪些情形之下讓他們不得已到台灣來他如果不是符合我們常規的這個移工的勞動情形之下所受到的處分當初去年上一期在這個屆期審查移民法的時候也就立法院就邀請有請那個移民署來彙整各個
transcript.whisperx[367].start 10802.365
transcript.whisperx[367].end 10814.724
transcript.whisperx[367].text 相關的意見來免於處罰的附帶決議那這部分的話也希望能夠透過勞動部有更完整的含釋來把這個事情做好那不知道這部分可不可以請部長這邊也能夠說明
transcript.whisperx[368].start 10816.601
transcript.whisperx[368].end 10844.099
transcript.whisperx[368].text 好其實這個關於外國人進來然後這個臨時外僑登記證的狀況尤其他可能是有一些可能會需要庇護的原因臨時外僑登記證是我從當立委的時候就非常關注的議題那但是的確因為他的這個組的機關其實會是在內政部那但是勞動部我們在做處分的時候我們不一定都能夠知道這個工作的人那他目前有沒有具備臨時外僑登記證上面的在這上面的名單
transcript.whisperx[369].start 10844.939
transcript.whisperx[369].end 10861.53
transcript.whisperx[369].text 所以如果今天在內政部這邊能夠提給我們相對應的這個名單上面的對象的話我們其實就可以依照內政部給我們的名單來去做相對應處分上面的調整或者是去做特別的看待
transcript.whisperx[370].start 10862.751
transcript.whisperx[370].end 10888.197
transcript.whisperx[370].text 那如果需要含釋的話就麻煩勞動部這邊也把這個需求能夠具體來完成包括這個違反服務法第43條裡面是不是有違反行政法法第43條的適用性還有是否能夠會避免抵觸兩公約這個需求我想我們都不希望去抵觸兩公約因為這當初在做這個當時在移民法修法的時候跟相關的配套裡面就是大家就非常看重這件事情尤其很多人權團體都很關注
transcript.whisperx[371].start 10888.837
transcript.whisperx[371].end 10917.478
transcript.whisperx[371].text 所以我想我們會來跟內政部這邊來聯絡他們一下如果他們有把這相關的名單就趕快提供給我們那我們依照這個名單來做處分上面的依據好 謝謝部長 謝謝主席好 謝謝蘇昭偉請你稍坐好不好現在這個時間是臨時提案的處理因為那個提案委員到了不然提案委員如果要讓你先講我沒有意見
transcript.whisperx[372].start 10919.431
transcript.whisperx[372].end 10926.165
transcript.whisperx[372].text 你要聯想起義嘛好不好好現在處理臨時提案既有一案請宣讀
transcript.whisperx[373].start 10927.527
transcript.whisperx[373].end 10952.225
transcript.whisperx[373].text 為保障勞工在AI浪潮下知工作權益與人性尊嚴並協助其順利轉型原要求勞動部應緊速研擬並公布企業使用人工智慧AI指導原則除應處理就業歧視職場監控與隱私權保護等基本議題外更應納入勞工的轉型教育權其次應保障勞工的程序參與權
transcript.whisperx[374].start 10953.746
transcript.whisperx[374].end 10977.024
transcript.whisperx[374].text 最重要者因維護勞動者的人性尊嚴在指引中揭示非由AI主導人之基本原則並針對AI與職場的監視追蹤等議題建立制度性規範提案人委員陳金輝 廖偉祥 邱振軍宣讀完畢好 請問本案行政當中有意見有 請說明
transcript.whisperx[375].start 11007.325
transcript.whisperx[375].end 11030.823
transcript.whisperx[375].text 報告委員因為這一個部分是對於企業使用AI的一個指導原則也就是我們希望引導企業去處理一些關於AI的事情那在文字建議上面因為有提到這個納入勞工的轉型教育權這個對企業相對的負擔是比較大的那所以我們這一個部分是建議是不是能夠做文字的刪除那以及
transcript.whisperx[376].start 11031.323
transcript.whisperx[376].end 11054.803
transcript.whisperx[376].text 可以去請他去做這個在職勞工提供這個AI的這些認知的部分在教育的部分就會建議刪除以及企業他應該也要做的是一個建立預防工作被取代的一個支持系統在轉職的部分應該是由我們政府單位來協助失業勞工所以我們的文字修正會是建議
transcript.whisperx[377].start 11055.924
transcript.whisperx[377].end 11072.832
transcript.whisperx[377].text 刪除這個納入勞工的轉型教育權以及刪除集師業以及刪除這個資在教育那轉職的 以及這個轉職的文字也刪除那我們
transcript.whisperx[378].start 11074.978
transcript.whisperx[378].end 11100.697
transcript.whisperx[378].text 你要不要 你對第幾段修什麼認識不會 我有聽懂你聽懂 好我來說明第一個我先跟大家講一下我們針對AI的自己而指引目前的進行的階段因為AI發展的速度很快所以近期所以我們其實目前也跟數位部我們跟數位部成立了一個聯合的協作的工作小組那就是希望能夠在透過
transcript.whisperx[379].start 11101.809
transcript.whisperx[379].end 11126.338
transcript.whisperx[379].text 我们比较了解劳动法规上面的需求包括就业歧视等等规定可是我们也需要在一些技术上面得到更多的资源或者投技术的观点来检视所以我们也跟数位部现在成立了一个协作的小组就是希望来去处理像这几个指引后续怎么让他可以真的在技术的使用端里面能够跟接地气的部分我们现在进入这个阶段
transcript.whisperx[380].start 11126.978
transcript.whisperx[380].end 11148.794
transcript.whisperx[380].text 那我们刚才同仁表达的事情是说因为这一份的这个指导原则或指引他其实是让企业在使用的所以我们可能就是说包括像转型的教育权我认为这可能是政府跟企业一起来做了然后也包括是建立预防工作被取代的这也是希望是政府跟企业一起来合作的部分可能
transcript.whisperx[381].start 11149.634
transcript.whisperx[381].end 11171.113
transcript.whisperx[381].text 怎麼樣子在我們在描述上面不會讓企業覺得好像這件事純然好像政府都把東西全部都丟給企業意思是這樣子啦對理解謝謝同意同意好對因為這個希望勞動部可以趕快有效率的產出這個才是我們希望的謝謝好謝謝提案委員接受這樣的一個建議修正那請再宣讀
transcript.whisperx[382].start 11174.936
transcript.whisperx[382].end 11188.259
transcript.whisperx[382].text 我們現在擬定一下具體文字好不好對不用就三條就好了對好你剛不是說你聽懂有聽懂好先讀先讀第三段
transcript.whisperx[383].start 11203.137
transcript.whisperx[383].end 11231.021
transcript.whisperx[383].text 第三段在第三行後面更因前瞻性抵後面的文字納入勞工的轉型教育權這幾個字刪除然後第五行前面知在教育的文字刪除後面那一句莫具支持系統的前面轉值兩個字刪除
transcript.whisperx[384].start 11233.547
transcript.whisperx[384].end 11253.131
transcript.whisperx[384].text 然後其他就跟原來的一樣還有一個部分是那個第四行有個及失業把失業拿掉在第四行的轉型教育權這幾個字刪除下一句對在職後面那幾個字及失業三個字刪除宣讀完畢好 田委員這樣OK吧
transcript.whisperx[385].start 11258.578
transcript.whisperx[385].end 11269.264
transcript.whisperx[385].text 可以收到 謝謝 同意那我們就修正通過 臨時提案全部處理完畢 接下來請蘇經元蘇昭偉來做選擇謝謝主席我們請部長勞動力發展署黃署長
transcript.whisperx[386].start 11290.603
transcript.whisperx[386].end 11314.603
transcript.whisperx[386].text 所以很好我今天問你三個問題 我簡單啦 我在形容外科 沒辦法 拖不下去啦第一個問題 你今年11月25 中心嘛 對不對你知不知道 你當時中心都不知道有點忘了日期了我都要給你monitor 要一年啊你對你一年來的表現 你自己判幾分
transcript.whisperx[387].start 11319.279
transcript.whisperx[387].end 11338.073
transcript.whisperx[387].text 自己打分數很不會被我覺得不用自己打分數吧我用比較客觀看啦 我覺得你很幼老啦很細膩但是細膩而已啦 私立而已開窗不太夠
transcript.whisperx[388].start 11346.292
transcript.whisperx[388].end 11361.983
transcript.whisperx[388].text 伴隨第二個問題 我要問如果像國昌有說八十歲以上不用用八十兩票這也是柯文哲提出來 也是侯友宜提出來我這裡要跟你說就是侯友宜這個案子是我提的
transcript.whisperx[389].start 11363.621
transcript.whisperx[389].end 11371.111
transcript.whisperx[389].text 所以我把它拿出來 是要做它的競選的政見所以我對這個 我很關心我們要過這個法的時候
transcript.whisperx[390].start 11378.976
transcript.whisperx[390].end 11406.645
transcript.whisperx[390].text 大家都說會加幾萬尤其是我們一些女性的立法委員都一直說會增加十萬 二十萬會增加多少 會排擠但是我看因為像這個外籍看護沒有在縮沒有在縮不然大家都很害怕台灣善者是比較多不對 這點你有同意嗎
transcript.whisperx[391].start 11409.031
transcript.whisperx[391].end 11425.06
transcript.whisperx[391].text 當然政府的政策上面希望盡量的去拉近不同家庭的處境所以你這樣考慮太多結果呢 實施了到現在看起來也沒有像我們想的那麼嚴重我們花了很大的力氣去設計配套
transcript.whisperx[392].start 11427.403
transcript.whisperx[392].end 11438.573
transcript.whisperx[392].text 不可以說大家 像八十幾歲的人身體用日照的條 要請一個人做看護 還要花這麼多錢我感覺那是不可能的事情 賺錢不太好賺 勞工改革賺錢不太好賺所以我早就預測說 不想你想那麼嚴重
transcript.whisperx[393].start 11451.995
transcript.whisperx[393].end 11459.979
transcript.whisperx[393].text 第二就是我比較高興的因為現在24個24萬個外籍看護裡面以前是21萬變22萬變23萬現在這裡面你說發揮去捨棄重的然後他會去要自己照顧比較輕盈的這是我們高興的嘛會排除一些重症的沒有人要照顧結果我看也不是這樣
transcript.whisperx[394].start 11477.679
transcript.whisperx[394].end 11499.975
transcript.whisperx[394].text 我想外籍康復來講 他要捱的可能是待遇啦還有工作的磁場 還有氛圍啦你如果說僱主的人對他比較好 或是說再給他一點養活這樣 他如果是沒有那樣照顧重症的跟照顧輕症的 我看差不多啦照顧重症的反而是壓力變那麼大反正聰明就聰明
transcript.whisperx[395].start 11504.406
transcript.whisperx[395].end 11530.798
transcript.whisperx[395].text 照顧親政的反省還會出問題呢這個這樣的敘述行政部門不能講啊你不能講啊而且我們不能這樣想啊好我們不能這樣想啊就是說重症會沒人顧他會選僱主然後跑掉也沒有像我們想的那麼的嚴重對不對黃署長署長有沒有你看到有這個情形嗎
transcript.whisperx[396].start 11532.27
transcript.whisperx[396].end 11560.793
transcript.whisperx[396].text 就是說大家都跑去照顧年輕的然後就自己選僱主然後跑來跑去那個我來回答第一個是其實我們還是有聽到會有一些重症的家庭跟我們反映其實家裡的看護外籍看護工其實的確在好像有點想要在外面去找工作然後找比較輕的工作這個狀況現象不是沒有有這樣的聲音我們陸續都有聽到
transcript.whisperx[397].start 11562.034
transcript.whisperx[397].end 11584.477
transcript.whisperx[397].text 但第二個事情是的確我們從行政部門角度我們本來就要為比較嚴峻的狀況去做設想我們不能都假設我都不去設想大家又會說很輕忽我們要為比較嚴峻的狀況去做設想並擬定相關的配套所以當初在上路的時候我們也提出六大配套也希望能夠透過配套來減少可能原本大家擔心的衝擊
transcript.whisperx[398].start 11585.738
transcript.whisperx[398].end 11612.467
transcript.whisperx[398].text 這也是我們在設計配套的原因所以你們的設計配套盡了很多力你們有什麼量化的Data讓我們能夠感覺你們有努力或是你們有 我想這種Data吃牌吃牌其實包括我們在這次我們也擴大了直接擴大免評這擴大免評也讓申請的件數從申請的案件數從五成變七成其實現在有高達七成其實都適用多元免評的資格
transcript.whisperx[399].start 11613.587
transcript.whisperx[399].end 11634.532
transcript.whisperx[399].text 所以其實很多的配套 配套的範圍也擴大那這都是我們希望符合大家民眾的需求之下盡量來減少衝擊的做法我倒是覺得啦 很多的北省省我去屏東高秋那一四個這些家屬在懷念的是什麼呢
transcript.whisperx[400].start 11635.919
transcript.whisperx[400].end 11650.804
transcript.whisperx[400].text 他說我這個老人都重症有的重大三病等等我們就已經 經濟面就不是很好聽這個話就好來做康復是無不理想的後來就出事了你又把我收到救援安定會這件事有減免嗎
transcript.whisperx[401].start 11652.458
transcript.whisperx[401].end 11672.869
transcript.whisperx[401].text 是減免還是免除如果它的經濟弱勢比方是相對是經濟上比較弱勢的其實是不用 是免救安費的是免交 還有三千塊對不對兩千是免救安費的免交還是減免它如果是經濟弱勢的話是減免減免 那有的是免費對不過這個要弱勢啦如果我們大家相當的反應是這一點
transcript.whisperx[402].start 11674.85
transcript.whisperx[402].end 11700.99
transcript.whisperx[402].text 所以你就知道你嫁到那裡是對人來說有多重要好啦 這個就衍生第三個問題我們賴總統就是要叫婦女來參與勞動力這也是很好的事情啊讓這些女性投入出場我們現在的勞工是一千兩八萬人嘛 對不對那如果這些女性這裡有的全都特勤館 年齡也好你到處顧小孩 能帶上去外籍幫養
transcript.whisperx[403].start 11703.696
transcript.whisperx[403].end 11720.008
transcript.whisperx[403].text 來出國 現在才兩千五百這要怎麼做呢對我們女性就業的參與率增加社會勞動率也增加 品質也提高我們就從補助 從店裡總統有一個很好的想法你現在還在考慮 你是在考慮什麼
transcript.whisperx[404].start 11723.37
transcript.whisperx[404].end 11739.958
transcript.whisperx[404].text 各位說明這幾個月我想我們都在評估中然後也把各種可能的情境行政院也指示了幾個原則包括必須考慮本國的勞工的狀況也必須去考慮多元家庭的需求也包括一些
transcript.whisperx[405].start 11740.738
transcript.whisperx[405].end 11754.142
transcript.whisperx[405].text 也許在照顧上面或者是在這個工作上面的品質然後最後也包括就是最重要的事情是說這個政策如果要實行的話那是要能夠真的減少這個照顧者的負擔台灣勞工不窮這是會越來越嚴重沒有可能會越來越好
transcript.whisperx[406].start 11760.024
transcript.whisperx[406].end 11772.189
transcript.whisperx[406].text 不管是製造業 不管是營建業 不管是什麼都欠了連在大太魯的大便都扣多了在做所以這個問題是越來越嚴重所以要讓這個婦女再來參與 這是好事不然說什麼五千塊要調去八千塊的 安靜的 安定的署長你是在調什麼意思 你是
transcript.whisperx[407].start 11783.033
transcript.whisperx[407].end 11805.653
transcript.whisperx[407].text 用克魯莎還是根據哪一個條例我跟委員說明一個政策一個政策的推出都會有它可能會有的正面或負面的影響那我們也透過各種政策工具去思考怎麼樣減少可能會負面的影響所以各種政策工具也必須去評估
transcript.whisperx[408].start 11806.414
transcript.whisperx[408].end 11834.283
transcript.whisperx[408].text 所以您是 您就當沒想過要把它動起來不要做 還是因為我看我們現在就是在評估中你這個配套就是要把它動起來啊跟委員說明我們其實現在就是在評估中對這個安定會五千到八千你這個女性出來上班不就要賺五六萬六七萬她到底要不要請因為你請一個外資班
transcript.whisperx[409].start 11836.823
transcript.whisperx[409].end 11858.78
transcript.whisperx[409].text 幫你用的 再加一支救援電話 再八千塊再加一支骨肉骨素 再加下去 再讓他吃 再大 再大要不然四萬塊超過啊確實在這個議題上面各界有不太一樣的看法會有不同的出發點的看法那我們作為一個政策的規劃者跟評估者我們其實需要把各界的各種的看法跟需求都考慮進來
transcript.whisperx[410].start 11860.518
transcript.whisperx[410].end 11880.51
transcript.whisperx[410].text 所以可能會有不同的出發點但是這是從 因為從不同的角度看待的原因你這個喔 你這個人要 要說調到這樣你要穿喔 這些女性要投入職場的差不多都要白領階級以上的啦差不多要一個個都穿六萬以上 八萬以上到我才穿
transcript.whisperx[411].start 11881.451
transcript.whisperx[411].end 11909.57
transcript.whisperx[411].text 你如果說 像藍綠的你說要叫他請 那不可能的事情他請不上去 老是自己顧孩子就好啊所以這個美意就沒了各個因素我們都要綜合考慮啦示範啦 各個因素我們都必須綜合考慮因為 有很的確我們聽到有很需要的聲音但也會有一些比較一直在提醒我們跟擔心的聲音這個正反意見都存在
transcript.whisperx[412].start 11914.585
transcript.whisperx[412].end 11942.581
transcript.whisperx[412].text 好 謝謝 接下來請代會委員委員來做選擇代會委員委員來做選擇謝謝主席 我們有請勞動部部長來 請洪部長還有我們那個責安署署長來 洪署長責安署 勞動部署
transcript.whisperx[413].start 11943.462
transcript.whisperx[413].end 11970.699
transcript.whisperx[413].text 部長 署長 午安我想在這裡先跟你們線上感謝在這一次七月丹納斯颱風重創重創我們整個雲嘉南尤其是台南的這個西北地區那西北它本身就是一個農業區那存在的保留了很多的一個石棉瓦這個石棉瓦其實存在了很多的農舍甚至就是一般的住家
transcript.whisperx[414].start 11971.806
transcript.whisperx[414].end 11993.842
transcript.whisperx[414].text 那其实在那段时间常常就是说在空气里头还飘散的那种纤维的一个粉尘为什么因为大家在拆房子的时候大家是用一个最直接的方式也没有戴口罩也没有戴手套那就是这样子就是把这个那个屋顶上的石棉整个拉下来
transcript.whisperx[415].start 11994.542
transcript.whisperx[415].end 12015.385
transcript.whisperx[415].text 那謝謝你們就是說展署那提出來的這一個災後重建防護指揮所那甚至就是說在我們四個區裡頭做了災後防護的一個服務站那也送出去了一萬多組一萬多組的這個防護包那可是在我們台南
transcript.whisperx[416].start 12016.306
transcript.whisperx[416].end 12036.965
transcript.whisperx[416].text 還有大概接近接近7大概6000噸6000噸的石棉瓦還沒有清印所以在這裡要特別跟部長就是做一個請命你們現在都已經測了是不是可以留下一個固定的窗口因為事實上這個讓災民跟業者知道拆石棉是要找誰
transcript.whisperx[417].start 12038.146
