iVOD / 15718

Field Value
IVOD_ID 15718
IVOD_URL https://ivod.ly.gov.tw/Play/Full/1M/15718
日期 2024-03-13
會議資料.會議代碼 委員會-11-1-26-5
會議資料.會議代碼:str 第11屆第1會期社會福利及衛生環境委員會第5次全體委員會議
會議資料.屆 11
會議資料.會期 1
會議資料.會次 5
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1會期社會福利及衛生環境委員會第5次全體委員會議
影片種類 Full
開始時間 2024-03-13T08:30:31+08:00
結束時間 2024-03-13T13:24:00+08:00
影片長度 04:53:29
支援功能[0] ai-transcript
video_url https://h264media01.ly.gov.tw:443/vod_1/_definst_/mp4:1M/bfaf9b39ac01a685d26331c83256afb89e2506b9d78cd73c3be8d109af184be4ad9dee8e7ce717095ea18f28b6918d91.mp4/playlist.m3u8
會議時間 2024-03-13T09:00:00+08:00
會議名稱 立法院第11屆第1會期社會福利及衛生環境委員會第5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。 【3月13日及14日二天一次會】)
委員名稱 完整會議
委員發言時間 08:30:31 - 13:24:00
transcript.pyannote[0].speaker SPEAKER_28
transcript.pyannote[0].start 361.25721875
transcript.pyannote[0].end 361.51034375
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 1774.21784375
transcript.pyannote[1].end 1775.21346875
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 1775.95596875
transcript.pyannote[2].end 1777.62659375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 1791.97034375
transcript.pyannote[3].end 1792.03784375
transcript.pyannote[4].speaker SPEAKER_03
transcript.pyannote[4].start 1794.18096875
transcript.pyannote[4].end 1794.51846875
transcript.pyannote[5].speaker SPEAKER_03
transcript.pyannote[5].start 1794.82221875
transcript.pyannote[5].end 1798.78784375
transcript.pyannote[6].speaker SPEAKER_07
transcript.pyannote[6].start 1798.78784375
transcript.pyannote[6].end 1798.80471875
transcript.pyannote[7].speaker SPEAKER_03
transcript.pyannote[7].start 1799.39534375
transcript.pyannote[7].end 1800.03659375
transcript.pyannote[8].speaker SPEAKER_07
transcript.pyannote[8].start 1800.03659375
transcript.pyannote[8].end 1802.51721875
transcript.pyannote[9].speaker SPEAKER_07
transcript.pyannote[9].start 1802.92221875
transcript.pyannote[9].end 1840.35096875
transcript.pyannote[10].speaker SPEAKER_07
transcript.pyannote[10].start 1840.73909375
transcript.pyannote[10].end 1869.15659375
transcript.pyannote[11].speaker SPEAKER_07
transcript.pyannote[11].start 1870.40534375
transcript.pyannote[11].end 1871.97471875
transcript.pyannote[12].speaker SPEAKER_03
transcript.pyannote[12].start 1871.97471875
transcript.pyannote[12].end 1874.89409375
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 1876.42971875
transcript.pyannote[13].end 1884.95159375
transcript.pyannote[14].speaker SPEAKER_03
transcript.pyannote[14].start 1885.10346875
transcript.pyannote[14].end 1887.48284375
transcript.pyannote[15].speaker SPEAKER_03
transcript.pyannote[15].start 1888.95096875
transcript.pyannote[15].end 1890.60471875
transcript.pyannote[16].speaker SPEAKER_03
transcript.pyannote[16].start 1893.96284375
transcript.pyannote[16].end 1895.34659375
transcript.pyannote[17].speaker SPEAKER_03
transcript.pyannote[17].start 1897.54034375
transcript.pyannote[17].end 1898.85659375
transcript.pyannote[18].speaker SPEAKER_03
transcript.pyannote[18].start 1900.57784375
transcript.pyannote[18].end 1901.84346875
transcript.pyannote[19].speaker SPEAKER_03
transcript.pyannote[19].start 1903.17659375
transcript.pyannote[19].end 1903.53096875
transcript.pyannote[20].speaker SPEAKER_03
transcript.pyannote[20].start 1904.22284375
transcript.pyannote[20].end 1905.13409375
transcript.pyannote[21].speaker SPEAKER_03
transcript.pyannote[21].start 1905.57284375
transcript.pyannote[21].end 1913.33534375
transcript.pyannote[22].speaker SPEAKER_03
transcript.pyannote[22].start 1914.43221875
transcript.pyannote[22].end 1917.75659375