transcript.whisperx[417].end 12054.265
transcript.whisperx[417].text 要問誰要怎麼拆才合法才安全這個對於我們的災區來講這個是非常非常重要的是不是請部長回應一下跟委員說明因為的確在尤其之前在台南的災區然後遇到一個這樣子
transcript.whisperx[418].start 12055.986
transcript.whisperx[418].end 12078.886
transcript.whisperx[418].text 過去沒有發生過的颱風的路徑所造成的影響很大然後大家也都很辛苦所以我們當初設定了這樣子的一個工作站的方式那目前我們其實是跟台南市政府討論接下來的這個窗口由台南市政府來擔任但我們還是會全力支持包括相關的物資還是會由我們來提供
transcript.whisperx[419].start 12080.409
transcript.whisperx[419].end 12102.197
transcript.whisperx[419].text 部長我想在這裡我還是特別要再跟你做建議我認為由中央來做這一個固定的窗口因為物資當然是由我們勞動部來提供那如果這個固定的窗口是由我們來指揮的話我相信成效會更好其實你已經編了那麼多的錢環境部已經編了那麼多的錢這個超過20億 20億還是不夠
transcript.whisperx[420].start 12104.978
transcript.whisperx[420].end 12127.672
transcript.whisperx[420].text 前面的7億 第一次的7億 再來的20億後續我想還是要再追加的因為數量實在是太龐大了所以我想部長你考慮看看我希望這個固定的窗口是由你們你們把它就是可以那個總體的那個指揮這個對我們地方來講是一個比較好的
transcript.whisperx[421].start 12128.352
transcript.whisperx[421].end 12147.357
transcript.whisperx[421].text 那這樣好不好我是覺得我們可以用我們的南區中心來跟台南市政府一起建立一個平台那當然物資的提供協助我們都還是會做我們的南區中心跟地方政府我覺得南區中心就是跟台南市政府一起來合作一起合作大家一起協助我們還是願意做這個事情的謝謝部長
transcript.whisperx[422].start 12149.338
transcript.whisperx[422].end 12168.603
transcript.whisperx[422].text 那再就是也再一次感謝勞動部就是在丹納斯颱風災後你啟動了三大支持的一個方案第一個就是天然災害的那個臨時的工作津貼這個其實在這個整個災情的過程當中我們啟動了這個天然的工作津貼那也
transcript.whisperx[423].start 12169.875
transcript.whisperx[423].end 12189.077
transcript.whisperx[423].text 帮了很多很多的忙就是说因为很多就是我们临时要找到工人就是有这一笔钱其实让我们很好的去调度再来就是说职业训练的一个补助那第三个就是说创业贷款的本息的那个环角这一个其实部长
transcript.whisperx[424].start 12190.12
transcript.whisperx[424].end 12213.209
transcript.whisperx[424].text 我要跟你做一個探討就是說在農漁業的部分我們是爭取到了我們是爭取到了就是那個多了20萬然後是一年加三個月那他的利息他的利息是0.915非常非常的便宜可是你的青農的創業你們竟然就是給他只有半年
transcript.whisperx[425].start 12214.329
transcript.whisperx[425].end 12237.387
transcript.whisperx[425].text 我覺得相形之下這個對於就是這些青年創業的一個貸款那在面臨到大家一樣都碰到了這一個丹納斯颱風那農民跟漁民農業部可以做這樣的一個補貼那為什麼我們勞動部對於青創的一個補貼竟然只是半年而已這個是不是請說明一下
transcript.whisperx[426].start 12241.4
transcript.whisperx[426].end 12258.981
transcript.whisperx[426].text 是不是可以比照就是我們的龍一鳴這個創業貸款的貸款的還款應該委員指的是說這個勞動部創業貸款的還款的期限目前我們最長是六個月希望可以再延長
transcript.whisperx[427].start 12260.182
transcript.whisperx[427].end 12285.991
transcript.whisperx[427].text 沒有錯我想我們來研究一下好不好因為整體來講就是說這整個受創的面積就是大部分就是都是在整個就是在鄉村區那鄉村區的這一些青龍還有這一些就是說回到地方開設的一些小商店其實他是很值得就是說我們勞動部來協助他你看我們的農藝民都幫了這麼多了
transcript.whisperx[428].start 12287.517
transcript.whisperx[428].end 12314.344
transcript.whisperx[428].text 我們再研究一下這個事情好 那也希望就是那個部長研究好不好來 再接著跟最後跟部長探討一個農業移工他需要快速的一個荷花因為農業有季節性部長你知道這一段時間什麼東西什麼水果最好吃就是洋香瓜最好吃還有我們的蓮角也很好吃可是當我要一比一就是說我一個本老 一個外老
transcript.whisperx[429].start 12316.12
transcript.whisperx[429].end 12330.562
transcript.whisperx[429].text 這樣子的一個申請方案的時候通常就是把整個程序跑完了以後那進來的移工事實上緩不及急還有我很想邀請你有空到我們整個南部
transcript.whisperx[430].start 12331.303
transcript.whisperx[430].end 12352.944
transcript.whisperx[430].text 其實都可以讓你點名在我們的畜牧業裡頭很多是自己的孩子自己的孩子在養豬自己的孩子在養雞為什麼因為請不到本地的勞工這個是在畜牧業存在的非常非常大的一個困難我不知道部長怎麼看這個農業移工這一個速度
transcript.whisperx[431].start 12353.632
transcript.whisperx[431].end 12374.239
transcript.whisperx[431].text 跟文說明的確我們知道在農村地區的缺工的問題很嚴重那所以目前其實也跟農糧署這邊或者是跟農業部這邊我們其實在合作這個農業移工的合給的情況其實我們願意來跟農業部來討論怎麼樣加速因為這裡面的程序
transcript.whisperx[432].start 12374.813
transcript.whisperx[432].end 12395.65
transcript.whisperx[432].text 有些是劳动部的有些是在农业部的所以说是跨部会的一个合作因为你从一万二到两万事实上我们看到了这一个数字可是问题就是说这个数字是不是可以真正的落实到这个农村里头来因为你还卡了一个一个本劳一个外劳本劳就差不过了
transcript.whisperx[433].start 12397.878
transcript.whisperx[433].end 12412.684
transcript.whisperx[433].text 所以這個畜牧業這個畜牧產業有很多是家族式的為什麼他沒有辦法因為他請不到工人啊所以連他的女兒都是一起跳下來要養豬要養雞這個是存在的我們南部很大的一個畜牧困境
transcript.whisperx[434].start 12413.024
transcript.whisperx[434].end 12430.012
transcript.whisperx[434].text 是那個委員其實我覺得針對這個核發的或者申請跟核發的程序面的話我們跟農業部在討論啦因為其實我們在前一輪裡面我們已經盡量把勞動部這一端的程序盡量收到最短把它收到一個禮拜對不對我記得是
transcript.whisperx[435].start 12430.532
transcript.whisperx[435].end 12451.267
transcript.whisperx[435].text 可是我們招募的部分他跟農業部申請了以後要90天才有辦法到勞動部這裡來那雖然你這一端已經縮短了可是農業部那一端還是拉到90天所以我覺得這個是需要一個跨部會大家共同再來討論那個你剛才講90天部分還是他的效期啊
transcript.whisperx[436].start 12451.567
transcript.whisperx[436].end 12473.998
transcript.whisperx[436].text 他的校期 這是指的是他的校期那好那如果一個農業移工從申請到進來你們最短的時間可以拉到多久如果在國內承接的話速度就很快對但是因為如果涉及到海外的話還有在海外招工跟挑工的階段這部分就比較難
transcript.whisperx[437].start 12475.216
transcript.whisperx[437].end 12494.086
transcript.whisperx[437].text 一概而論的說有一個固定的數字可是部長其實基本上海外的一個招募本來就是移工的一個大眾對不對所以這個存在的困難就是在這個地方那我們還是希望就是跨部會的一個討論那也特別跟部長做一個
transcript.whisperx[438].start 12495.106
transcript.whisperx[438].end 12509.771
transcript.whisperx[438].text 提醒真的畜牧的一個移工非常非常的缺如果我們的畜牧產業要升級的話不是只有就是說智慧的一個設計而已這個人啊人的那個問題是要強化來解決
transcript.whisperx[439].start 12511.212
transcript.whisperx[439].end 12537.287
transcript.whisperx[439].text 跟我們說明其實我們有看到這個狀況那當然因為這個名額的申請其實會是目的事業主管機關來申請所以如果農業部有這個需求那也明確大家確認是有這個需求那在額度上名額上面要再做調整的話我想我們都是可以很開放的來討論的那在程序面我們也願意跟農業部一起來看怎麼樣縮短讓我們的農民朋友讓我們的農會讓我們地方上面最重要的產業能夠更方便這樣子
transcript.whisperx[440].start 12538.648
transcript.whisperx[440].end 12562.245
transcript.whisperx[440].text 謝謝部長部長我對你有期待因為你剛你跟我做過同事我知道你的能力是非常好的所以期待就是台灣的農業我們可以看到救世主好謝謝非常謝謝賴會員發言也謝謝部長跟同仁的答詢下一位我們要請劉建國召委發言
transcript.whisperx[441].start 12570.853
transcript.whisperx[441].end 12589.658
transcript.whisperx[441].text 謝謝主席 有請部長好 有請洪部長那感謝洪部長今天精闢的這個報告跟說明整本業務的報告有28頁我真的很用心的拜讀部長有詳細的說明勞動部在你帶領之下的方向與願景
transcript.whisperx[442].start 12591.69
transcript.whisperx[442].end 12613.103
transcript.whisperx[442].text 但我很遺憾這個成本的業務報告裡面找不到英文三個字部長知道是哪三個嗎找不到英文對找不到三個的英文字母沒有知道嗎猜到有講猜不到要把胡錫刮掉
transcript.whisperx[443].start 12619.06
transcript.whisperx[443].end 12624.01
transcript.whisperx[443].text 應該是關注EAP的問題對啊好那你不用掛了
transcript.whisperx[444].start 12625.222
transcript.whisperx[444].end 12654.902
transcript.whisperx[444].text 就算是中文的員工協助方案很抱歉這六個字也沒有在這本報告裡面出現過當然在15頁的時候你有針對這個加強營造友善職場環境落實這個職場的工作平權勞動部有很多的說明那諸如有提供這個安心生養的職場環境支持企業提供友善職場也加強這個宣導職場平權消米懷孕歧視等等等
transcript.whisperx[445].start 12655.823
transcript.whisperx[445].end 12680.563
transcript.whisperx[445].text 這些確實都有說明但唯獨沒有提到勞動部到底要如何協助企業建立推動EAP因為去年在責安署霸凌事件中勞動部 衛護部等相關單位都認同AAP的重要性但沒有一個單位去落實能做好的就連勞動部 自己也離譜了去年12月也在這個質詢台本期特別質詢
transcript.whisperx[446].start 12682.563
transcript.whisperx[446].end 12697.766
transcript.whisperx[446].text 也提醒部長就是說 勞動部的EAP平均一人500元左右而勞動部底下的2899 2899名的這個承攬人員不是用勞動部的員工協助方案
transcript.whisperx[447].start 12698.466
transcript.whisperx[447].end 12725.757
transcript.whisperx[447].text 那當時總統部長有引諾會來改善是 對 阿一年啊 到底現今的改善狀況怎麼樣 部長可以說明一下嗎好 跟委員說明 剛才委員在講的是兩個部分第一個部分是針對企業的部分 其實我們在114年2025年的時候 其實我們辦了10場的教育的訓練那總共有超過2000人次的企業代表來參訓那就是希望能夠把主管在這方面的敏感度跟關懷的
transcript.whisperx[448].start 12727.478
transcript.whisperx[448].end 12740.088
transcript.whisperx[448].text 的部分能夠做到更到位那我們也有大概超過50家的入場的輔導這都是在針對企業的部分來進行針對部裡面的部分的話因為委員其實也很關注所以我們那時候其實也承諾我們會把這個
transcript.whisperx[449].start 12743.23
transcript.whisperx[449].end 12763.204
transcript.whisperx[449].text EAP的範圍不只是放在我們的正式人力上面也包括我們的約聘的人員這些人員一併的納入到這裡面所以我們現在應該都已經放入到這裡面都變成是我們EAP的相關的對象但是部長114年度勞動部的EAP預算是45萬
transcript.whisperx[450].start 12766.134
transcript.whisperx[450].end 12791.066
transcript.whisperx[450].text 115年度的勞動部EAP預算也是45萬那是部門部的對對嘛對 部門部就不增加了那因為那匡論底下的所屬單位會增加那我們就拭目以待在審查預算的時候就好好來救教部長因為比較多的越過人其實坦白說是在我們的所屬啦是對 所以所屬都有增加有嗎
transcript.whisperx[451].start 12795.038
transcript.whisperx[451].end 12823.635
transcript.whisperx[451].text 我想預算審查室我一定會好好請教部長報告委員我們今年的EAP的那個契約的那個預算是本來是235萬多那因為那個諮商的時數有擴增所以我們後來擴增到280萬280萬3000多萬3926元你講今年的嘛對不對今年的 對嘛那明年我們也有再擴增
transcript.whisperx[452].start 12824.694
transcript.whisperx[452].end 12845.031
transcript.whisperx[452].text 擴增多少 大約明年我們擴增到350萬左右增加20% 是差不多嘛 是 對就那個單位而已還是總TOTAL 這是本土及所屬部跟所屬 是總TOTAL增加20% 是好 到時候我們再好好討論好不好好 謝謝那請部長看這個新聞
transcript.whisperx[453].start 12848.923
transcript.whisperx[453].end 12877.191
transcript.whisperx[453].text 這家公司承攬多項政府部門的員工協助方案委外契約嘛依照採購契約要有合格的心理諮商等專業服務但政府員工在尋求諮商服務時察覺有異陳警檢舉發現創意老闆根本沒有心理師的證書卻親自提供諮商服務這台北體驗署已經在涉日違反心理師法將這個老闆提起公訴了這部長知道嗎
transcript.whisperx[454].start 12881.889
transcript.whisperx[454].end 12903.465
transcript.whisperx[454].text 你們有委外他來做員工寫書方案嗎有做心理諮商的部分嗎有嗎勞動部有嗎你們不是這一家不是不是是哪一家報告委員我們不是這一家你們不是這一家好你們不是這一家你們有這一家的狀況嗎
transcript.whisperx[455].start 12904.4
transcript.whisperx[455].end 12914.288
transcript.whisperx[455].text 我們瞭解這一家的狀況可是我們沒有沒有這一家你們不是委任這一家嗎那你們委任別家比較像這一家的狀況嗎沒有沒有你確定是
transcript.whisperx[456].start 12915.478
transcript.whisperx[456].end 12933.312
transcript.whisperx[456].text 要不要再想一下是 我們目前的這一家是有合格的心理諮商的專業服務好都直接在線上就直接有這個服務好你看 這個是新聞已經出來了根據採購企業內容該公司需指派具有心理師資格的人來負責接聽電話
transcript.whisperx[457].start 12934.713
transcript.whisperx[457].end 12957.28
transcript.whisperx[457].text 接聽電話有些契約跟要求有心理諮商這個諮商心理臨床心理相關工作必須達兩年以上的這樣的一個工作經驗但是實際上這個就是沒有嘛本身沒有心理師的這個證書然後也沒有當然就沒有什麼什麼兩年以上的這些經驗嘛對不對所以你們確定你們都不都有齁都有具備嘛齁好謝謝
transcript.whisperx[458].start 12960.049
transcript.whisperx[458].end 12987.958
transcript.whisperx[458].text 你知道我們工部門目前尤其中央機關有多少單位委託這家公司嗎環境部 外交部 農業部 經濟部 教育部還有金門縣政府我要提這個就是台灣現今在處理這個員工協助方案的一個處境不僅做不好 甚至被人家騙了而且是一堆工部門被騙還好你們勞動部沒有被騙到
transcript.whisperx[459].start 12990.703
transcript.whisperx[459].end 13011.96
transcript.whisperx[459].text 阿彌陀佛部長也在做功德那公部門都會這個樣子你看民間企業會什麼樣子你看中央幾個部會啊我剛念了五六個以上還有包含地方政府那如果公部門都這個樣子的我再強調一次那企業部門會怎麼樣我們再看一個報導天下雜誌有專題
transcript.whisperx[460].start 13019.639
transcript.whisperx[460].end 13043.79
transcript.whisperx[460].text 霸凌性侵平轉為何企業員工協助方案失靈那這邊報導指出是EAP淪為刑事然後缺乏人性關懷企業引進EAP是基於企業形象而會真正關心員工所以我們勞動部在做EAP是要塑造勞動部的形象還是要真正關心我們相關的同仁
transcript.whisperx[461].start 13046.256
transcript.whisperx[461].end 13063.21
transcript.whisperx[461].text 裡面提到一般企業組不太主動會提供EAP的協助很多是等到出事的時候甚至員工親身才會積極的去連結還是再去啟動這類的資源所以現今的企業EAP更像是事後補救
transcript.whisperx[462].start 13064.617
transcript.whisperx[462].end 13090.358
transcript.whisperx[462].text 絕對不是事前的預防部長你再看一個數據我真的不曉得為什麼這樣因為這個EAP我已經講了兩三年而且是不只是部會我連院的層級我都一個一個一個去講在司法法制委員會在其他的委員會我都一而再再而三去講不厭其晚的講一而再三的提醒那我現在講說部長你看這個
transcript.whisperx[463].start 13091.859
transcript.whisperx[463].end 13117.959
transcript.whisperx[463].text 協助事業單位辦理員工協助方案我們100年08年這個是在疫情前嘛 對不對還有18場 人數是15 1500多109 110 11是疫情它降下來了 沒話講112 一樣10場 人數有多一點點113 一樣有10場 人數再往下降一點點今年是114 請教今年辦了幾場
transcript.whisperx[464].start 13121.784
transcript.whisperx[464].end 13147.801
transcript.whisperx[464].text 勞動部嗎對這個就是勞動部協助事業單位辦理的員工協助方案到今年為止已經辦了幾場今年辦了十場辦了十場的嗎對確定我的資料怎麼是七場我們今年辦十場好 您辦十場是人數多少目前是兩千 兩千二左右兩千二左右也多了沒有很多啊
transcript.whisperx[465].start 13154.445
transcript.whisperx[465].end 13179.245
transcript.whisperx[465].text 我們目前是規劃應該會有2200大概的人次的企業代表來參選所以部長認定有達標了我想這不是我們從我們的角度不一定叫做達標但是如果做得更多更好我們會盡量來進行的確現在部裡面也非常關注就是怎麼樣來規劃友善職場的部分友善職場的配套所以剛剛委員講的我非常同意
transcript.whisperx[466].start 13179.825
transcript.whisperx[466].end 13195.443
transcript.whisperx[466].text 其實EAP當然是一個工具可是最重要的目的還是要改變企業的文化讓企業有辦法可以更大程度去支持勞工我們從這個角度其實也會規劃一些相關其他的配套能夠讓這個配套起來以後能夠更善用EAP這樣的工具OK
transcript.whisperx[467].start 13196.3
transcript.whisperx[467].end 13223.089
transcript.whisperx[467].text 我再補充一個數據給部長通考台灣中小企業約莫大概是167萬家左右全體的企業98%提供將近917萬的就業數所以我們常說中小企業是台灣的骨幹但EAP對中小企業而言是什麼這個專題中有這邊提到了稱EAP對中小企業來講就是奢侈品
transcript.whisperx[468].start 13224.352
transcript.whisperx[468].end 13245.146
transcript.whisperx[468].text 尤其小企業要內要去建立一個EAP幾乎是不可能的任務因素很多甚至有很多就像環境部農業部找一間公司外包結果到底是不是真的EAP也不知道然後要協助中國企業解決這個問題不要讓EAP變成這個奢侈品推廣EAP是勞動部的工作
transcript.whisperx[469].start 13246.813
transcript.whisperx[469].end 13259.687
transcript.whisperx[469].text 這是勞動部的工作而且是要守重因為勞動部每年如果這樣召開市長教育訓練對中小企業設立EAP來協助員工部長你的看法到底有沒有實質的協助
transcript.whisperx[470].start 13262.433
transcript.whisperx[470].end 13278.848
transcript.whisperx[470].text 的確中小企業因為在相比於比較大規模的企業上面其實包括他的人資的制度包括他整體的這個企業內部的治理的狀況有的時候真的比比較大型的企業會差一點這是事實
transcript.whisperx[471].start 13280.169
transcript.whisperx[471].end 13299.557
transcript.whisperx[471].text 所以我们在推广的时候比方说我们确实看到确实比较有人资制度的企业他对EAP的掌握度会比较高那所以我们的确可能会需要在中小企业的协助上面更花一些心力因为如果他没有很健全的人资制度的时候确实要设置这个的挑战会比较大
transcript.whisperx[472].start 13301.072
transcript.whisperx[472].end 13326.392
transcript.whisperx[472].text 部長要講HR嘛 對不對這個報導的專題中也有提到就是說他有明確建議EAP要入法強化企業的責任部長怎麼看而且政府要扮演更積極的角色才能促使企業從出事再處理轉向預防式的管理這樣才能夠真正建立起這個堅固的社會安全網
transcript.whisperx[473].start 13327.657
transcript.whisperx[473].end 13343.589
transcript.whisperx[473].text 就像委員現在秀出來的報導他其實也強調這裡面就是人資跟HR在使用EAP上的角色因為EAP是一個系統可是要怎麼真的能夠把它使用的好其實要有一些人而且專責性的人去使用這部分其實這就是人資系統
transcript.whisperx[474].start 13344.349
transcript.whisperx[474].end 13365.661
transcript.whisperx[474].text 但是我說中小企業有時候它有人資的比例會比較低這也會讓他們去投入這個事情的意願會比較低其實同樣的狀況所以我們自己是希望說當然我們從大型的開始做可是我們其實現在也有一個規劃我們跟我們的福祉師其實我們也希望把這個企業友善職場的做法能夠建立一個資料庫
transcript.whisperx[475].start 13366.901
transcript.whisperx[475].end 13393.406
transcript.whisperx[475].text 然後讓這個資料庫讓大家都知道不同規模的企業在支持勞工上面做了哪些事情大家可以在不同層級上面或不同規模上面去互相的學習那因為可能30人的企業他很難去學習2000人的企業但30人的企業也許他比較有條件去學習40人50人的企業那我們怎麼把這樣子的這個友善職場的資料庫給做出來讓大家可以互相比較互相競爭我們是有這樣的考慮跟規劃
transcript.whisperx[476].start 13394.807
transcript.whisperx[476].end 13411.801
transcript.whisperx[476].text 好 部長這邊有一段話你要看一下這是現狀推動EAP對HR來說是一個高風險的工作許多HR的主管缺乏高層的支持所以他就很難說服他的老闆所以我們就應該扮演更記憶角色所以你對路華你的看法怎麼樣
transcript.whisperx[477].start 13412.702
transcript.whisperx[477].end 13440.246
transcript.whisperx[477].text 我覺得當然是可以大家可以來評估跟考慮的啦只是重點入法以後還是重點是怎麼去落實啦對啊沒有錯法規在台灣的中小企業跟產業的情境裡面其實落實都是反而我們會需要更花心力去思考的一個重點沒有錯啦但是有法制化之後落實會比較實際一點啦是速度也會加快一點好不好一個月內可以吧我們來做一些這個可行性的評估這樣子好一個月內好謝謝謝謝主席
transcript.whisperx[478].start 13441.948
transcript.whisperx[478].end 13456.597
transcript.whisperx[478].text 好謝謝劉警國召委的發言謝謝部長的答詢下一位請洪孟凱委員發言主席謝謝麻煩請洪部長有請洪部長
transcript.whisperx[479].start 13464.69
transcript.whisperx[479].end 13479.501
transcript.whisperx[479].text 好 部長好部長來之前本席就有就教過就是因為長榮航空的空服員事件而引發就說這個請假的一個相關的爭議那我知道說昨天我們勞動部已經有針對保障勞工並駕權的會議有召開了前天
transcript.whisperx[480].start 13482.683
transcript.whisperx[480].end 13501.179
transcript.whisperx[480].text 前天兩天前沒錯那現在當然裡面與會代表對於勞工請病假不得扣獎金或是不利處分有高度的共識但是對於不利處分的範圍就是所謂的天數有不同的建議那請教一下到目前為止我們自己勞動部的立場為何
transcript.whisperx[481].start 13503.115
transcript.whisperx[481].end 13519.188
transcript.whisperx[481].text 我想我們當然是我們之所以會召開這個會議就代表我們其實認為現在在勞工勤兵價上面確實應該做更進一步的保障尤其是面對可能有些雇主會過度的使用管理制度造成
transcript.whisperx[482].start 13520.289
transcript.whisperx[482].end 13543.679
transcript.whisperx[482].text 讓大家不敢請必須報病上班的狀況我想我們是意願我們是有這個意圖要來做制度上面的調整的這也是我之前一直在說的那的確現在是大家在思考的事情說這個保障的程度包括保障的天數那大家在這裡面做討論那所以我們禮拜一也邀請了各界一起來表達他的看法論舉從幾天到幾天
transcript.whisperx[483].start 13546.158
transcript.whisperx[483].end 13571.274
transcript.whisperx[483].text 因為一定是有一個Range嘛可能僱主代表會希望是說相對少一點嘛那勞工代表相對多一點嘛我都可以理解啦那或者說到之後還是會回歸到說主管機關的態度 立場因為到之後還是要定出一個時間點我們當然希望對勞工的保護可以多一點是 所以那時候會議裡面的Range有到幾天到幾天其實會議現場應該有人從三天 五天 七天
transcript.whisperx[484].start 13572.796
transcript.whisperx[484].end 13578.666
transcript.whisperx[484].text 12天15天都有人講30天也有人講是那所以到最後那好我請教後續
transcript.whisperx[485].start 13579.841
transcript.whisperx[485].end 13608.796
transcript.whisperx[485].text 部長 後續什麼時候會把它訂因為你開完會了既然你講說從3天到30天就10%到100%那總是到時候你還是要訂出來嘛那後續你要怎麼做第一個我們的確是在這些建議下面我們現在在綜合的評估那時間點那第二個是我們希望這個相關制度上面的調整包括請假規則上面的修訂我自己也希望盡快甚至我們希望明年大概就可以實施嘛
transcript.whisperx[486].start 13608.936
transcript.whisperx[486].end 13626.454
transcript.whisperx[486].text 明年14歲最快今年年底要出來我們能快我就盡量快啊是所以部長我現在確認就是說後續現在意見收集完畢還會再開第二次會嗎還是其實那天會議已經OK了那天是請大家一起來到這個會議但是過程裡面可能還會有針對個別我們會跟個別的
transcript.whisperx[487].start 13627.295
transcript.whisperx[487].end 13643.355
transcript.whisperx[487].text 發言的單位可能會再跟他們確認一下他們一些意見那他們考慮的實質考慮的點其實通常我們會有一個像這樣的會議可是因為私下我們跟這些工會包括跟這些企業還是會有些聯絡現在要看到的是我們勞動部的態度嘛
transcript.whisperx[488].start 13643.635
transcript.whisperx[488].end 13666.478
transcript.whisperx[488].text 就是说针对这个意见你已经有我肯定说我们开了这个会但是后续你开会要有结论那结论我现在因为我还有其他问题所以我是不是能够确认一个时间点什么时候我们会有后续的指引或者是劳工请假规则修正出来第一个我们希望尽快然后第二个我自己很希望明年就可以上路实施好所以说今年年底有办法出来
transcript.whisperx[489].start 13667.423
transcript.whisperx[489].end 13686.958
transcript.whisperx[489].text 才有辦法符合您的期待啊當然啊所以今年年底可以出來當然我沒有想在這事情拖延來那部長那另外請教有勞工代表建議要把友善請假制度列入ESG的一個揭露項目揭露內容本席覺得這也可能變成是我鼓勵
transcript.whisperx[490].start 13688.649
transcript.whisperx[490].end 13710.871
transcript.whisperx[490].text 友善的企業告訴我們全台的民眾哪一些雇主針對這個部分是友善的那也許他會有一個bonus就是說他在徵才的時候更多的勞工願意來去投這個投履歷來去應徵您怎麼看第一個納入ESG的部分我們很願意跟金管會在這部分來做討論
transcript.whisperx[491].start 13712.112
transcript.whisperx[491].end 13730.196
transcript.whisperx[491].text 那過去我們其實已經這個也不需要金管會同意因為勞動部如果說有的話其實就可以拔給金管會會做它是一個揭露EHCG揭露的一些範例那金管會會請各部會會放入ESG的部分來去做提出那就是勞動部如果說同意或說勞動部認為說這個東西是一個指標我們當然認為這是一個好的方法
transcript.whisperx[492].start 13730.636
transcript.whisperx[492].end 13756.582
transcript.whisperx[492].text 是 所以說你願意我們願意來嘗試但是這裡面當然就會有跟包括幾個相關的部會因為金管會他目前管的部分比較是在EHG的揭露上面部長 本席這樣子理解你剛回答的態度本席理解你剛回答的態度應該算是正向看待接納這一個意見我也希望這樣子好那這樣子不要說到最後沒有嘛那如果說沒有的話就政府因為政府是一體的
transcript.whisperx[493].start 13757.702
transcript.whisperx[493].end 13784.332
transcript.whisperx[493].text 我想政府是一體的不是互推皮球在這邊講完這邊算然後結果我到九樓大禮堂換要諮詢金管會諮詢財政的時候財政部長另外一套那如果說真的願意往這個方向推那是不是部長能夠譬如說召集找金管會換你找金管會來開會請金管會把他放入那就是我們往這個方向做是的委員政府是一體的但是我的發言人比較只能夠代表勞動部
transcript.whisperx[494].start 13785.692
transcript.whisperx[494].end 13809.014
transcript.whisperx[494].text 我覺得我們這個相關院現在大家非常非常關心病假協會檢查權的部分來行人別說我行為啦說實在勞動部願意放入如果說你有這樣的意向我覺得不會有其他部會說會否決勞動部但重點在於是說是不是把這個東西給揭露讓其他的企業能夠來去做遵循其實我覺得這個是加分項目
transcript.whisperx[495].start 13810.371
transcript.whisperx[495].end 13818.84
transcript.whisperx[495].text 這個叫做加分項目他不是說你把它揭露出來讓那個企業能夠有這個加分項目我覺得這是好事我們盡快來跟金管會討論吧盡快 對兩個禮拜內可以嗎可以啊好 謝謝部長最後一個問題
transcript.whisperx[496].start 13826.935
transcript.whisperx[496].end 13851.454
transcript.whisperx[496].text 勞動部在之前那個呂樹業有講是說就是加薪2000元來可以新聘移工我想先確認一下2000怎麼來的這個數字第一個2000這個數字我們其實當然當初有好幾個數字評估對 但本席跟很多國內人納悶就是說為什麼是加薪2000我們考慮幾件事情一個月30天加薪2000那平均一天加薪不到100塊
transcript.whisperx[497].start 13853.766
transcript.whisperx[497].end 13881.851
transcript.whisperx[497].text 那現在最低工資28590加薪2000平均不到十分之一啊那這樣子真的有實質的幫助本勞嗎跟我的說明第一個我們其實當初也評估如果把加薪的幅度拉得比較大的話那可能會受惠的本國勞工就會少一點就是如果加薪的幅度再拉大一點的話可能雇主會考慮的就會少
transcript.whisperx[498].start 13882.688
transcript.whisperx[498].end 13907.662
transcript.whisperx[498].text 可能受惠的會少一點沒有 僱主的想法一定是他加薪譬如說他加薪三千元他可以多請一個外勞那他重點就讓僱主去思考說他到底是要再多請一個外勞的人力來還是說他其實可以善待他原本有的員工所以我要提的事情是說其實我們在這次的配套其實有講加薪兩千可以取得一個名額但三年後你如果要保持這個名額你還必須再加一次
transcript.whisperx[499].start 13908.923
transcript.whisperx[499].end 13924.215
transcript.whisperx[499].text 三年後 就累進的加薪然後每一次都是兩千對 而且同樣的人數還要再加一次來 那部長我們在這次方案裡面是很明定這件事情的所以說三年有一個持續加薪的機制就保障這個員工如果說在旅宿業的話他可以持續
transcript.whisperx[500].start 13925.456
transcript.whisperx[500].end 13945.564
transcript.whisperx[500].text 增加他的收入另外一個部分就是怎麼樣監督確實有加薪我們會依照他的薪資單還是勞保會在我們的系統裡面在勞保裡面來去確認我們會確認他有比方說他這個企業如果需要10個增加的名額他就要挑10個相對低薪的勞工就是低薪的勞工
transcript.whisperx[501].start 13947.044
transcript.whisperx[501].end 13971.902
transcript.whisperx[501].text 比较低薪的来加薪那我们看到有加薪以后才能确保他这个名额所以说有先有确认他的一个加薪的部分那可能他就变是说他报他的薪资单或者说他的劳保申请如果没有加到的话我们如果没有加他是假加薪反正就是他申请填完了之后我们会这样粉丝理解一下我们会有一个申请机制有意愿的饭店业者他来去
transcript.whisperx[502].start 13972.382
transcript.whisperx[502].end 14000.208
transcript.whisperx[502].text 登錄申請機制並且提供相關的文件確實他有加薪了他才可以取得名額就是我們會檢核然後如果他是假加薪或他沒有做到加薪的話我們就會撤銷他的名額所以說他一定是先加完薪並且檢附相關的文件讓我們勞動部這邊確認之後他才可以取得一個聘請外勞的名額我們會來檢核這件事情你會檢核一樣我們會定期的來檢核你會定期檢核所以一開始的申請
transcript.whisperx[503].start 14002.629
transcript.whisperx[503].end 14027.96
transcript.whisperx[503].text 一開始申請會有一次的確認機制然後也會有定期的檢核我們會定期的檢核那如果他就是說他如果做假那就是廢掉他這個名額然後確保這個有加薪的事實達成所以如果說未來假設他先申請到我們也會不定期的集合因為變成是有多少申請的飯店業你其實是可以掌握的嘛對不對你會有一個譬如說
transcript.whisperx[504].start 14028.8
transcript.whisperx[504].end 14048.076
transcript.whisperx[504].text 用這樣子辦法來申請的飯店業的名單那業者名單裡面你可能不定期會集合抽查那如果說抽查集合那如果說裡面還有一些飯店業者他可能比較真的99%一定都是符合我們法規但如果說1%他又把它調回來或甚至說他就讓那加薪的員工
transcript.whisperx[505].start 14050.038
transcript.whisperx[505].end 14076.208
transcript.whisperx[505].text 離職等等那我們會取消他的我們就會按比例取消他的這個名額等於是說我們就是要確保一定是先保障本國勞工才有聘請外國 外籍員工這是我們政策設計的原意好 但是設計的原意沒有錯所以說本席也在這邊就教您是說到底我們的集合以及落實的方案是什麼所以現在目前都有想到這些部分我們會有查核的其實當然好 OK那未來等政策上路之後我們也要一一來檢視好不好 謝謝
transcript.whisperx[506].start 14078.327
transcript.whisperx[506].end 14090.895
transcript.whisperx[506].text 好謝謝黃孟愷委員發言謝謝部長答詢下一位請房卿黃委員發言謝謝主席我們請部長好有請部長黃委員好
transcript.whisperx[507].start 14097.267
transcript.whisperx[507].end 14122.258
transcript.whisperx[507].text 部長好 部長我先請教就是說勞動部在112年有公布一個勞僱雙方約定工資給付日及工資給付指導原則那這個是針對月薪這個月薪制的這個僱主在薪資發放時間上就是需要遵循的一些相關規範那我想請教就是說這個指導原則在112年開始推動之後
transcript.whisperx[508].start 14124.219
transcript.whisperx[508].end 14131.566
transcript.whisperx[508].text 那當時有一個推進的一個時程我想請教部長就是說到現在落實的這個狀況如何
transcript.whisperx[509].start 14135.047
transcript.whisperx[509].end 14151.984
transcript.whisperx[509].text 跟文報告112年那時候訂定的時候其實是因為有一些個案比如說保全保全人員他們這個月工資勞務給付完了要領薪水的時候下個月會到15號以後然後雇主才發薪是所以為了改善這個狀況當時就訂了這個原則
transcript.whisperx[510].start 14154.807
transcript.whisperx[510].end 14158.349
transcript.whisperx[510].text 那這個原則訂了以後呢 112年訂了以後我們113年有把地方政府都邀集過來那請地方政府就他們轄區內的部分要積極輔導然後去了解那目前為止我們其實有請地方政府了解有沒有這個勞工陳情
transcript.whisperx[511].start 14174.296
transcript.whisperx[511].end 14201.867
transcript.whisperx[511].text 就針對他的工資給付發放日覺得有權益受損的勞資增益案件目前這樣的案件是不多不過我們今年過完之後明年初的時候會再邀集地方政府我們再做一個檢視滾動式的去檢討那我想請教就是說你們自己有沒有去盤點就是說這個企業或者是地方政府跟你們回報的就是有遵照這樣的一個指導原則來進行
transcript.whisperx[512].start 14204.368
transcript.whisperx[512].end 14224.128
transcript.whisperx[512].text 因為依法上面呢這個雇主其實只要他有定期每個月支付兩次工資然後雙方如果約定有支付一次那在這個指導原則下其實雇主是不會有違法就是他的發放薪資日其實是雙方議定
transcript.whisperx[513].start 14224.949
transcript.whisperx[513].end 14249.392
transcript.whisperx[513].text 所以這個部分我們目前是透過這個地方政府他去訪視事業單位的時候幫我們了解那普查的部分我們是沒有做這樣子動用到大家去進到事業單位普查但是我們是透過地方政府要了解所有的勞資爭議案件有沒有這一類型的所以你們是透過勞資爭議案件去看有沒有接獲陳情或者是
transcript.whisperx[514].start 14250.753
transcript.whisperx[514].end 14265.666
transcript.whisperx[514].text 那如果說因為當初你們有這樣的一個指引有一個指導原則那也有特別提到就是說可能在2023年就是剛開始的時候你們有指引就是說500人以上就是10日那到2025年就是5日
transcript.whisperx[515].start 14266.767
transcript.whisperx[515].end 14283.743