transcript.pyannote[23].speaker SPEAKER_03
transcript.pyannote[23].start 1919.41034375
transcript.pyannote[23].end 1922.36346875
transcript.pyannote[24].speaker SPEAKER_03
transcript.pyannote[24].start 1923.25784375
transcript.pyannote[24].end 1926.98721875
transcript.pyannote[25].speaker SPEAKER_03
transcript.pyannote[25].start 1927.66221875
transcript.pyannote[25].end 1930.95284375
transcript.pyannote[26].speaker SPEAKER_03
transcript.pyannote[26].start 1932.08346875
transcript.pyannote[26].end 1935.99846875
transcript.pyannote[27].speaker SPEAKER_03
transcript.pyannote[27].start 1936.74096875
transcript.pyannote[27].end 1939.45784375
transcript.pyannote[28].speaker SPEAKER_03
transcript.pyannote[28].start 1940.38596875
transcript.pyannote[28].end 1943.15346875
transcript.pyannote[29].speaker SPEAKER_03
transcript.pyannote[29].start 1944.28409375
transcript.pyannote[29].end 1947.11909375
transcript.pyannote[30].speaker SPEAKER_03
transcript.pyannote[30].start 1948.18221875
transcript.pyannote[30].end 1952.40096875
transcript.pyannote[31].speaker SPEAKER_03
transcript.pyannote[31].start 1953.36284375
transcript.pyannote[31].end 1957.85159375
transcript.pyannote[32].speaker SPEAKER_03
transcript.pyannote[32].start 1959.20159375
transcript.pyannote[32].end 1962.45846875
transcript.pyannote[33].speaker SPEAKER_03
transcript.pyannote[33].start 1963.48784375
transcript.pyannote[33].end 1971.43596875
transcript.pyannote[34].speaker SPEAKER_03
transcript.pyannote[34].start 1971.90846875
transcript.pyannote[34].end 1972.81971875
transcript.pyannote[35].speaker SPEAKER_03
transcript.pyannote[35].start 1973.56221875
transcript.pyannote[35].end 1974.94596875
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 1975.33409375
transcript.pyannote[36].end 1976.26221875
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 1976.80221875
transcript.pyannote[37].end 1978.60784375
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 1979.16471875
transcript.pyannote[38].end 1980.12659375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 1980.56534375
transcript.pyannote[39].end 1981.52721875
transcript.pyannote[40].speaker SPEAKER_03
transcript.pyannote[40].start 1982.32034375
transcript.pyannote[40].end 1990.97721875
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 1991.65221875
transcript.pyannote[41].end 1995.65159375
transcript.pyannote[42].speaker SPEAKER_03
transcript.pyannote[42].start 1997.10284375
transcript.pyannote[42].end 1998.08159375
transcript.pyannote[43].speaker SPEAKER_27
transcript.pyannote[43].start 2001.89534375
transcript.pyannote[43].end 2005.25346875
transcript.pyannote[44].speaker SPEAKER_27
transcript.pyannote[44].start 2005.74284375
transcript.pyannote[44].end 2009.97846875
transcript.pyannote[45].speaker SPEAKER_27
transcript.pyannote[45].start 2010.24846875
transcript.pyannote[45].end 2012.02034375
transcript.pyannote[46].speaker SPEAKER_27
transcript.pyannote[46].start 2012.54346875
transcript.pyannote[46].end 2018.24721875
transcript.pyannote[47].speaker SPEAKER_27
transcript.pyannote[47].start 2018.56784375
transcript.pyannote[47].end 2023.78221875
transcript.pyannote[48].speaker SPEAKER_27
transcript.pyannote[48].start 2024.11971875
transcript.pyannote[48].end 2027.76471875
transcript.pyannote[49].speaker SPEAKER_27
transcript.pyannote[49].start 2028.05159375
transcript.pyannote[49].end 2031.54471875
transcript.pyannote[50].speaker SPEAKER_27
transcript.pyannote[50].start 2031.81471875
transcript.pyannote[50].end 2033.82284375
transcript.pyannote[51].speaker SPEAKER_27
transcript.pyannote[51].start 2034.49784375