transcript.whisperx[515].text 就是有這樣的一個指導原則那我不知道說這些企業有按照你們這樣的一個指導原則下去做或者是沒有那你剛剛講的就是說好像就是地方的這個地方政府好像也沒有回報就是說有類似的這個勞資糾紛
transcript.whisperx[516].start 14286.886
transcript.whisperx[516].end 14315.918
transcript.whisperx[516].text 那如果没有的话那你怎么去知道就是说我原本有这样的一个指导原则也希望就是说我们的这个资方能够尽早把这个薪资发放到这个这个劳方的手上嘛那既然有这样的一个指导原则那你们是不是也要去统计一下到底有多少人有按照这样一个指导原则去做或者是没有那我相信很多的这个劳工都希望这个能够尽早他劳务都已经这个
transcript.whisperx[517].start 14316.818
transcript.whisperx[517].end 14337.581
transcript.whisperx[517].text 工作都已經整個月的工作都做完了這個月的薪資在下個月是不是能夠儘早能夠拿到也許他會有需要家裡面的經濟的開銷都需要這筆錢既然有這樣的一個指導原則你們是不是也要去統計一下到底有沒有去落實
transcript.whisperx[518].start 14338.402
transcript.whisperx[518].end 14351.498
transcript.whisperx[518].text 是的委員我們現在是有規劃在明年的時候會請地方政府幫我們針對轄區內的事業單位特別規模大的部分去了解然後回報我們勞動部做一個這個檢討這個指導原則的一個參考
transcript.whisperx[519].start 14354.341
transcript.whisperx[519].end 14376.64
transcript.whisperx[519].text 那我想請教就是說因為我們這個指導原則也沒有什麼法則可是我們在那個勞基法上面就有約定工資支付的這個相關規定跟法則那有沒有未來有沒有可能就是把我們原本的這個勞僱雙方約定工資的給付日還有工資給付指導原則這個部分直接入法有沒有可能
transcript.whisperx[520].start 14378.796
transcript.whisperx[520].end 14392.835
transcript.whisperx[520].text 委員我們可能步驟上面會先了解實際上面的狀況跟勞工或者是工會對於這一方面權益受損的情形那了解過後我們再評估這個法制面的部分有沒有再需要加強的地方好
transcript.whisperx[521].start 14393.456
transcript.whisperx[521].end 14419.581
transcript.whisperx[521].text 我希望就是說不論是公部門或者是私部門應該是要先從公部門自己做起因為我們有很多各單位都會有月聘僱人員或臨時人員那如果薪資可以在這個勞務的隔月的5日內就可以拿到的話其實我覺得應該是你們既然勞動部有這樣的一個指導原則那是不是可以先從公部門這邊做起
transcript.whisperx[522].start 14421.397
transcript.whisperx[522].end 14445.973
transcript.whisperx[522].text 委員您的這個提示我們可以盡快跟公共工程委員會還有我們這個人種這個部分我們做一個溝通協商評估看這個部分怎麼落實下去因為有很多都是到月中的時候才領到那如果既然我們有這樣的一個指導原則那是不是就先從公部門自己做起
transcript.whisperx[523].start 14446.673
transcript.whisperx[523].end 14472.815
transcript.whisperx[523].text 對不對先從立法院做起也可以或是先從勞動部你們自己的這個約聘僱人員開始做起是不是可以這樣子做我們來參考委員的這個建議好那接下來我想請教部長就是說我們之前這個80歲免巴士量表那可以申請這個外籍看護外籍看護工那我想請教就是說從這個制度開始之後到現在申請的狀況如何
transcript.whisperx[524].start 14474.036
transcript.whisperx[524].end 14497.909
transcript.whisperx[524].text 那會不會排擠到一些重症的這個患者就目前我們看到的數據從8月開始上路申請到目前11月應該是11月初吧那我們看到的數據是目前因為這個修法而取得資格而有來申請的大概是1萬多了1萬人這樣子
transcript.whisperx[525].start 14498.823
transcript.whisperx[525].end 14512.808
transcript.whisperx[525].text 那我們當然希望目前還是希望透過各種配套來去降低當初大家其實可能遇到的衝擊所以當初我們在8月的時候我們其實也提出了六大的配套的措施希望來去降低衝擊
transcript.whisperx[526].start 14514.329
transcript.whisperx[526].end 14531.234
transcript.whisperx[526].text 所以目前的狀況是還好不會去衝擊到這個可能重症或者是這個重度殘障這些朋友的這個權益我們確實還是有聽到有一些重症的家庭他們也在表達他們的
transcript.whisperx[527].start 14532.614
transcript.whisperx[527].end 14560.712
transcript.whisperx[527].text 這個外籍的康護那近期其實當然會各種的在工作現場會表達說是不是想要換到別的地方去確實會有這樣的一個狀況也會有這樣子的表達那我們也了解這樣子的表達存在那只是我們還是希望因為修法通過了那從行政部門角度我們還是要想辦法執行然後來降低衝擊所以只要能做的降低衝擊的我想我們還是會盡力來做
transcript.whisperx[528].start 14561.973
transcript.whisperx[528].end 14581.01
transcript.whisperx[528].text 因為其實我們都會聽到就是說原本的外籍看護他可能想要他會覺得說這個比較不好照顧那他想要換也許他會跟家人會特別提到就是說他想要換個環境 換個工作
transcript.whisperx[529].start 14581.59
transcript.whisperx[529].end 14607.032
transcript.whisperx[529].text 那通常這個家庭他也許希望他留下來就會給他薪資可能再加一些所以我希望就是說勞動部針對這部分你們應該也要持續去關心因為確實這個也會造成重症家庭的比較大的一個負擔而且外籍看護他也許他會一直表達他想要
transcript.whisperx[530].start 14608.913
transcript.whisperx[530].end 14629.518
transcript.whisperx[530].text 換個環境所以我希望說你們真的也要持續去關心這樣的一個事情不要讓後面真的原本家裡面有這樣的一個家人就已經這個負擔就已經蠻大的就已經很辛苦了那如果又遇到這個看護他又想要跳槽要跳到其他地方去其實這個對這個家庭來講都是負擔蠻大的
transcript.whisperx[531].start 14633.46
transcript.whisperx[531].end 14661.879
transcript.whisperx[531].text 那我希望就是说部长针对这一部分我们还是持续关心那我还是会持续关心因为确实这个问题是还存在的因为我们在跑行程的时候都会有听到这样的一个声音我们有收到这样的讯息所以我们持续关心不要后面造成这样的一个家庭更大的一个负担谢谢谢谢房秀安委员的发言谢谢部长的答询下一位请林淑芬委员发言
transcript.whisperx[532].start 14670.526
transcript.whisperx[532].end 14680.252
transcript.whisperx[532].text 好 謝謝主席是不是再請我們洪部長有請洪部長蘇分委員好
transcript.whisperx[533].start 14681.093
transcript.whisperx[533].end 14704.591
transcript.whisperx[533].text 部長在政策上面最近拋出了一個小孩的家庭也可以聘外籍家庭幫傭行政院在研議就是說只要現行的家庭幫傭每個月5000元的就業安定費提高到8000元就可以以價值量大概朝著這個方向去開放
transcript.whisperx[534].start 14705.191
transcript.whisperx[534].end 14714.617
transcript.whisperx[534].text 你覺得勞動部在行政院的指示之下你會這樣子做嗎我想我們都是綜合的在評估中
transcript.whisperx[535].start 14715.51
transcript.whisperx[535].end 14741.966
transcript.whisperx[535].text 綜合式評估在這裡我讓我提醒你幾個問題婦女薪資還有勞政發布的新聞稿反對他們認為放寬聘僱家庭幫傭這樣的人力市場只能加惠少數富貴人家凸顯社會不公平的現象會使現行公共托育服務倒退回家庭化過度市場化的模式
transcript.whisperx[536].start 14742.426
transcript.whisperx[536].end 14765.5
transcript.whisperx[536].text 好 我就我剛才講行政院指示的就業安定費用從五千提高到八千可以以價質量這一句話來講這一句話顯然以價質量就不是每個人可以負擔得起的嘛就不是要讓每個人負擔得起嘛就是為了某個經濟能力以上的人在開這個方便門的嘛不是嗎 這一句話
transcript.whisperx[537].start 14770.677
transcript.whisperx[537].end 14799.127
transcript.whisperx[537].text 就業安定費要繳8000喔因為剛剛委員在講到一些民間團體的聲音我們其實也有聽到也有看到所以現在就是各種不同的聲音因為的確有人講到他的需求然後各種不同的聲音但就綜合在評估有人 那有人是誰啊現在行政院講的是一個月就業安定費8000以價質量他就不是要讓大家來用的嘛以價質量就是要限縮在用得起的人才能用嘛
transcript.whisperx[538].start 14800.427
transcript.whisperx[538].end 14820.627
transcript.whisperx[538].text 你覺得這樣的政策會是一個好的政策嗎你的政策目標鎖定的是有消費能力有經濟能力高的那一些婦女嗎那我現在再跟你提醒第二件事當全世界所有的國家都在對公共政策就是在
transcript.whisperx[539].start 14821.368
transcript.whisperx[539].end 14847.427
transcript.whisperx[539].text 解決少子化幫女性幫年輕人的家庭解決托育的問題的時候都是往國家幫忙養的方向不是嗎我們也是如此號稱啊但是當我們也跟著全世界潮流再往國家幫忙養的方向的時候怎麼會突然轉彎變成孩子自己找外擁帶自己養
transcript.whisperx[540].start 14849.329
transcript.whisperx[540].end 14872.375
transcript.whisperx[540].text 你覺得這樣的轉彎適合嗎那我再提醒你第三件事移工政策的最核心是什麼移工政策的最核心是它只能是補充原則絕對不能夠產生替代你們說你們要做政策評估你心裡面也有數這個東西會不會搶走了國內從業人員的工作
transcript.whisperx[541].start 14878.052
transcript.whisperx[541].end 14888.539
transcript.whisperx[541].text 大家都知道即便是補充原則他也會產生另一種效果對國內的員工衝擊很大是什麼這30年來你知道的部長是什麼即便是補充原則對國內的勞工還是產生很大的衝擊是什麼勞動條件上面勞動條件簡單來講薪資的滑坡薪資的滑坡
transcript.whisperx[542].start 14907.448
transcript.whisperx[542].end 14926.677
transcript.whisperx[542].text 低薪化本來我們是有國內的就業人員如果你政策適當你不是補充你搶走了國內不管是家庭幫傭的家事服務的國內居家托育的或是保姆在宅這個托育的
transcript.whisperx[543].start 14927.677
transcript.whisperx[543].end 14950.467
transcript.whisperx[543].text 或是幼兒園的 幼兒園的生意也都一樣啊本來是這樣的 而且每個保姆每一個人都要有合格的證照要上過課 要訓練當國內的托育是這樣子專業化在前進的時候你們外籍移工的開放有可能要證照嗎會跟保姆一樣要證照嗎
transcript.whisperx[544].start 14955.427
transcript.whisperx[544].end 14971.187
transcript.whisperx[544].text 委員這真的是在總體的評估之中欸啊 抽屜裡面喔總體的評估之中總體的評估 你先就我問就教於你的你提一下你個人的看法 回應一下
transcript.whisperx[545].start 14973.736
transcript.whisperx[545].end 14983.2
transcript.whisperx[545].text 任何外國人力的開放與否的政策當然都要那我先問你一句話啦提供家事勞動服務的還有保母的 顧小孩的還有幼兒園從業的你覺得這個產業 這一些產業
transcript.whisperx[546].start 14992.003
transcript.whisperx[546].end 15013.901
transcript.whisperx[546].text 服務業支援服務業從業人員有多少在家庭幫傭家事勞動托兒育兒這個領域總的加起來的總就業人口數是多少你告訴我清潔人員保姆家事服務家事勞動有多少人有多少就業人口
transcript.whisperx[547].start 15015.643
transcript.whisperx[547].end 15040.043
transcript.whisperx[547].text 家事服務大概是數千到萬吧你有在說 我有聽到對不對家事服務數千到一萬家事服務 家事服務的部分家事服務保姆餒對 保姆不是家事服務我現在問你總的啊總的我可能要另外再講家庭幫傭他要來取代誰的工作啊難道不是保姆嗎不是家事服務嗎家事勞動 家庭幫傭啊
transcript.whisperx[548].start 15042.219
transcript.whisperx[548].end 15066.583
transcript.whisperx[548].text 然後小孩就從公共領域公共托育回到家庭但沒有衝擊到幼兒園沒有衝擊到托兒那個保母的這個托兒產業嗎衝擊多大我先問你是從業人員有多少目前詳細的數字我可能手邊沒有好我現在告訴你
transcript.whisperx[549].start 15067.526
transcript.whisperx[549].end 15087.939
transcript.whisperx[549].text 保姆清潔人員等其他服務業還有所謂的資源服務業從這一些來看家庭幫傭所替代掉的從業的女性比例這一些從業女性大概佔整體女性的從業人口的有人推估是7.7%所以推估起來總的
transcript.whisperx[550].start 15090.1
transcript.whisperx[550].end 15107.221
transcript.whisperx[550].text 女性就業人數是510萬以7.7%去推估從業人員有三四十萬三四十萬保姆家庭幫傭清潔人員還有這個公共托育托兒這一些總的加起來幾十萬
transcript.whisperx[551].start 15109.953
transcript.whisperx[551].end 15137.375
transcript.whisperx[551].text 你可能會說我可能人家這樣講法是高退估那也不管兩萬也很多三萬保姆三萬也很多人家剛才就是這樣在質疑你當初開放這個長照的外傭外籍移工不是也是這樣退估嗎那我現在也是這樣退估給你看嘛所以在這樣子裡面會受到這幾十萬的人的就業會受到多大的衝擊我現在還在講喔
transcript.whisperx[552].start 15139.212
transcript.whisperx[552].end 15163.401
transcript.whisperx[552].text 沒有這個政策以前 你們還沒有開放嘛現在評估嘛 沒有開放以前很多職業婦女仰賴就是她二度就業就去當終點費的清潔或是到府服務的保姆他們去取得證照所以這是從業人員都是中高齡的台灣婦女然後如果你們把這個門檻鬆綁以後呢大家都去請外籍幫庸的話這個會失業的啊
transcript.whisperx[553].start 15166.711
transcript.whisperx[553].end 15186.425
transcript.whisperx[553].text 再來我剛剛講孩子留在家裡面衝擊的也是幼兒園托兒所托嬰中心也是女性衝擊的也是女性再來我剛剛講的從業人員要證照你現在把他外籍化了他連語言能力都不一定好你顯然你們覺得看顧孩子就是吃喝拉撒睡
transcript.whisperx[554].start 15187.185
transcript.whisperx[554].end 15213.863
transcript.whisperx[554].text 整個國家在整個公共托育還有這個保姆上照顧幼兒上我們都專業化的往證照制度在推結果國家在前進的時候你們如果政策轉彎專業化 證照化在轉彎那你們就是認為說這個幼兒只需要照顧他嬰兒吃喝拉撒睡幼兒看顧他不要跌倒不要有危險這樣子而已嗎
transcript.whisperx[555].start 15216.927
transcript.whisperx[555].end 15222.265
transcript.whisperx[555].text 語言文化上的隔閡也不重要然後再來呢
transcript.whisperx[556].start 15224.349
transcript.whisperx[556].end 15250.821
transcript.whisperx[556].text 我們在講說這個經濟能力誰可以負擔經濟能力誰可以負擔你們以價質量你們已經宣稱了這不是給一般婦女用的光沒有聘僱的成本你就要先繳8000元的就業安定基金那再加上聘僱的我現在在講外籍移工不是源源不絕你還要產業界在搶
transcript.whisperx[557].start 15253.117
transcript.whisperx[557].end 15268.663
transcript.whisperx[557].text 還有跟這個長照看護的在搶移工的價格是不便宜的不便宜的再加上你的就業安定基金 一個月不是3萬 4萬啦 最少5萬但是呢什麼人負擔不去 每個月5萬 8萬 什麼人負擔不去保證什麼人負擔不去
transcript.whisperx[558].start 15281.926
transcript.whisperx[558].end 15303.084
transcript.whisperx[558].text 金字塔頂端的家庭一個月可以花8萬金字塔頂端哪有一個國家的誘餌開放家庭幫傭 你是服務你的國家政策是服務有錢人而已這樣的政策是最好的政策嗎還直接說我要以價值量
transcript.whisperx[559].start 15305.066
transcript.whisperx[559].end 15333.196
transcript.whisperx[559].text 你們要 你們瓦解了這個公共托育的政策大家都大肚子餓 去搶一個來購公共托育瓦解誰受災受災的當然是那個經濟能力負擔不起不要以為你們不會衝擊到產業衝擊到婦女 中高齡婦女的就業你們還衝擊到產業而你們還說你們在評估 我覺得你們就是要 因為這麼多年來一直都是要啦
transcript.whisperx[560].start 15335.832
transcript.whisperx[560].end 15347.344
transcript.whisperx[560].text 再來 我再教你 部長你覺得一個個人僱主個人聘僱一個家事個人聘僱的家事幫傭或是其實外籍移工看護的也一樣
transcript.whisperx[561].start 15348.553
transcript.whisperx[561].end 15366.057
transcript.whisperx[561].text 作為一個個人僱主他真的有能力把勞動條件給看守好嗎更不要講他的勞動環境你可以給人家一個單獨的獨立的然後勞動條件你的勞動條件要怎麼定難道要放任跟看護長照一樣嗎24小時全年無休給那麼一點點的加班費就買斷了他
transcript.whisperx[562].start 15373.318
transcript.whisperx[562].end 15401.957
transcript.whisperx[562].text 當成21世紀把它當成現代奴隸一樣的驅使嗎你們如果去你們對於他的勞動條件要怎麼把關你有辦法把關在私領域在私宅裡面有辦法把關嗎勞動條件你要怎麼設定你沒有辦法設定要再一次的步入我們長照長照看護的外籍移工的那種處境嗎你的想像是什麼你就這一點你來談談看
transcript.whisperx[563].start 15406.025
transcript.whisperx[563].end 15430.697
transcript.whisperx[563].text 這個相關的政策的確各方有不太一樣的意見然後不太一樣的需求所以我們現在針對這些不同的各方 少數的各方啦少數 你忘了講兩個字 少數我們針對這些各方的需求就是在做評估跟各種可能效應等等的評估目前的情況就是這樣子從長照看護裡面我們已經看到很多了就是說大家玩家衝突
transcript.whisperx[564].start 15432.149
transcript.whisperx[564].end 15453.69
transcript.whisperx[564].text 脅迫雇主 逼迫雇主說你非得同意我轉換雇主不可那我現在在問你說 家庭幫傭也一樣啊是不是可能成為移工轉換行業的跳板有沒有可能 管理上的漏洞啊有沒有可能要洗澡這要再算什麼 要再換雞要再炒
transcript.whisperx[565].start 15455.131
transcript.whisperx[565].end 15482.996
transcript.whisperx[565].text 大家都覺得這是外籍移工的問題 可是事實上是嗎你如果沒有訂出好的勞動條件然後人家產業上虛空籍啊然後在那裡人家用好的薪資而且固定的工時而且要符合勞基法的規定人家就挖走了啊然後流動性也會跟著跳啊跟搶 流動性高啊
transcript.whisperx[566].start 15484.704
transcript.whisperx[566].end 15495.074
transcript.whisperx[566].text 不是嗎 柏中你都不敢說 你一句話就不敢說你都不敢說 你都知道啦 心知肚明可是呢 你們會不會還是要繼續要這樣做我曉得我問你這樣好了我這樣做好了 第一個你說要做評估 請問你們產業衝擊評估有沒有做了 委託了沒
transcript.whisperx[567].start 15509.076
transcript.whisperx[567].end 15536.267
transcript.whisperx[567].text 就是各方面我們都在評估你誰評估啊 你要專業去評估還是你們自己評估 怎麼評估有些部分我們跟衛福部討論第二個 有沒有做過性別平等評估有沒有做出符合兒童最佳利益的評估你難道不需要嗎你這樣子交給外籍移工來吃拉撒碎的顧小孩跟我們朝向證照制度專業化的顧小孩保姆都要證照
transcript.whisperx[568].start 15537.625
transcript.whisperx[568].end 15561.904
transcript.whisperx[568].text 你這樣子沒有損及兒童最佳利益嗎你在性別上面對我們二度就業的婦女就業難道沒有衝擊嗎你們在性平上產業衝擊上要怎麼評估你說你們評估你們怎麼評估不是都要說我要做評估我要做評估五個字不是你們要請誰做要怎麼做要做哪些評估
transcript.whisperx[569].start 15569.142
transcript.whisperx[569].end 15592.543
transcript.whisperx[569].text 現在就是綜合在評估中你不敢講 你也回答不出來連說你們有沒有做這一些評估好 那我問你你認不認為需要做兒童最佳福利的這個評估你認不認為應該要做是不是符合兒童最佳福利要不要做這種評估我覺得各個層面都必須考慮
transcript.whisperx[570].start 15593.883
transcript.whisperx[570].end 15601.236
transcript.whisperx[570].text 你繼續打高空 你講不出來好 沒關係 我知道因為真的是回答不出來啦
transcript.whisperx[571].start 15604.231
transcript.whisperx[571].end 15631.113
transcript.whisperx[571].text 我也是傻眼那我問你別的問題好了現在旅遊業開放中階移工那以薪資門檻三萬二要求要有華語能力技能資格大家知道旅宿業這個不是地帶啦這補充啦 因為沒有人要走嘛但是最怕衝擊的就是薪資衝擊嘛但是在這種狀況裡面我要問你我也時間有限我只問你一件事情啦
transcript.whisperx[572].start 15631.954
transcript.whisperx[572].end 15638.081
transcript.whisperx[572].text 你知道旅宿業大家流行一句話 整本店都要倒了啦都要倒了啦
transcript.whisperx[573].start 15640.667
transcript.whisperx[573].end 15661.094
transcript.whisperx[573].text 你在審核他缺工的相關資訊的時候要不要審核他的營運狀況那特別是大家都知道台灣旅宿業的環境不好經營不善如果倒閉了這個移工被迫要失業然後這些失業因為關閉倒閉的移工你的管理配套是什麼
transcript.whisperx[574].start 15662.952
transcript.whisperx[574].end 15673.578
transcript.whisperx[574].text 跟委員說明第一個我們目前其實目前開放的比較是在這個觀光旅館跟飯店業那這個觀光旅館跟飯店現在倒閉潮很多嗎倒閉潮當然這個企業的狀況我想
transcript.whisperx[575].start 15681.882
transcript.whisperx[575].end 15696.009
transcript.whisperx[575].text 目前他有這個缺工的缺包括我們在我們自己的調查你也看出他有這個缺工尤其是比較基層的工作的缺工的需求是有的所以我說補充原則不是替代是 台灣人不要做所以補充沒關係
transcript.whisperx[576].start 15696.969
transcript.whisperx[576].end 15725.145
transcript.whisperx[576].text 但我現在在說的是倒閉潮倒閉潮可是你申請了一大堆外籍移工進來這個旅館這個飯店倒閉以後這些移工的安置的配套未來的管理配套是什麼你總不能叫他在那裡漫長的等待吧當然如果這個企業遇到了比方說經營不善的狀況無法再經營下去那當然這個移工就變成我們要來協助全力協助他轉換
transcript.whisperx[577].start 15726.895
transcript.whisperx[577].end 15749.284
transcript.whisperx[577].text 就慢慢的等待這樣子嗎其實不是慢慢等待因為接下來其實我們也把現在在技術能力的需求給打開了所以我們認為對於轉換也會比較有利所以你叫下游去幫他擦屁股那你為什麼不再上游你需不需要在他申請的時候要對於他的營運狀況也要一併考量從上游源頭管理嘛
transcript.whisperx[578].start 15750.868
transcript.whisperx[578].end 15779.978
transcript.whisperx[578].text 不用嗎然後大家進來然後一直管理不善的營運不善的也申請了可是做沒幾個月就倒了你還要幫他處理跟委員說明第一個當然這部分這個飯店業他的管理或他的經營這部分可能很難是勞動部這邊來去說我要對你設一個我現在講是他要申請外籍移工你在審查的時候要不要框一個要件
transcript.whisperx[579].start 15782.185
transcript.whisperx[579].end 15796.395
transcript.whisperx[579].text 我不知道這是不是一定要啦但是我想到的是倒閉的時候要怎麼處理就算要檢視的話我們可能要跟消防部一起討論那我再問你如果這個倒閉非自願性失業的移工那他會不會適用這個那個失業給付失業給付目前是沒有的因為失業給付主要是來自救保
transcript.whisperx[580].start 15807.881
transcript.whisperx[580].end 15835.994
transcript.whisperx[580].text 那救保啊 雇主啊所以我才講作為一個個人雇主是不是有能力cover起來他其實連勞動條件都很難去cover起來所以個人雇主我們一直在主張個人雇主的這一個制度要不要落日作為外籍移工的雇主從長照到現在你要再開放我們都一直在討論說要不要落日結果你們一直在討論要不要再開更多的門
transcript.whisperx[581].start 15836.974
transcript.whisperx[581].end 15864.834
transcript.whisperx[581].text 那個人聘僱外籍移工的僱主他的能力就是這麼的有限他就是在勞動條件上沒有辦法去支撐然後呢 你如果再叫他講說如果失業在那裡漫長等待對人家 如果一般勞工也是不公平的啊那在這種狀況裡面 你叫他救保費用你也繼續繳 幫這些移工也繳那是不可能的啊 對不對我問你啦 廠工有沒有繳救保
transcript.whisperx[582].start 15865.612
transcript.whisperx[582].end 15875.108
transcript.whisperx[582].text 沒有 廠工的老闆也沒有因為廠工不會他們就三年一聘不會突然倒了廠工沒有算因為他補充人力所以他沒有算在救保裡面
transcript.whisperx[583].start 15875.851
transcript.whisperx[583].end 15896.031
transcript.whisperx[583].text 對啊 少數嘛就是基本上還算穩定的嘛但是飯店旅宿可能那個不穩性一定很高你要去想一想啦稍微要想一下好 謝謝重點是剛才在講的只為少數人服務的那一個開放那個門要好好的想啦 謝謝好 謝謝接下來請盧縣議委員來做詢問
transcript.whisperx[584].start 15910.193
transcript.whisperx[584].end 15936.48
transcript.whisperx[584].text 有請部長各位好新的一年要到了那部長我之前我有詢問說關於我們原住民的那個植栽的風險之前我們在看的時候是植栽風險就高了16倍因為這樣看的話3.54這是我們原住民的
transcript.whisperx[585].start 15937.06
transcript.whisperx[585].end 15957.796
transcript.whisperx[585].text 一般國人的話是0.221那死亡率是全國的6倍也就是說我上次有詢問我們的何部長說能不能提供一個所謂的我們的死亡類別或者說分析它的形成的原因有助於我們以後預防它的發生所以有在做這方面的分析或者是說進度嗎
transcript.whisperx[586].start 15960.817
transcript.whisperx[586].end 15979.467
transcript.whisperx[586].text 對不起 我在說明就是說我們勞工的職災死亡個案分析因為我們知道現在我們的死亡率是高於一般國人的6倍我們職災風險是16倍所以在去年的時候我有請勞動部提供我們這方面的一個資訊給我可是到現在還沒有看到
transcript.whisperx[587].start 15981.428
transcript.whisperx[587].end 16009.647
transcript.whisperx[587].text 我們就把這個資訊卡還提供給委員吧好不好一個禮拜內提供可以好 謝謝其實常常會發生就是說我們的勞工是因為墜落或者是層層轉包這些營造業我們會發現說去找這些真正的老闆的時候其實找不到是這個方面的一個機率有沒有變少因為我覺得去年我們在詢問的時候很像責任歸屬
transcript.whisperx[588].start 16012.469
transcript.whisperx[588].end 16033.922
transcript.whisperx[588].text 實際找不到應該要負責的老闆所以這方面你們有在做追蹤嗎對 這也是這次修法的重點我想知道說這方面比如說轉包的責任鏈你被勒令停工的這一年裡面實際有停工的案例嗎有有嗎當然希望能夠一併報給我好嗎當然好
transcript.whisperx[589].start 16035.723
transcript.whisperx[589].end 16062.281
transcript.whisperx[589].text 那就是我們現在有在推我們的原住民的降災或是減災的一個專案比如說你們引進了什麼現代科技 科技減災的工作坊我有看到你們所做的努力可是我想知道說這些真正的智慧科技防災的這個部分你要怎麼落實在部落或是非典型僱用的這些中小型包商所僱用的原住民勞工你要怎麼實際應用上 你有沒有想到
transcript.whisperx[590].start 16063.711
transcript.whisperx[590].end 16083.246
transcript.whisperx[590].text 這個智慧防災的做法是現在業界在針對治安的問題非常重要的部分甚至很多還運用AI來去做相關的風險評估跟決策當然他可能不一定說特別針對原住民族的這個族人的勞工那他當然就是相關的勞工都希望能夠有幫忙
transcript.whisperx[591].start 16084.695
transcript.whisperx[591].end 16108.169
transcript.whisperx[591].text 對 當然就是說我們就智慧工地科技減債這個部分是很值得肯定不過我希望有一些減債的指標你不論是從定性或是定量這個方面來做一些指標比如說如果是從定量的話我們來看你重大職災死亡人數的減少率你應該說2030年或者是說幾年之內我們可以把這個死亡率從原本是博人的6倍能不能
transcript.whisperx[592].start 16109.309
transcript.whisperx[592].end 16133.157
transcript.whisperx[592].text 減為國人的一倍兩倍這樣至少要讓原住民的勞工說政府有在做這方面的努力根本說明比方說舉例來說我們的數字看到112年這個重大植栽死亡的統計在營建工程的部分原住民是死亡是13位那今年一直到今年的現在10月底目前的數字是7位其實可以看得到一些改善的
transcript.whisperx[593].start 16133.757
transcript.whisperx[593].end 16153.171
transcript.whisperx[593].text 改善的幅度因為我看到的是整體性的比如說你們的報告裡面在111年的策略裡面看到說希望兩年內能夠減少10%那我希望這個原住民因為是高高於國人六倍的話是不是在標準會可以定得更高讓我們的安全性可以顧及我們所有的原住民勞工可以嗎
transcript.whisperx[594].start 16154.051
transcript.whisperx[594].end 16180.899
transcript.whisperx[594].text 我跟文說明我們其實這次修職案法也包括接下來會希望能夠提出一個在職災上面的減災的計畫其實就是希望全面性的把這個職災的風險給降低我希望有定性的也有定量的所以這個部分希望你們再多做努力然後第二個主題就是說我在去年有發現一個個案就是在他的賠償不公與單身者的一個保障的問題就是去年的10月17號的質詢
transcript.whisperx[595].start 16182.279
transcript.whisperx[595].end 16204.624
transcript.whisperx[595].text 我看到有一個就是族人來陳情就說因為他沒有仔細清楚結果他勞保的死亡給付就是導致有天然之別可以有180萬然後如果有家屬或者是有婚姻的話是900萬在那個差別我是覺得說面對這些高風險單身非典型勞工這些保障能不能做一些這方面的改進
transcript.whisperx[596].start 16206.621
transcript.whisperx[596].end 16229.079
transcript.whisperx[596].text 其實如果委員有相關的建議的話我們很願意來參考因為這個高風險的勞工當然是我們最希望能夠保護的一群就是常常是會發生在沒有結婚的或者是父母親已經不在結果沒有所謂的那個可以繼承的這些保險金的結果他的那個金額就非常低這是去年實際發生的案例在台中
transcript.whisperx[597].start 16230.212
transcript.whisperx[597].end 16257.007
transcript.whisperx[597].text 跟委員報告 我也是在提到說勞工他死亡 他因為是單身有兄弟姊妹來領遺屬年金或者是津貼的時候可能不符合資格這個主要是因為我們大法官會議解釋549號的解釋認為說遺屬津貼是所得的替代所以他要避免遺屬生活無辜必須受被保險生前撫養
transcript.whisperx[598].start 16258.628
transcript.whisperx[598].end 16279.517
transcript.whisperx[598].text 為條件他不是遺產所以我們有一定的條件就是說這個兄弟姐妹必須在生前受到被保險是撫養的人他才可以是受益人來請那最後一個問題就是說我們的執訓的資源錯位就是說我們可以發現我們的現在原住民的那個執訓類別大概就是餐飲業民宿職業駕駛美容美髮這些那我們一直
transcript.whisperx[599].start 16282.978
transcript.whisperx[599].end 16302.939
transcript.whisperx[599].text 知道說我們目前的原住民勞工跟一般國人勞工平均的薪資差距在一萬元以上那我覺得說是不是我們可以給策略性的引導族人去受高薪之類的一個資訊比如說目前在推的利率人才風電維護 太陽能安裝這方面的專班計畫可以讓我們原住民勞工也可以進入這個職場
transcript.whisperx[600].start 16307.469
transcript.whisperx[600].end 16327.287
transcript.whisperx[600].text 其實基本上這些職類基本上大家都沒有去做身份的設限當然我們也特別希望原住民的勞工如果要更大的投入我們也是很歡迎的你應該可以明訂一個名額比如說常常在我們的資訊裡面因為沒有這方面的一個名額所以就不會有
transcript.whisperx[601].start 16328.227
transcript.whisperx[601].end 16341.14
transcript.whisperx[601].text 有人去受訓因為看到的類別裡面就是駕訓班美容美髮課 蒼蠅這方面的訓練就沒有這方面綠領人才其實我想我們很歡迎原住民的朋友一起來報名這些相關的課程包括綠領 風電
transcript.whisperx[602].start 16343.826
transcript.whisperx[602].end 16368.436
transcript.whisperx[602].text 然後綠能相關的部分的確是薪資是比較高的我們在111年看到我們光復沙老部落它原名會運用了綜合發展基金貸款然後結合地方創生讓培訓落地然後轉換成為我們訓練走向就業的一個成功模式那我要講的就是說我們能不能就是勞動部這邊也可以結合我們
transcript.whisperx[603].start 16369.036
transcript.whisperx[603].end 16384.784
transcript.whisperx[603].text 原民會然後就在地就業成功模式來推廣比如說他們成功的經驗我們就用這樣的方式來各個社區或者是部落來推廣讓實際我們的年輕人留在部落然後就業能夠真正落實在各個層面這樣
transcript.whisperx[604].start 16386.792
transcript.whisperx[604].end 16404.413
transcript.whisperx[604].text 我們來看用什麼方式我想我們可能這部分會需要跟園民會一起來討論對 所以我希望能夠跨部會的對 這可能要跟園民會來討論因為園民會會更比我們更清楚知道原住民的需求這樣子好 那看哪些部分能夠跨部會一起來合作的我們當然願意盡量來去做參考
transcript.whisperx[605].start 16404.693
transcript.whisperx[605].end 16426.447
transcript.whisperx[605].text 好 那希望部長就我們原住民的死亡率能夠再多費心所謂的6倍 還有現在勞工風險 勞安風險是16倍這個差距希望在明年或者是近幾年能夠獲得實質的改善謝謝好 謝謝接下來請羅廷偉委員來做詢問
transcript.whisperx[606].start 16434.424
transcript.whisperx[606].end 16453.872
transcript.whisperx[606].text 謝謝主席 有請部長來 請部長部長要喝水嗎不用喔可以先用餐 沒關係陸委員好好 部長好部長 長榮航空空服員過世至今一個月了有關勞工請假這個不利的對待目前有沒有什麼進度
transcript.whisperx[607].start 16455.291
transcript.whisperx[607].end 16481.396
transcript.whisperx[607].text 我們在禮拜一的時候也才找了包括勞資團體各方那也包括學者那來針對這部分有一個座談會來諮詢大家的意見好有進度都是最好的那我想不只航空業醫療產業也有相關的聲音我要求在這一次呢我們希望部長對於航空醫療相關工會的聲音啊要認真處理包括昨天你說的這個相關的一些溝通協調
transcript.whisperx[608].start 16482.576
transcript.whisperx[608].end 16503.87
transcript.whisperx[608].text 禮拜一的時候包括航空業的工會包括醫療業的工會都有一起謝謝你謝謝我想也要再跟部長再次強調就是改革啊要避免流於形式避免讓這個勞工呢再次的有這樣子的一個相關的變相懲罰這部分我們會持續的追蹤第二個部長上個月月底啊
transcript.whisperx[609].start 16504.79
transcript.whisperx[609].end 16522.65
transcript.whisperx[609].text 行政院通過了跨國勞動力的精進方案正式宣告服務業移工要開放那目前規劃是旅宿服務還有這個商港碼頭貨物卸裝集散的工作想請問一下為什麼初期只有這兩類為什麼其他類沒有
transcript.whisperx[610].start 16524.686
transcript.whisperx[610].end 16542.837
transcript.whisperx[610].text 第一個因為當然各個行業別我們都在都需要評估也需要目的事業主管機關來提出那在上崗碼頭的確是我們看到上崗碼頭他其實他的缺工的問題很嚴重那尤其是
transcript.whisperx[611].start 16544.017
transcript.whisperx[611].end 16568.456
transcript.whisperx[611].text 他的這個行業別裡面現在真的那個年紀都很大那他們甚至都跟我說他們其實已經要退休的勞工還要去想辦法去拜託他不要退休那真的年輕人比較不願意有這樣子的困境我都知道但是我現在要講的就是說三港碼頭那個部分那個沒有話說啦但是很多類型的也都一直在努力希望他們能夠爭取這個部分的開放當然
transcript.whisperx[612].start 16569.316
transcript.whisperx[612].end 16589.468
transcript.whisperx[612].text 能不能全面開放當然不行我們一定要最審慎的評估我想這是勞動部的一個工作但是目前我想很多人也都會想說為什麼其他類不行所以我想加速的這個評估在沒有影響到國人的工作權的情況之下能夠有更多的好消息但今天我想跟你探討的是呂素月為主呂素月到底是缺工
transcript.whisperx[613].start 16590.712
transcript.whisperx[613].end 16610.172
transcript.whisperx[613].text 還是缺便宜的勞工我想跟你分享一下我從111上面找到的幾個案件第一個我們看到部長麻煩你看一下曾飯店的工作公務人員喔他這個是公務修水電消防空調電信最好具備水電相關的證照那薪資是32000到36000
transcript.whisperx[614].start 16612.421
transcript.whisperx[614].end 16633.321
transcript.whisperx[614].text 那真空調水電的工程維護技術員他不是房屋喔剛剛講的是公務不是房屋喔那現在的工程的技術人員啊飯店的建築物空調水電啊然後機電設施的維修啊各項設備的維護保養修繕水電拉線配管配電等施工工作定體檢查有沒有異常狀況33000到38000
transcript.whisperx[615].start 16636.852
transcript.whisperx[615].end 16659.415