transcript.pyannote[51].end 2041.01159375
transcript.pyannote[52].speaker SPEAKER_27
transcript.pyannote[52].start 2041.19721875
transcript.pyannote[52].end 2043.86346875
transcript.pyannote[53].speaker SPEAKER_27
transcript.pyannote[53].start 2044.18409375
transcript.pyannote[53].end 2047.20471875
transcript.pyannote[54].speaker SPEAKER_27
transcript.pyannote[54].start 2047.42409375
transcript.pyannote[54].end 2051.65971875
transcript.pyannote[55].speaker SPEAKER_27
transcript.pyannote[55].start 2052.14909375
transcript.pyannote[55].end 2056.28346875
transcript.pyannote[56].speaker SPEAKER_27
transcript.pyannote[56].start 2056.63784375
transcript.pyannote[56].end 2058.76409375
transcript.pyannote[57].speaker SPEAKER_27
transcript.pyannote[57].start 2059.08471875
transcript.pyannote[57].end 2060.53596875
transcript.pyannote[58].speaker SPEAKER_27
transcript.pyannote[58].start 2060.62034375
transcript.pyannote[58].end 2064.80534375
transcript.pyannote[59].speaker SPEAKER_27
transcript.pyannote[59].start 2065.29471875
transcript.pyannote[59].end 2068.48409375
transcript.pyannote[60].speaker SPEAKER_27
transcript.pyannote[60].start 2069.00721875
transcript.pyannote[60].end 2074.47471875
transcript.pyannote[61].speaker SPEAKER_27
transcript.pyannote[61].start 2075.09909375
transcript.pyannote[61].end 2079.50346875
transcript.pyannote[62].speaker SPEAKER_27
transcript.pyannote[62].start 2079.92534375
transcript.pyannote[62].end 2082.97971875
transcript.pyannote[63].speaker SPEAKER_27
transcript.pyannote[63].start 2083.35096875
transcript.pyannote[63].end 2094.72471875
transcript.pyannote[64].speaker SPEAKER_27
transcript.pyannote[64].start 2095.01159375
transcript.pyannote[64].end 2097.17159375
transcript.pyannote[65].speaker SPEAKER_27
transcript.pyannote[65].start 2097.69471875
transcript.pyannote[65].end 2100.07409375
transcript.pyannote[66].speaker SPEAKER_27
transcript.pyannote[66].start 2100.37784375
transcript.pyannote[66].end 2103.66846875
transcript.pyannote[67].speaker SPEAKER_27
transcript.pyannote[67].start 2103.98909375
transcript.pyannote[67].end 2107.54971875
transcript.pyannote[68].speaker SPEAKER_27
transcript.pyannote[68].start 2107.90409375
transcript.pyannote[68].end 2109.97971875
transcript.pyannote[69].speaker SPEAKER_27
transcript.pyannote[69].start 2110.43534375
transcript.pyannote[69].end 2112.93284375
transcript.pyannote[70].speaker SPEAKER_27
transcript.pyannote[70].start 2113.13534375
transcript.pyannote[70].end 2116.94909375
transcript.pyannote[71].speaker SPEAKER_27
transcript.pyannote[71].start 2117.75909375
transcript.pyannote[71].end 2123.49659375
transcript.pyannote[72].speaker SPEAKER_27
transcript.pyannote[72].start 2123.91846875
transcript.pyannote[72].end 2127.15846875
transcript.pyannote[73].speaker SPEAKER_27
transcript.pyannote[73].start 2127.81659375
transcript.pyannote[73].end 2129.09909375
transcript.pyannote[74].speaker SPEAKER_27
transcript.pyannote[74].start 2129.52096875
transcript.pyannote[74].end 2131.54596875
transcript.pyannote[75].speaker SPEAKER_27
transcript.pyannote[75].start 2131.78221875
transcript.pyannote[75].end 2137.62096875
transcript.pyannote[76].speaker SPEAKER_27
transcript.pyannote[76].start 2138.19471875
transcript.pyannote[76].end 2140.70909375
transcript.pyannote[77].speaker SPEAKER_27
transcript.pyannote[77].start 2140.96221875
transcript.pyannote[77].end 2142.83534375
transcript.pyannote[78].speaker SPEAKER_27
transcript.pyannote[78].start 2143.30784375
transcript.pyannote[78].end 2146.34534375
transcript.pyannote[79].speaker SPEAKER_27
transcript.pyannote[79].start 2146.64909375