transcript.whisperx[615].text 還有安全部的工作人員顧公司的財產安全啊顧員工旅客安全啊要會消防設備跟監視器的一個狀況通報排除啊三萬二到三萬四所以我要跟部長分享部長你覺得有水電證照的飯店公務人員起碼要多少起薪你覺得才符合他這樣子的一個證照跟他相關的一個專業你覺得呢
transcript.whisperx[616].start 16660.682
transcript.whisperx[616].end 16680.023
transcript.whisperx[616].text 我很難在這邊就講一個數字很難再講但是你看到剛剛那個數字你有沒有覺得好像偏低第一個當然我們會非常非常留意產業裡面行業裡面這個低薪的狀況所以這也是為什麼我們在這次的制度的設計裡面我們設計應該要先加薪必須加薪作為前
transcript.whisperx[617].start 16681.625
transcript.whisperx[617].end 16709.106
transcript.whisperx[617].text 但是我要講就是說我知道你們的設計的初衷是利益良善但是我要講就是說你看他們現在加薪了2000剛剛說的33000有的是35000加薪2000我覺得在這個部分上實務上還是有一點差距所以我想勞動部做了哪些努力現在有沒有幫忙做一些媒合的狀況我想希望說在這個部分上工作的媒合就現在來看我們先不講移工開放
transcript.whisperx[618].start 16709.847
transcript.whisperx[618].end 16733.777
transcript.whisperx[618].text 工作的媒合勞動部有沒有做當然有然後而且我們對呂樹業工作的媒合也是我們希望盡量來協助的但是我必須坦白講媒合應該是做的有做但沒有做到確實做到非常的落實甚至做得很好如果媒合不好的話是因為薪水差所以找不到人那開放移工以後呢飯店的薪資會不會就卡死在這個低價位
transcript.whisperx[619].start 16734.597
transcript.whisperx[619].end 16757.011
transcript.whisperx[619].text 那麼正在找飯店從事類的工作的國人比如說公務 剛剛說的房務可能薪水會比剛剛舉例的兩間飯店高一點會不會移工一開放他們就沒工作了跟委員說明目前我們的確看到第一個飯店業確實相對在職缺調查裡面他們一個職缺能夠找到人的時間真的是比其他來的長而且長很多
transcript.whisperx[620].start 16758.192
transcript.whisperx[620].end 16781.987
transcript.whisperx[620].text 所以的確他們缺工的狀況是比較嚴重的第二個是我們其實這次的設計裡面我們也有包括設計進去我們是用技術人力的方式來開放也就是用技術人力的方式來開放的時候他其實會要有他的薪資門檻的底線技術人力就是剛剛說的公務也是技術人力之一但是我說技術人力的部分是因為他不能夠用最低薪資來拼顧
transcript.whisperx[621].start 16784.008
transcript.whisperx[621].end 16805.411
transcript.whisperx[621].text 所以這是為什麼我們要設用技術能力的角度來開放就是希望我們有一個薪資門檻的工具可以來做這個相關薪資上面的調教我要這樣講這個案例我希望只是個案不是通案那當然我們也不要拿這個單一事件來做整體的一個評估但我要講的是今天我們要如何保障國人的工作權
transcript.whisperx[622].start 16806.292
transcript.whisperx[622].end 16820.604
transcript.whisperx[622].text 不只如此我們還有很多是以建教合作在飯店所謂假實習真打工轉個彎就進來了相關的勞動檢查有沒有進行違規的比例這部分可以跟我分享一下嗎
transcript.whisperx[623].start 16821.26
transcript.whisperx[623].end 16844.441
transcript.whisperx[623].text 跟委員說明的確現在會有一些實習生尤其是外國的實習生目前是目的世界主管機關相關的要點所以我們其實現在也在跟交通部跟經濟部在討論針對這些這個外國學籍的實習生如果他的這個假設他的實際實際上他就是在進行工作的話怎麼把他的勞動條件應該盡量的保障給拉起來
transcript.whisperx[624].start 16844.921
transcript.whisperx[624].end 16855.311
transcript.whisperx[624].text 目前我們也跟這些目的世界主管就要討論這個我想最後那個勞動檢查假實習真打工這部分這個檢查的一個進行狀態還有他的比例為何相關數據可不可以提供給我
transcript.whisperx[625].start 16857.933
transcript.whisperx[625].end 16877.303
transcript.whisperx[625].text 其實他就我們的勞動檢查來說因為實習這件事情的主管坦白說是在教育部沒有錯但是你們勞動檢查的時候會抓到嗎但是如果是工作型實習的話當然我們認為我們就要比較一起來協助目的是主管機關來檢視他的工作的條件如果是工作型實習所以你們有勞動檢查嗎
transcript.whisperx[626].start 16878.303
transcript.whisperx[626].end 16904.353
transcript.whisperx[626].text 那有勞動勞檢的時候一定有數據嘛數據可不可以回扣提供給我我們有跟教育部的聯合檢查好再麻煩數據給我謝謝那部長我也要這個在這邊再一次的跟你關心喔早產兒的一個照顧啊照顧的問題呢我過去就很關心這個輕職假然後在今年6月18的時候我有跟部長說早產兒的醫療照顧假部長五個月過去了你答應我會有收集早產兒罕病家庭的一個實際照顧需求請問嗎現在呢
transcript.whisperx[627].start 16907.352
transcript.whisperx[627].end 16934.441
transcript.whisperx[627].text 早產兒的需求其實我們現在其實我們也做了這個育嬰留庭的彈性的措施現在可以以日來請休所以如果三歲以下的小孩的話這個我都知道他其實現在以日請休每個勞工可以有30天雙親加起來可以有60天但我要講的是說部長我有提出性別平等法工作的這個20條修正草案明定受僱者子女未滿6歲有早療或罕病的健康需求
transcript.whisperx[628].start 16935.501
transcript.whisperx[628].end 16955.275
transcript.whisperx[628].text 能夠申請醫療照顧假全年以18日為限喔這不記錄家庭照顧假的天數喔部長當時你也有說回去會想一想喔那目前你有沒有什麼想法還是你就是覺得就以剛剛所說的留職停薪啊家庭照顧假來跟我說現在留職停薪如果可以以日來請求的話他其實已經相對但我要講的是說而且他還是有薪水的
transcript.whisperx[629].start 16955.655
transcript.whisperx[629].end 16984.33
transcript.whisperx[629].text 我知道那第二個是說當然我們現在也是希望這個相關的制度上路可以有一個跟企業的調適期那未來是不是要擴大放寬我覺得當然這個我們也不我們可以開放的討論我想我們不是漫無目的的無止境的一直放寬一直放寬但是大家要知道部長我們生孩子真的是有這一個家庭照顧的需求可是現在問題是他是寒病兒他是早療需求他真的比較有困境
transcript.whisperx[630].start 16984.83
transcript.whisperx[630].end 17001.612
transcript.whisperx[630].text 更為困境所以雖然育嬰留職停薪現在的改進喔以及家庭照顧假新資2025年1月1號開始上市放寬了一個申請的方式每日就是你說的好但是呢但是這些措施對於早產家庭我相信絕對不足一定不足
transcript.whisperx[631].start 17002.212
transcript.whisperx[631].end 17029.285
transcript.whisperx[631].text 百分之百不足充其量整個勞動部的強調請假方式更具彈性但是以協助照顧臨時或短期需求我覺得部長對於早療或罕病的一個家庭獨立來設置所謂的醫療照顧假拜託你可不可以再給我更具體的一個研議我想這個研議可能我們要找衛福部來討論因為這涉及到可能特殊需求的小孩那他的實際的狀況
transcript.whisperx[632].start 17030.706
transcript.whisperx[632].end 17054.942
transcript.whisperx[632].text 那衛福部這邊可能我們也聽一聽衛福部他們這部分的看法我最後30秒這些早產兒的家庭真的是不夠因為什麼他們的次數早療的時段是有限定的甚至有限定路程有的是跨縣市才能夠到那邊去做進行早療並不是早療的這個點很多但是衛福部的問題可是我要講是現況是這樣我們要怎麼去支持他們這部分拜託一下
transcript.whisperx[633].start 17058.957
transcript.whisperx[633].end 17087.117
transcript.whisperx[633].text 好 謝謝接下來請林德烏委員林德烏委員 林德烏委員不在請鄭天才委員主席 各位委員 有請部長來 請部長部長好 辛苦了
transcript.whisperx[634].start 17089.719
transcript.whisperx[634].end 17116.145
transcript.whisperx[634].text 這個原住民的就業這個我們一直希望能夠有更好但是以目前的狀況並沒有更好雖然我們的前任的總統蔡總統他的原住民族就業政策要保障上望新的工作機會但是很遺憾的我們的
transcript.whisperx[635].start 17117.441
transcript.whisperx[635].end 17140.827
transcript.whisperx[635].text 原住民保障的就業的條文本來在一開始的時候就業服務法46條所授權訂定的外國人從事就業服務法第46條第一項第8款至第11款工作資格及審查標準這是民國93年1月13號訂定發布的這裡面特別
transcript.whisperx[636].start 17145.396
transcript.whisperx[636].end 17167.735
transcript.whisperx[636].text 規定每禁用言住民一人 得申請引進外國人兩人這樣的一個條文在109年7月31號被刪除了所以這個保障條款就變沒有了
transcript.whisperx[637].start 17168.905
transcript.whisperx[637].end 17193.303
transcript.whisperx[637].text 然後在111年4月29號就全文修正整個65條全文修正當然也沒有回復到我們的剛才講的被刪除的這個條文在這樣一個情況之下你看為了外勞現在為了外籍外勞不斷的修正這個
transcript.whisperx[638].start 17196.331
transcript.whisperx[638].end 17219.244
transcript.whisperx[638].text 這個審查標準工作資格及審查標準已經修了23次我們不反對我們確實也需要但是原住民為什麼要被犧牲所以這個部分尤其是我們原住民族的就業狀況
transcript.whisperx[639].start 17220.836
transcript.whisperx[639].end 17247.487
transcript.whisperx[639].text 我們主要是最高的最多的人數最多的比例最高的營建工程業百分之十八點五九這個比比例很高當然你勞動部一定很清楚現在進來的這些外勞營建工程非常最多然後我們
transcript.whisperx[640].start 17248.871
transcript.whisperx[640].end 17274.154
transcript.whisperx[640].text 我們就業的比例從事的行業製造業14.03%這是第二高而製造業進來的也越來越多所以這個23次的資格及審查標準的修正影響的都是原住民的勞工而且是我們就業的比例
transcript.whisperx[641].start 17275.543
transcript.whisperx[641].end 17303.823
transcript.whisperx[641].text 低高跟第二高的都受到很嚴重的影響接下來就是住宿及餐飲業這是我們的第三這是我們就業的第三現在也在受影響剛才羅廷偉委員講的這個跟教學教學跟這個就業合作的那個部分也影響到我們
transcript.whisperx[642].start 17305.134
transcript.whisperx[642].end 17326.197
transcript.whisperx[642].text 所以這個部分要請部長要能夠重視怎麼樣去解決把我們的條款能不能再列回來跟委員說其實現在在救福法裡面第24條其實是有把原住民納入成我們的特定對象裡面的部長
transcript.whisperx[643].start 17327.566
transcript.whisperx[643].end 17351.489
transcript.whisperx[643].text 就业服务法24条现在已经形同稀释因为根据24条根据24条才会有46条授权定定的一个保障条款现在没有了这个保障条款了 没了所以在这样一个情形之下我刚刚说了
transcript.whisperx[644].start 17352.926
transcript.whisperx[644].end 17361.982
transcript.whisperx[644].text 現在外勞進來的營建工程業最多正好是我們就業比例最高的第二 製造業
transcript.whisperx[645].start 17363.769
transcript.whisperx[645].end 17381.421
transcript.whisperx[645].text 外勞進來的很多我們都不反對外勞進來但是怎麼樣不要影響到我們的就業我們現在在原民會提供的這個失業率的數字上面其實的確沒有看到原住民族的失業率特別高他大概是3%左右
transcript.whisperx[646].start 17384.748
transcript.whisperx[646].end 17412.059
transcript.whisperx[646].text 還是比一般的其實跟一般跟全體還是差不多的還是比一般的高大概就是在3%左右其實跟其他是差不多的這個部長不能因為這個數字不能因為這個數字就認為說沒有影響到事實上是有影響到在審查已經通過了立法院已經通過了在外國人外國人專業的那個那個辦法
transcript.whisperx[647].start 17413.14
transcript.whisperx[647].end 17436.035
transcript.whisperx[647].text 外國專業人才禁用的那個辦法又擴大連副協士連副協士都算是一個專業人才外國專業人才副協士以前這個外國專業人才這個辦法副協士沒有列進去這是特別列進去我問教育部 問國發會他說因為勞動部支持
transcript.whisperx[648].start 17442.358
transcript.whisperx[648].end 17470.018
transcript.whisperx[648].text 所以这个部分都是影响到这个部分当然我们台湾的就业的问题很多眼没有错但是不要牺牲原住民原来的我们不会去牺牲原住民就老公在老公就是有啊我才会如果没有的话就是我们的老公跟我反映了
transcript.whisperx[649].start 17471.294
transcript.whisperx[649].end 17485.443
transcript.whisperx[649].text 老公 原住民的老公跟我反映了我才會去仔細的去看這些條文呢我才知道啊所以這個部分的部長如果你一開始現在我經過這樣的質詢之後這麼詳細的說明之後你都還認為沒有的話
transcript.whisperx[650].start 17492.067
transcript.whisperx[650].end 17517.023
transcript.whisperx[650].text 這樣是不好的跟委員說我不是認為沒有你可以說你回去再去我們可以跟原民會再來了解他這個數字統計數字背後是不是有什麼地方應該要多做考慮然後在這個考慮下我們既有的機制跟既有的這個法條包括特定對象的部分我們怎麼來去協助我們很願意來去檢視這些事情對但我們會要去跟原民會一起來討論
transcript.whisperx[651].start 17518.424
transcript.whisperx[651].end 17543.184
transcript.whisperx[651].text 那個部長現在不是嚴明會議是你們主動把這個我問過嚴明會當初你們是不是有同意把這個這個授權就業服務法46條所授權訂定的這個資格及審查標準他們說當初他們也反對啊但是就當然不是你部長認定了就這樣啊所以這個部分
transcript.whisperx[652].start 17545.748
transcript.whisperx[652].end 17567.708
transcript.whisperx[652].text 我都不反對外勞進來我們是確實是需要但是不要把原住民的保障條款給刪除回去好好的去評估我們再思考一下能夠再把它回復我只有沒有別的要求只是要求把它回復而已好不好謝謝
transcript.whisperx[653].start 17572.24
transcript.whisperx[653].end 17579.024
transcript.whisperx[653].text 好謝謝接下來請林思敏委員林思敏委員林思敏委員不在請吳麗華委員謝謝主席有請洪部長來請部長
transcript.whisperx[654].start 17603.263
transcript.whisperx[654].end 17617.65
transcript.whisperx[654].text 部長好我們原住民立委都很關心我們原住民族勞工的職災狀況那特別是最嚴重的就是根據這個統計看起來呢是營造業再來就是製造業
transcript.whisperx[655].start 17618.87
transcript.whisperx[655].end 17645.47
transcript.whisperx[655].text 那麼這幾個行業那它的一個實在在這麼多年的關注之下我們往往也發現其實它的件數不減反增啦所以我們也很想去了解說到底是要怎麼樣去做才有辦法有效的來改善這種情形那曾經監察院審計部有提過就是特別糾正勞動部他們的看法是說
transcript.whisperx[656].start 17646.391
transcript.whisperx[656].end 17671.044
transcript.whisperx[656].text 我國的勞檢人力不足會導致勞工檢查過低那不足以有效的嚇阻雇主違法行為及提供安全的工作環境所以我想特別先請教一下部長針對這個前兩名就是營造業製造業我們原住民比較容易發生的一個職災類別那目前的勞檢覆蓋率大概是怎麼樣
transcript.whisperx[657].start 17671.792
transcript.whisperx[657].end 17699.518
transcript.whisperx[657].text 跟委員說明其實勞檢的人力確實一直以來都相對比較辛苦的所以我們一直在跟行政院跟人總在爭取是不是能夠有更多的這個人力的名額但的確這裡面會涉及到這個整個員額編制上面的狀況所以在爭取上所以我們盡量希望能夠再多提高一些勞檢員他的勞動的條件或相關的這個家籍的部分來去協助
transcript.whisperx[658].start 17700.178
transcript.whisperx[658].end 17725.982
transcript.whisperx[658].text 那目前的這個覆蓋率我請署長這邊來說署長請跟委員報告確實現在我們原住民的勞工朋友主要是在這個高風險的營造業跟製造業那也跟委員報告光營造業我們一年的勞檢的常識就相當於到11萬常識所以這個兩個行業一直是我們一個檢查重點
transcript.whisperx[659].start 17727.263
transcript.whisperx[659].end 17754.884
transcript.whisperx[659].text 所以意思就是說在人力這些年持續不足的狀況下但是老減覆蓋率還是有在注意有在提升嗎那為什麼我這樣子問因為我們發現好像我們怎麼做都會就是道高一尺 謀高一丈我們往往發現這種層層轉包的這種方式其實我們在接受一些陳情案的時候也很困擾我們
transcript.whisperx[660].start 17756.466
transcript.whisperx[660].end 17772.843
transcript.whisperx[660].text 因為有很多隱匿的狀況那舉個例子來講我們很多發生的狀況就是他如果受傷了在工地受傷了會發現說不准叫救護車因為他們都會知道說這樣子報公安報勞檢
transcript.whisperx[661].start 17774.545
transcript.whisperx[661].end 17791.808
transcript.whisperx[661].text 可能就會被要求停工或怎麼樣所以他們就會有很多的方式去規避去隱匿那你覺得我們營建業 製造業有多少是因為這樣的原因被隱匿起來跟這個委員報告
transcript.whisperx[662].start 17793.447
transcript.whisperx[662].end 17812.958
transcript.whisperx[662].text 基本上我們其實現在也在新的這個責任法的修正條文裡面其實規定如果你有你就是該通報不通報的狀況的話其實最高可以罰到450萬我就是知道說你們有在進行修法好那可不可以說明一下修法的方向目前就是把罰則部分會我們會把它給提高
transcript.whisperx[663].start 17814.295
transcript.whisperx[663].end 17839.995
transcript.whisperx[663].text 然後包括營造業剛剛在委員在講的尤其是營造業的狀況的確我看到的情況是因為他的這個層層的分包讓他的責任很難追究所以這一次我們其實也在治安法的修法裡面明定了業主的責任也包括是在這層層轉包過程裡面要有一個包商責任的統合機制就是希望要避免說發生了職災其實照理來說
transcript.whisperx[664].start 17841.636
transcript.whisperx[664].end 17855.87
transcript.whisperx[664].text 更該負責的是一開始的業主或上面的大包可是最後卻都轉嫁變成是最下的小包然後做那個最基層的包商在承擔這個責任那這個其實不符合我們在整個工地裡面運作的狀況的認知
transcript.whisperx[665].start 17857.362
transcript.whisperx[665].end 17878.059
transcript.whisperx[665].text 部長我是很高興因為我們也關切很久也知道你們在進行修法那我剛剛聽起來一方面是罰金加重二方面是對於這種層層轉包責任全部都要分攤但是要整合或者是要整體的看待但是我現在的意思是說像這個狀況
transcript.whisperx[666].start 17879.6
transcript.whisperx[666].end 17896.779
transcript.whisperx[666].text 我覺得也必須要去被了解被處理因為他就是怕被停工他就是怕被罰錢嘛所以他一定會有很多隱匿的狀況所以我的意思是說這個部分在修法的時候有沒有去考慮到
transcript.whisperx[667].start 17897.881
transcript.whisperx[667].end 17911.76
transcript.whisperx[667].text 跟委員說明的確因為現在這個狀況其實不只發生在原住民的勞工其實整體在我們很多營造業都有我們執安法要修就是要這是一個破口漏洞那現在當然相關的通報或者是申訴其實
transcript.whisperx[668].start 17912.921
transcript.whisperx[668].end 17942.441
transcript.whisperx[668].text 包括家属也都可以所以我们能够做的当然是要把假设有这样的状况他被抓到的嚇阻要提高这是把罚金给提高的状况但是他就更怕被讲他可能就会有其他后面的动作所以我觉得我们可以来思考怎么样让这个通报或者是来申诉的门槛可以再降低那最后就是我再请教我其实是这样子想有没有可能成立一个原住民的公安推动小组
transcript.whisperx[669].start 17943.541
transcript.whisperx[669].end 17971.34
transcript.whisperx[669].text 部長您的看法如何我覺得如果原民會有這樣子的想法的話我們當然可以跟原民會來討論好那我希望進行討論但是這部分就原住民的情境原住民的特性當然原民會會比我們更加的清楚只是他在職場上面的狀況當然這部分我們能夠協助的我們願意來協助但是至少要有這個平台來開這個會如果原民會來跟我們討論的話我覺得我們可以來思考跟研議我也很感謝我有私下跟您提過就是救福法第12條
transcript.whisperx[670].start 17972.561
transcript.whisperx[670].end 17998.251
transcript.whisperx[670].text 有說縣市人口達兩萬人以上可以來設立這個公立的原住民就業服務機構這是我五六年前一直不斷訴求那很謝謝後來勞動部呢就是由中央來協助買單所以呢目前有六個縣市有申請那你們提供設施設備房屋租金租車人事費及業務費好但是我盤了一下目前
transcript.whisperx[671].start 17999.011
transcript.whisperx[671].end 18023.604
transcript.whisperx[671].text 我們勞動部協助的這些原住民的救福據點人力有28人那園民會呢他也用他的原住民的這些轉過來的貸金的這個就業基金他也做了各地方的一個救福辦公室目前人力有79名那我們原本是這樣想就是把整合或讓他1加1大於2但是我們發現說現在有個問題就是
transcript.whisperx[672].start 18027.466
transcript.whisperx[672].end 18049.122
transcript.whisperx[672].text 有的縣市它會放在原民局處有的縣市它會放在勞工勞動的局處這個勞政單位的我們就發現很好為什麼因為他們可以撈到這些正式的資料放在原民會的他們是撈不到這些資料
transcript.whisperx[673].start 18050.202
transcript.whisperx[673].end 18066.666
transcript.whisperx[673].text 那另外就是說放在園民會的呢就很困擾了因為他們會變成是園民會的救人帶這些新人所以他們在磨合的部分也要花很多的時間那我不曉得說勞動部這邊有沒有一個想法我們怎麼樣讓這個原本我們希望整合或1加1大於2的這樣的一個救福人力
transcript.whisperx[674].start 18078.328
transcript.whisperx[674].end 18084.387
transcript.whisperx[674].text 能夠讓它發揮功效所以我是想說部長有沒有可能就是勞動部邀請原民會
transcript.whisperx[675].start 18085.68
transcript.whisperx[675].end 18114.91
transcript.whisperx[675].text 能夠一同的來就這件事情好好的坐下來跟我說我是覺得我想我們跟地方政府在這部分合作我們不會我們主觀上不會想要去區分他是在哪個局處所以今天如果我們在資料上面資訊上面合作上面要借接的話我會請我們的同仁來擴大把各部會如果是放在原民局處的情況也納入然後也納入我們聯繫的對象好不好就不是因為的確勞動部過去在地方政府我這樣說好了
transcript.whisperx[676].start 18115.49
transcript.whisperx[676].end 18143.816
transcript.whisperx[676].text 就是因為放的地方不一樣我們就會接到陳情所以我覺得是不是至少勞動部 園民會就是一同的來就這件事情聽聽這兩邊救撫員的聲音可以 我是這樣想我們勞動部當然可以找園民會甚至委員如果這邊要召開一些協調的話我覺得也是很好那跨部會來針對它放在地方政府不同的局處我想我們都應該擴大的把它給納入
transcript.whisperx[677].start 18144.696
transcript.whisperx[677].end 18157.648
transcript.whisperx[677].text 在我們整個資源整合的過程裡面這樣子我們希望把這件事情把它成就起來啦好 不要為德不足啦 很可惜好 謝謝部長 謝謝主席好 謝謝吳委員 謝謝部長好 接下來請顏寬恆委員顏寬恆委員 顏寬恆委員不在請陳毅委員
transcript.whisperx[678].start 18174.807
transcript.whisperx[678].end 18195.393
transcript.whisperx[678].text 好 麻煩請洪聖翰部長來 請部長部長都還沒有吃 你們都吃飽了很好 沒事 市長好好 村委員好部長好我想先請教你那個就是說我們一般整體的這個失業率跟原住民的失業率各是多少
transcript.whisperx[679].start 18196.653
transcript.whisperx[679].end 18221.36
transcript.whisperx[679].text 目前應該都是3%出頭然後原民我剛看到是3.08我們在3出頭3.0幾是都一樣嗎兩個數字都一樣嗎很接近就原民會給我們原住民的原住民族的失業的數字所以這個部分是原民會做的不是你們去統計的是好那所以是你們委託原民會做
transcript.whisperx[680].start 18222.059
transcript.whisperx[680].end 18233.427
transcript.whisperx[680].text 不是他們自己做的他們自己做所以你們做的失業率就不會再分不會再特別分族群去做研究是嗎他們數據3.43抱歉好那整體的呢
transcript.whisperx[681].start 18242.347
transcript.whisperx[681].end 18267.392
transcript.whisperx[681].text 3.38我想是這樣因為今天前面有好幾位原住民的立委來為還關心原住民的這個就業的問題雖然這個沒有在我的質詢稿裡面但是就是說剛剛他們所提到的其實我很早以前我都有問過了但是我想我剛在這邊聽我想點出一些問題就是說
transcript.whisperx[682].start 18270.914
transcript.whisperx[682].end 18283.028
transcript.whisperx[682].text 我們其實常常在在部落也好或者是在很多地方我們在跑原住民的這個行程的時候也很巧你說3.48的失業率是嗎
transcript.whisperx[683].start 18287.511
transcript.whisperx[683].end 18310.876
transcript.whisperx[683].text 3.43的失业率那我们怎么走动好神奇哦就这3.43%的人我们走没几步就会遇到所以为什么刚刚有委员说你们不能光看你这个数字是不准那是因为我们出去走确实有遇到这样的现象所以我就要请教你了就是说
transcript.whisperx[684].start 18312.182
transcript.whisperx[684].end 18330.08
transcript.whisperx[684].text 你們原住民失業率的這個到底就是說這個採樣是怎麼樣那你們說是原民會做的那我現在因為我不太清楚說做這個是原民會的工作還是你們的工作還是你們有講好說就是讓他們做還是你們覺得他們做了你們就不用做了
transcript.whisperx[685].start 18330.99
transcript.whisperx[685].end 18345.26
transcript.whisperx[685].text 因為畢竟我認為勞動部在做這些研究或許是比較專業的我想委員針對你剛才講的這個現象我覺得我們可以來跟原民會來討論就是說到底了解一下他的調查方法如何對你們要
transcript.whisperx[686].start 18346.422
transcript.whisperx[686].end 18361.122
transcript.whisperx[686].text 了解一下它的那個樣本對 更好的調查方法那大家在不同的調查方法上面就是說不同的調查單位其實能夠去做對接在方法上面比較奇異比較能也能夠去做可行性的比較那我是不是也建議你們也做一下
transcript.whisperx[687].start 18362.123
transcript.whisperx[687].end 18386.742
transcript.whisperx[687].text 因为其实在做这个失业率的统计当然有很多的技巧我相信劳动部的各位应该都比我还熟起码看你们是直化还是量化或者两个并行怎么样做比较准这个还牵扯到这个区域的问题因为我们原乡跟都会区的原住民的工作形态差距是非常大的
transcript.whisperx[688].start 18387.723
transcript.whisperx[688].end 18402.615
transcript.whisperx[688].text 所以這個部分因為我這樣聽起來我認為部長對於原住民的這個整個生活型態並不是很了解我們也可以體諒但是不能一直包容下去因為您坐這個位置原住民的勞工
transcript.whisperx[689].start 18403.195
transcript.whisperx[689].end 18429.053
transcript.whisperx[689].text 好跟跟這個其他勞工朋友本國的勞工朋友外籍的勞工朋友都一樣都是勞工也都是勞動部需要關心的對象那所以這個部分我本期建議就是說勞動部你們可以也邀集好先討論一下就是說看要你們自己研究所要做還是你們委外給哪個單位做但是要做之前
transcript.whisperx[690].start 18430.214
transcript.whisperx[690].end 18436.041
transcript.whisperx[690].text 我覺得你們要去找就是說對於原住民整個生活型態很了解的因為畢竟過去
transcript.whisperx[691].start 18437.973
transcript.whisperx[691].end 18463.105
transcript.whisperx[691].text 我曾經聽到在這個公部門有人很得意的講這個不小心讓我聽到就是說因為我們要降低這個數據我們就其實就有很多這個臨時的工作跑出來當這個臨時的工作跑出來的時候你當然在做說他這個失業率在做的時候當然跟當然
transcript.whisperx[692].start 18464.306
transcript.whisperx[692].end 18483.813
transcript.whisperx[692].text 到底說他是誤差還是他是技巧性的美化這個我們就不知道了啊好部長你覺得這個部份我們統一處這邊來說明一下報告委員是這樣子就是我們國家的那個政府統計他是你可以大聲一點我們國家的
transcript.whisperx[693].start 18485.427
transcript.whisperx[693].end 18502.245
transcript.whisperx[693].text 我們國家的政府統計它是依據主席總署的各部會統計範圍劃分方案來分工的這個原因是因為你分什麼工分工 譬如說哪個統計是哪個部會負責
transcript.whisperx[694].start 18505.769
transcript.whisperx[694].end 18520.295
transcript.whisperx[694].text 那因為各部會的這個職權多少有點重複的地方譬如說好沒關係我了解你要講什麼我想如果是如果是已經有這個分工所以你這個分工確定是
transcript.whisperx[695].start 18521.115
transcript.whisperx[695].end 18536.833
transcript.whisperx[695].text 那個原住民的失業率是由原民會來做是嗎好那這個部分本席在這裡要求那你們是不是可以討論一下就是說也理解了解一下那提供你們平常在做那個失業率的部分好怎麼樣做然後也跟原住民的部分
transcript.whisperx[696].start 18537.293
transcript.whisperx[696].end 18562.893
transcript.whisperx[696].text 就是說大家做一下意見交流我覺得在做之前我們這樣好不好我們來跟原住民原民會討論一下他們做的方法上面有沒有什麼地方可以我們有提供建議的地方我們會來找他們因為以前你們勞動部應該是自己也有做過你可以去了解一下看看我印象中是這樣子另外就是說我要講的是
transcript.whisperx[697].start 18564.761
transcript.whisperx[697].end 18581.209
transcript.whisperx[697].text 再來就是說大家如果不是在數據上琢磨的話那我認為就是說剛剛前面委員提到的在這個營造業特別蓋房子這個部分
transcript.whisperx[698].start 18583.453
transcript.whisperx[698].end 18596.218
transcript.whisperx[698].text 其實不談先不談這個失業率我們談的是說在我們現在的這個逃逸的外籍勞工人數已經邁入
transcript.whisperx[699].start 18599.139
transcript.whisperx[699].end 18626.812
transcript.whisperx[699].text 10万9万也快10万了多少9万4很快可能你再过一两个礼拜搞不好就变10万了所以这个部分你们导师可以好好的去了解一下因为这个部分影响的是我们原来从事这些营造业的我们原住民的朋友的日薪他们的收入
transcript.whisperx[700].start 18628.066
transcript.whisperx[700].end 18652.987
transcript.whisperx[700].text 因為就請這個逃逸的就比較便宜啊那當然大家都會去請那我們也遇到就是說之前有原住民的朋友拿不到工資的來跟我們懲請我們有協助去溝通那拿到以後他生氣不聘請這個正常的原住民的這個老公朋友現在就轉而去聘請這些逃逸的
transcript.whisperx[701].start 18654.298
transcript.whisperx[701].end 18671.645
transcript.whisperx[701].text 所以你們應該也要我要在這邊也要請你們再做一個研究跟評估就是這個逃逸的這個外籍勞工對營造業的勞工的就業影響以及這個衝擊評估好特別是原住民的部分
transcript.whisperx[702].start 18673.598
transcript.whisperx[702].end 18702.939
transcript.whisperx[702].text 我們綜合的來思考一下好了這部分對不是我不曉得你的思考是什麼就是我們來看一下你要思考什麼我請你做這個評估你要思考什麼就是可以跟不可以我們來看一下這個評估現在有沒有一些資料可以來提供我們請我們研究所來看一下對有嗎現在有嗎現在沒有嗎就請你們做啊對如果他說沒有能做嗎如果沒有的話我們就來進行吧對好這部分也請你們一併就做一下
transcript.whisperx[703].start 18705.083
transcript.whisperx[703].end 18732.465
transcript.whisperx[703].text 好那大概我想就针对原住民的部分大概是这样那我最后提一下比较具体一点的在我也想同步了解一下就是这个缺工缺工因为那个目前目前统计出来就是那个旅宿业流动率就特别高嘛我们在这个表上面很清楚
transcript.whisperx[704].start 18733.53
transcript.whisperx[704].end 18743.878
transcript.whisperx[704].text 平均就花了花了大概三個月好的招募然後也很難找到人所以我想從這個表
transcript.whisperx[705].start 18745.952
transcript.whisperx[705].end 18769.85
transcript.whisperx[705].text 我們今天都脫稿來質詢那這個部分我們就是因為我觀察到的在台東那個勞動部去辦理這個就是說就業的這些這些媒合那是就是等於大雜燴各類型的全部都在一起
transcript.whisperx[706].start 18771.348
transcript.whisperx[706].end 18799.93
transcript.whisperx[706].text 也很好也认真但是呢我们有没有考虑过就是说我们在未来是不是就是说分类更集中比如说我今天我针对的是这个吕树叶的我们就今天就来一个好来一个吕树叶很集中有之前做过我不知道因为我在台东我是没有看到我刚好可能没看到之前针对吕树叶我们其实有进专案媒合但有媒合到我们那里去吗
transcript.whisperx[707].start 18802.562
transcript.whisperx[707].end 18830.305
transcript.whisperx[707].text 那個不要緊我是說建議我不是說只有鋁樹葉啦我說未來你們就是說整體綜合的那是不是未來有幾項抽出來我們也就是分類型去辦理我在這裡我沒有沒有責備的意思啦我是說我們可以好調整一下那我也想了解就是說因為我去台東我有去參加那個就是那個中高齡的
transcript.whisperx[708].start 18831.426
transcript.whisperx[708].end 18850.736
transcript.whisperx[708].text 那個就業的你們有一個就業的那個中心開幕我有去那這半年就是台東縣銀髮人才服務據點的這個部分可能已經經過6個月了我想了解一下這6個月你們的成效怎麼樣
transcript.whisperx[709].start 18852.484
transcript.whisperx[709].end 18878.217
transcript.whisperx[709].text 大概我想大概是这样所以我们一周内把相关的资料送到委员办公室好不好你们在会后再麻烦一下那因为刚刚就是有那个刚刚也有原住民的立委特别有提到就是说好像我们常在做那个就业的那个训练啊职训都是固定的好像都只有那几种类型而且不是很高阶的
transcript.whisperx[710].start 18879.057
transcript.whisperx[710].end 18899.743
transcript.whisperx[710].text 我要在這裡點出一個問題啦因為我知道你們資訊有時候也是委外那在我們台東確實有一些有奇特的現象長期以來呢可能就是單一的協會在辦理那這個單一協會的辦理就很容易他就是會有集中在幾項的這個
transcript.whisperx[711].start 18902.945
transcript.whisperx[711].end 18918.771
transcript.whisperx[711].text 我們的這個執訓的部分那除了表面上是這樣那實質上有沒有其他的目的我覺得你們應該也要關心一下我今天在這裡我就不要講的太明講出來就傷感情了我想這個部分未來
transcript.whisperx[712].start 18920.051
transcript.whisperx[712].end 18934.078
transcript.whisperx[712].text 就是說我們在這個執訓的委外單位的這個訓練跟培養其實也可以更多元好大機會可以給更多的人去參與好 以上謝謝好 謝謝接下來請葉原職委員來做詢問
transcript.whisperx[713].start 18952.931
transcript.whisperx[713].end 18968.326
transcript.whisperx[713].text 主席好 今天部長沒關係反正不想要叫你 但既然你上來就問一下就看你啊部長好我想我只有接到一個陳情他是這樣子就是他的爸爸是89歲
transcript.whisperx[714].start 18970.248
transcript.whisperx[714].end 18992.846
transcript.whisperx[714].text 然後在一兩年前當時他的外籍看護啊就是被發現居然對他的爸爸強插鼻胃管然後後來他們發現之後覺得非常不可思議因為他爸爸當時在八九歲嘛抗拒但是力氣沒有看護這麼大啦看護就一直一直要幫他插進去啊然後家人看到之後都非常心痛
transcript.whisperx[715].start 18993.747
transcript.whisperx[715].end 19022.368
transcript.whisperx[715].text 那這個事情當然對家屬而言他沒有辦法接受所以後來就要申請廢紙聘僱那這件事情後來事發之後九天這個看護就跑掉了跑掉那本來應該是遇到這個狀況應該是有兩種一種是廢聘要求他直接遣返是有這種機制然後另外但是廢聘廢聘遣返是不是空窗期會等比較久他的看護空窗期會比較久嗎
transcript.whisperx[716].start 19023.592
transcript.whisperx[716].end 19036.634
transcript.whisperx[716].text 一個月吧一個月那廢聘轉出的話空窗期會比較短嗎如果部長不了解的話可以請那個相關單位回答
transcript.whisperx[717].start 19038.328
transcript.whisperx[717].end 19054.474