transcript.pyannote[79].end 2148.53909375
transcript.pyannote[80].speaker SPEAKER_27
transcript.pyannote[80].start 2148.77534375
transcript.pyannote[80].end 2150.49659375
transcript.pyannote[81].speaker SPEAKER_27
transcript.pyannote[81].start 2150.95221875
transcript.pyannote[81].end 2156.11596875
transcript.pyannote[82].speaker SPEAKER_27
transcript.pyannote[82].start 2156.70659375
transcript.pyannote[82].end 2159.99721875
transcript.pyannote[83].speaker SPEAKER_27
transcript.pyannote[83].start 2160.31784375
transcript.pyannote[83].end 2163.08534375
transcript.pyannote[84].speaker SPEAKER_27
transcript.pyannote[84].start 2163.30471875
transcript.pyannote[84].end 2165.27909375
transcript.pyannote[85].speaker SPEAKER_27
transcript.pyannote[85].start 2165.71784375
transcript.pyannote[85].end 2169.86909375
transcript.pyannote[86].speaker SPEAKER_27
transcript.pyannote[86].start 2170.37534375
transcript.pyannote[86].end 2172.28221875
transcript.pyannote[87].speaker SPEAKER_27
transcript.pyannote[87].start 2172.78846875
transcript.pyannote[87].end 2175.03284375
transcript.pyannote[88].speaker SPEAKER_27
transcript.pyannote[88].start 2175.13409375
transcript.pyannote[88].end 2177.39534375
transcript.pyannote[89].speaker SPEAKER_27
transcript.pyannote[89].start 2177.66534375
transcript.pyannote[89].end 2181.54659375
transcript.pyannote[90].speaker SPEAKER_27
transcript.pyannote[90].start 2181.93471875
transcript.pyannote[90].end 2184.22971875
transcript.pyannote[91].speaker SPEAKER_27
transcript.pyannote[91].start 2184.63471875
transcript.pyannote[91].end 2187.04784375
transcript.pyannote[92].speaker SPEAKER_27
transcript.pyannote[92].start 2187.23346875
transcript.pyannote[92].end 2191.19909375
transcript.pyannote[93].speaker SPEAKER_27
transcript.pyannote[93].start 2191.55346875
transcript.pyannote[93].end 2194.13534375
transcript.pyannote[94].speaker SPEAKER_27
transcript.pyannote[94].start 2194.67534375
transcript.pyannote[94].end 2195.90721875
transcript.pyannote[95].speaker SPEAKER_27
transcript.pyannote[95].start 2196.24471875
transcript.pyannote[95].end 2198.35409375
transcript.pyannote[96].speaker SPEAKER_27
transcript.pyannote[96].start 2198.94471875
transcript.pyannote[96].end 2202.30284375
transcript.pyannote[97].speaker SPEAKER_27
transcript.pyannote[97].start 2202.58971875
transcript.pyannote[97].end 2203.73721875
transcript.pyannote[98].speaker SPEAKER_27
transcript.pyannote[98].start 2204.07471875
transcript.pyannote[98].end 2207.92221875
transcript.pyannote[99].speaker SPEAKER_27
transcript.pyannote[99].start 2208.36096875
transcript.pyannote[99].end 2213.67659375
transcript.pyannote[100].speaker SPEAKER_27
transcript.pyannote[100].start 2214.01409375
transcript.pyannote[100].end 2219.44784375
transcript.pyannote[101].speaker SPEAKER_27
transcript.pyannote[101].start 2219.92034375
transcript.pyannote[101].end 2226.68721875
transcript.pyannote[102].speaker SPEAKER_27
transcript.pyannote[102].start 2226.78846875
transcript.pyannote[102].end 2230.48409375
transcript.pyannote[103].speaker SPEAKER_27
transcript.pyannote[103].start 2230.83846875
transcript.pyannote[103].end 2233.89284375
transcript.pyannote[104].speaker SPEAKER_27
transcript.pyannote[104].start 2234.31471875
transcript.pyannote[104].end 2236.99784375
transcript.pyannote[105].speaker SPEAKER_27
transcript.pyannote[105].start 2237.75721875
transcript.pyannote[105].end 2239.15784375
transcript.pyannote[106].speaker SPEAKER_27
transcript.pyannote[106].start 2239.49534375
transcript.pyannote[106].end 2244.84471875
transcript.pyannote[107].speaker SPEAKER_27
transcript.pyannote[107].start 2245.21596875