transcript.whisperx[717].text 如果是經過外國人有違規廢聘的話雇主是可以立即遞補那如果是雙方合意解約的話那超過一個月以上也可以遞補所以就變成說雙方要第一個要合意如果沒辦法合意的話就會拖非常久嘛
transcript.whisperx[718].start 19055.274
transcript.whisperx[718].end 19080.953
transcript.whisperx[718].text 然後第二個不是如果是外國人違規不可歸咎於雇主的話其實可以直接就轉換可以直接就遞補問題是你認定你要由誰來認定是不是要經過一定的認定程序地方政府會來認定所以他就是第一個就是認定的時間然後第二個就是雙方要提出很多對自己比較有利的證據那有的時候可能也沒有辦法馬上有答案我現在
transcript.whisperx[719].start 19081.773
transcript.whisperx[719].end 19096.268
transcript.whisperx[719].text 所以家屬就覺得說而且這個案子比較特殊的是後來那個看護跑掉以後他提出廢聘程序的過程當中他要一直幫這個看護付就業安定費還有保費然後
transcript.whisperx[720].start 19098.328
transcript.whisperx[720].end 19116.714
transcript.whisperx[720].text 看護也請律師所以雙方就進入到這種比如說法律的程序廢聘之後不用付專費程序上在申請的程序過程但廢聘之後就不用了對 不用但是過程拖比較久因為看護也有找律師所以要拖比較久
transcript.whisperx[721].start 19117.93
transcript.whisperx[721].end 19139.999
transcript.whisperx[721].text 我現在的問題是這樣第一就是我覺得事後我把這個案子就轉交給勞動部先去了解一下那僱主是覺得說第一他覺得這個看護沒有辦法得到應有的處分因為強插鼻胃管這個事情應該有違法吧
transcript.whisperx[722].start 19140.899
transcript.whisperx[722].end 19156.11
transcript.whisperx[722].text 可是到目前為止都沒有認定他有違法的狀況然後僱主認為說這個事情應該不是一般的勞資糾紛他有牽涉到虐待老人的問題那我們現在勞動部好像相關的法令都比較偏向外籍看護
transcript.whisperx[723].start 19157.111
transcript.whisperx[723].end 19172.891
transcript.whisperx[723].text 所以其實這衍生出來的問題是其實我們有很多不只是這位長者啦可能有一些生長者 重度生長者他也會面臨到外籍看護虐待的問題但有沒有一個機制是能夠保護雇主的
transcript.whisperx[724].start 19173.191
transcript.whisperx[724].end 19201.667
transcript.whisperx[724].text 就是說譬如說可以立刻讓僱主可以讓他廢聘速度快一點而且在廢聘的申請過程當中可以不用再去繳什麼就業安定費然後或者是保費然後讓他可以在那個空窗期是可以越短越好的因為很多僱主會擔心的是我現在去申請這個廢聘的程序我不知道下一個看護什麼時候會來那中間就會衍生出空窗期的問題我覺得這個是很多僱主會擔心的部分
transcript.whisperx[725].start 19203.072
transcript.whisperx[725].end 19228.747
transcript.whisperx[725].text 那個根本說沒有如果這個外籍勘案有違規的狀況當然這可以用透過1955來做透過1955來做申訴那如果需要調查的話當然也可以請地方政府來做查查這部分是這樣那第二個是當然如果這個當然廢聘期間可能要確認廢聘了以後才能不繳就安定費啦不然這過程會很難認定這樣子
transcript.whisperx[726].start 19231.448
transcript.whisperx[726].end 19260.704
transcript.whisperx[726].text 再一个事情说如果有空窗期的话当然现在其实也是可以用短照或者是传息的资源来去协助那这个短照跟传息的资源目前就我们知道卫福部这边其实也有做相关政府有相关的补助跟补贴对那有关于就是很多雇主认为说像虐待老人或者是看护可能虐待这种认定好像都轻轻放过把它当做是一般的劳资纠纷那这个有什么救济管道吗
transcript.whisperx[727].start 19262.255
transcript.whisperx[727].end 19271.471
transcript.whisperx[727].text 這個可能會要是請地方政府然後社政單位來做這個相關的認定但我覺得有牽涉到全國的一致性這有牽涉到全國一致性
transcript.whisperx[728].start 19272.61
transcript.whisperx[728].end 19293.975
transcript.whisperx[728].text 對 但是我就說執行這件事情當然是地方政府要執行那當然運用的法規就是說是不是有虐待的法規這個是老扶法嘛對不對是老扶法要來做認定對 就是從老扶法來去做是否有虐待或者是這個很不OK的對待的狀況會是由老扶法來做判定
transcript.whisperx[729].start 19294.451
transcript.whisperx[729].end 19310.787
transcript.whisperx[729].text 好OK我希望勞動部可以可以關心一下啦這些可能有遭受到虐待或者是不當對待的這些僱主啦他們的一些權利跟他們心聲啦那這個應該是不牽涉到地方啦希望勞動部可以關心一下這個因為我剛講那個案例在
transcript.whisperx[730].start 19311.528
transcript.whisperx[730].end 19333.569
transcript.whisperx[730].text 在一些外籍看护的雇主的群组其实是大家我们有了解到对对对当然新生是大家是蛮有共鸣的所以希望劳动部可以了解然后再一点时间上次有问部长说研究一下因为既然我们就医院安定精精啊钱那么多都可以拍影片那是不是可以让一些中度或重度失能以上的雇主
transcript.whisperx[731].start 19334.301
transcript.whisperx[731].end 19362.807
transcript.whisperx[731].text 就是说他是要请外籍看护来照顾他家人这些雇主可以免缴救援安定费这个上次好像部长说要研议跟委员说明接下来在救援费的使用上面我们很明确做了判定只要是不相干的业务的话就不能够使用救援费这本来就应该这样所以我们其实在今年已经做了更严格的规定所以过去的某些使用也许会有一些大家因为我下面要去扯那个那些事情对所以我还是要先说因为委员刚才前面先讲了这个部分第二个是说
transcript.whisperx[732].start 19363.727
transcript.whisperx[732].end 19383.92
transcript.whisperx[732].text 针对救安费比方说比较特殊的状况的救安费那是不是要减收或者是什么状况当然我觉得我们这部分是可以来研议的有啦上一次来咨询就说要研议因为又过一个月了啦赶快上次有答应要给我们那个报告时间快到了提醒你一下因为我知道你们做了严格规范代表说
transcript.whisperx[733].start 19384.961
transcript.whisperx[733].end 19405.173
transcript.whisperx[733].text 花的會比較少嘛因為之前就是太多了太多他就亂花嘛那你現在嚴格規範代表就是很多錢會省下來嘛啊這個錢既然省下來基金也沒有要用到的話不如就讓那些中重度失能家庭可以勉強嘛就回饋給弱勢啦我們綜合的來對評估一下對好好謝謝好謝謝接下來請張雅玲委員來做詢問
transcript.whisperx[734].start 19421.469
transcript.whisperx[734].end 19440.544
transcript.whisperx[734].text 謝謝主席我們邀請洪部長部長好我想請教一下你覺得你的工作跟你們勞動部的工作跟生育率提升有沒有關係我覺得現在各部會的工作都跟生育率有關係
transcript.whisperx[735].start 19441.69
transcript.whisperx[735].end 19460.548
transcript.whisperx[735].text 好 那我跟你分享一份研究报告它其实已经不是新的研究报告了但是最近这位郑彦新研究员中研院的研究员他在8月5号的时候在中研院的学术讲堂再次针对如何理解台湾的低生育率现象的时候呢
transcript.whisperx[736].start 19461.992
transcript.whisperx[736].end 19481.203
transcript.whisperx[736].text 進行演講然後這副影片呢哇迴響非常大有超過一萬人來觀看這個這副這個影片喔所以我想這個影片的主題大家非常有共鳴那我簡單跟部長講一下又看過你看過了是不是好那總結了三個重點嘛對不對那部長他講了三個重點
transcript.whisperx[737].start 19482.504
transcript.whisperx[737].end 19505.389
transcript.whisperx[737].text 為什麼大家不結婚的主因就是婚姻跟生育的概念問題第二個年輕世代不結婚的主因就是因為工時很長沒有對象然後呢還有這個經濟門檻比較高那第三個是這個那我想我們今天就先針對於第二個年輕世代不結婚的主因來跟部長做個討論那我想這個工時很長不僅是影響到大家可能
transcript.whisperx[738].start 19506.85
transcript.whisperx[738].end 19530.488
transcript.whisperx[738].text 應該我簡單講一下他講就是說他的研究是說如果你有生如果你有結婚那其實蠻高的比例都會生小孩這是他裡面的一個重點那但是呢所以要如何讓年輕人結婚那就是非常重要的一件事情可是呢現在年輕人就因為工時太長了他其實沒有時間去做社交那其實也就很難產生到接下來我們要結婚生小孩這個部分所以呢我想跟部長來討論就是說因為這個
transcript.whisperx[739].start 19533.31
transcript.whisperx[739].end 19560.121
transcript.whisperx[739].text 工時很長不僅只是影響到生育率還有家長之間的教養關係以及我們的這個孩子的學習時數也是很有關係所以我想跟部長來討論一下就是您現在有沒有跟我們其他的部會一起來討論來解決這個工時過長的問題例如就是說可能像是交友與生活空間改善的一個策略跟內政部來做個討論
transcript.whisperx[740].start 19562.591
transcript.whisperx[740].end 19591.457
transcript.whisperx[740].text 跟 內政部為什麼是跟內政部對啊 因為交友與生活空間的改善因為內政部是人口的部分嘛因為通常公職問題大家都會是指責勞動部公職但也有你的部分等一下下題就是你的我們是沒有跟內政部直接討論說這個休閒的空間的問題啦這個休閒空間生活空間跟交友空間的部分
transcript.whisperx[741].start 19592.057
transcript.whisperx[741].end 19607.241
transcript.whisperx[741].text 我們應該是沒有跟內政部針對這個主題來進行討論這樣子但是整體在少子化精英政策裡面我們當然是這裡面我們當然也很願意在我們業務業館的業務下面來協助那工時的部分的確
transcript.whisperx[742].start 19609.762
transcript.whisperx[742].end 19632.765
transcript.whisperx[742].text 我們其實也很希望就是說比方說我們在相關的政策上這也是為什麼我們希望能夠逐年的來提高最低工資就是希望把因為過去會有一些勞工他因為他的薪資比較低所以他必須透過一直加班來增加薪水所以我們希望把這些比較低薪的勞工的他的這個最低的地板的薪資地板的狀況盡量往上拉也希望能夠減少大家
transcript.whisperx[743].start 19633.706
transcript.whisperx[743].end 19648.572
transcript.whisperx[743].text 加班的機會可是加班與否的問題的確會跟整個台灣的經濟情境的景氣也會有關係所以裡面聯動的因素也會蠻多的對 那我想問一下就是說因為其實 幫我下頁好了
transcript.whisperx[744].start 19649.605
transcript.whisperx[744].end 19666.816
transcript.whisperx[744].text 因為其實我們在看113年的勞工生活及就業狀況調查裡面也有提到就是不改變目前的一個工作時數的狀況之下因為剛剛聽起來解決工時的要處理的問題還蠻複雜跟經濟有非常關係非常多關係那勞工其實就有提到如果每週工作
transcript.whisperx[745].start 19667.757
transcript.whisperx[745].end 19684.779
transcript.whisperx[745].text 有46.5%的人希望可以採彈性工時的一個工作方式那我想這其實也是一個目前可以解決在不影響工時的狀況整體工時的狀況的一個方法那可是呢我也有看到很多的家長他們在網路也有提到說
transcript.whisperx[746].start 19685.8
transcript.whisperx[746].end 19701.534
transcript.whisperx[746].text 他也很希望可以有彈性工時讓他可以去接送小孩那之前我們現在已經做到這個育嬰明年要開始嘛育嬰彈性的這個部分那接下來我就想要請教我們是不是可以針對這個地方提供給不管是家長也好或是年輕的工作者也好有更多的一個彈性呢
transcript.whisperx[747].start 19703.373
transcript.whisperx[747].end 19715.829
transcript.whisperx[747].text 跟文報告其實現在我們的確看到現在很多勞工他對於職場的彈性的需求或對這個需求的表達的程度比以往來的更高那
transcript.whisperx[748].start 19718.052
transcript.whisperx[748].end 19743.232
transcript.whisperx[748].text 甚至也不只只有年輕的勞工這樣表達但是的確年輕的勞工表達需要這樣彈性的比例或者強烈的程度也是比較高這也是為什麼我們在設計我們給青壯世代包括我們讓這個家庭照顧價可以更彈性以小時來請 嬰嬰留庭可以以日來請的重要的原因那我們其實就目前我們政策上面我們有一些
transcript.whisperx[749].start 19744.293
transcript.whisperx[749].end 19758.647
transcript.whisperx[749].text 補助那如果尤其是有些婦女他如果二度就業他需要有更彈性的彈性工時的話來去協調相關上下班時間的部分的話其實我們有給雇主相對應的補助其實也有但都是圍繞著怎麼讓職場更彈性的這個主題
transcript.whisperx[750].start 19761.594
transcript.whisperx[750].end 19782.61
transcript.whisperx[750].text 對 但是我想也可能不是二度就業啦應該是所有的不管是現在的上班族可能特別是針對於家長他們都有強烈的表達他們非常期待有這樣子的一個需求那雖然說性工法提供了這樣子的一個規定可是事實上實務上到底有多少的企業提供了這樣子的一個服務跟一個支持我不曉得勞動部這邊有統計嗎因為我們是沒有找到相關的資料
transcript.whisperx[751].start 19783.393
transcript.whisperx[751].end 19809.714
transcript.whisperx[751].text 我們可能相關的統計我們還要再來看一下有沒有這樣相關的數字那我想一下我想確認一下就是說如果我們這邊目前沒有相關的數字我們是不是可以進行相關的調查了解到底實務上面到底有多少企業可以做到這件事情我是覺得這個主題是蠻值得來了解一下的對可以嗎好那這個如果大概什麼時候可以告訴我們有相關的資料如果有的話這個調查可能會需要的時間會長一點我覺得可能要半年喔
transcript.whisperx[752].start 19810.083
transcript.whisperx[752].end 19823
transcript.whisperx[752].text 沒有啦 你們如果現在手邊有資料的話給你們多少時間找一下我們可能沒有非常嚴謹的調查的資料對 我們如果有資料我們到委員辦公室這邊來跟委員討論好 沒關係
transcript.whisperx[753].start 19825.243
transcript.whisperx[753].end 19840.328
transcript.whisperx[753].text 那如果沒有的話我就希望我們至少在半年之內我們可以了解一下到底食物上面有多少的企業可以提供這樣子的支持那我們才能夠知道說是不是接下來我們下一步可以怎麼做那在下一個部分想要延續一樣再往下
transcript.whisperx[754].start 19841.929
transcript.whisperx[754].end 19857.338
transcript.whisperx[754].text 延續一下我想部長最近也應該有看到韓國的生育率微幅的上漲對不對這個大家也重新的去看了一下他們提供了非常非常多的一個支持那我今天先簡單講一個重點就好了因為時間也有限那就是我講一個重點就是說在
transcript.whisperx[755].start 19858.058
transcript.whisperx[755].end 19882.064
transcript.whisperx[755].text 在韓國生育率的微幅上漲其實他有三個重點那我自己特別覺得很關鍵的一個是2025年起政府強制要求上司公司揭露托兒與育嬰相關的統計資料並且對中小企業提供財政的補助然後也計劃在育兒支援工作家庭平衡和住房補貼上投入了19.7兆的一個韓元較2024年成長了22%
transcript.whisperx[756].start 19884.644
transcript.whisperx[756].end 19904.571
transcript.whisperx[756].text 所以我覺得這個上市公司或者是中小企業我們如何鼓勵他們更積極的去鼓勵他們其實也是一個非常關鍵的事情所以我也想要了解說在這個部分上面這是先提但我先講但是待會兒這是其中一個問題所以等我講完第二個問題的時候部長再一起回答
transcript.whisperx[757].start 19905.151
transcript.whisperx[757].end 19920.547
transcript.whisperx[757].text 所以我們到底有沒有什麼樣子更積極的做法鼓勵大家可以提供更友善育兒的環境第二個部分就是說他們在2026年要即將推動一個政策這個政策是針對育兒期的勞工小學生的家長他10點以後才要去上班
transcript.whisperx[758].start 19922.268
transcript.whisperx[758].end 19935.2
transcript.whisperx[758].text 也就是說他每天可以少一個小時的工作時間來協助勞工育兒那目前他們其實是已經在光州事辦過成效不錯那我也想了解說我們有沒有考慮往這個方向來去效法呢
transcript.whisperx[759].start 19936.974
transcript.whisperx[759].end 19961.439
transcript.whisperx[759].text 委員兩個部分來回答第一個事情是針對企業托育的部分我們正請我們的業務單位在研擬一個希望能夠鼓勵加碼的計劃不管是它的設施比較是在它硬體的設施上或者是在軟體的上面我們也希望有一個擴大的計劃目前我們在研議中
transcript.whisperx[760].start 19962.079
transcript.whisperx[760].end 19981.258
transcript.whisperx[760].text 那大概什么时候我们会知道比较详细的内容呢可能可能年底吧年底是吗应该会跟之前稍微更精进吧因为我想之前过去就能提供托育啦托育的空间这些东西那应该还要再加嘛在软体的部分对我们也认为因为过去我看幕僚很用力的点头因为
transcript.whisperx[761].start 19981.898
transcript.whisperx[761].end 20010.041
transcript.whisperx[761].text 過去在硬體的部分很多還是會回復說受限空間嘛空間還是一個限制的條件所以我們希望在軟體的部分能夠更多的幫助這樣子這是第一個那第二個當然我們有看到韓國的這個做法其實在新聞上面有看到但實際上面我們當然也可以再了解他們實施這個做法以後遇到的問題當然我覺得現在因為台灣的少子化的問題其實相對應的職場制度的調整我覺得各國的做法都應該納為我們參考的對象
transcript.whisperx[762].start 20011.242
transcript.whisperx[762].end 20039.243
transcript.whisperx[762].text 我想这个部分的话就请部长持续的来去了解因为他们就是在光州实施之后效果很不错所以他们才会在2026年全韩国一起试用那这在网路上面许多的家长的回馈台湾家长的回馈都觉得非常的羡慕所以我希望就是说因为刚刚部长有讲嘛步步其实都跟生育率非常有关系那所以也希望劳动部针对这一点也可以持续的再跟进来提供一个更友善的一个工作环境来给我们的家长这样子
transcript.whisperx[763].start 20039.443
transcript.whisperx[763].end 20058.779
transcript.whisperx[763].text 是 怎麼讓這個職場對於家庭的照顧有些對小孩的照顧更有效我想我們近期真的很多相關的業務主管單位都為這個事情花了蠻多的心力在研擬都希望能夠突破一些過去的框架好 那我們就相關的這些資料我們就後續來跟勞動部追 謝謝好 謝謝
transcript.whisperx[764].start 20062.81
transcript.whisperx[764].end 20074.605
transcript.whisperx[764].text 好 謝謝接下來請農民財委員 農民財委員不在請翁曉琳委員 翁曉琳委員不在請林柱英委員 林柱英委員不在
transcript.whisperx[765].start 20076.258
transcript.whisperx[765].end 20099.619
transcript.whisperx[765].text 本次會議詢答全部結束委員楊耀 林德虎 翁曉玲所提書面質詢列入記錄刊登公報 現在作為以下決定第一 報告其詢答完畢第二 委員質詢為其答覆或請補充資料者請相關期慣例兩週內以書面答覆委員另有要求其限則從其所定本次會議到此結束 現在散會