transcript.pyannote[107].end 2255.34096875
transcript.pyannote[108].speaker SPEAKER_27
transcript.pyannote[108].start 2255.77971875
transcript.pyannote[108].end 2262.39471875
transcript.pyannote[109].speaker SPEAKER_27
transcript.pyannote[109].start 2262.76596875
transcript.pyannote[109].end 2265.66846875
transcript.pyannote[110].speaker SPEAKER_27
transcript.pyannote[110].start 2265.92159375
transcript.pyannote[110].end 2271.52409375
transcript.pyannote[111].speaker SPEAKER_27
transcript.pyannote[111].start 2272.03034375
transcript.pyannote[111].end 2275.32096875
transcript.pyannote[112].speaker SPEAKER_27
transcript.pyannote[112].start 2275.65846875
transcript.pyannote[112].end 2276.85659375
transcript.pyannote[113].speaker SPEAKER_27
transcript.pyannote[113].start 2277.32909375
transcript.pyannote[113].end 2280.14721875
transcript.pyannote[114].speaker SPEAKER_27
transcript.pyannote[114].start 2280.40034375
transcript.pyannote[114].end 2283.11721875
transcript.pyannote[115].speaker SPEAKER_27
transcript.pyannote[115].start 2283.94409375
transcript.pyannote[115].end 2287.40346875
transcript.pyannote[116].speaker SPEAKER_27
transcript.pyannote[116].start 2287.62284375
transcript.pyannote[116].end 2291.75721875
transcript.pyannote[117].speaker SPEAKER_27
transcript.pyannote[117].start 2291.90909375
transcript.pyannote[117].end 2294.13659375
transcript.pyannote[118].speaker SPEAKER_27
transcript.pyannote[118].start 2294.52471875
transcript.pyannote[118].end 2296.83659375
transcript.pyannote[119].speaker SPEAKER_27
transcript.pyannote[119].start 2297.19096875
transcript.pyannote[119].end 2300.07659375
transcript.pyannote[120].speaker SPEAKER_27
transcript.pyannote[120].start 2300.11034375
transcript.pyannote[120].end 2301.88221875
transcript.pyannote[121].speaker SPEAKER_27
transcript.pyannote[121].start 2302.62471875
transcript.pyannote[121].end 2303.94096875
transcript.pyannote[122].speaker SPEAKER_27
transcript.pyannote[122].start 2304.10971875
transcript.pyannote[122].end 2308.22721875
transcript.pyannote[123].speaker SPEAKER_27
transcript.pyannote[123].start 2308.49721875
transcript.pyannote[123].end 2311.39971875
transcript.pyannote[124].speaker SPEAKER_27
transcript.pyannote[124].start 2311.68659375
transcript.pyannote[124].end 2315.31471875
transcript.pyannote[125].speaker SPEAKER_27
transcript.pyannote[125].start 2315.58471875
transcript.pyannote[125].end 2318.14971875
transcript.pyannote[126].speaker SPEAKER_27
transcript.pyannote[126].start 2318.45346875
transcript.pyannote[126].end 2321.37284375
transcript.pyannote[127].speaker SPEAKER_27
transcript.pyannote[127].start 2321.69346875
transcript.pyannote[127].end 2329.67534375
transcript.pyannote[128].speaker SPEAKER_27
transcript.pyannote[128].start 2329.82721875
transcript.pyannote[128].end 2332.34159375
transcript.pyannote[129].speaker SPEAKER_03
transcript.pyannote[129].start 2333.40471875
transcript.pyannote[129].end 2333.60721875
transcript.pyannote[130].speaker SPEAKER_03
transcript.pyannote[130].start 2334.01221875
transcript.pyannote[130].end 2350.02659375
transcript.pyannote[131].speaker SPEAKER_03
transcript.pyannote[131].start 2350.11096875
transcript.pyannote[131].end 2353.01346875
transcript.pyannote[132].speaker SPEAKER_03
transcript.pyannote[132].start 2353.31721875
transcript.pyannote[132].end 2355.24096875
transcript.pyannote[133].speaker SPEAKER_03
transcript.pyannote[133].start 2355.42659375
transcript.pyannote[133].end 2357.24909375
transcript.pyannote[134].speaker SPEAKER_03
transcript.pyannote[134].start 2357.40096875
transcript.pyannote[134].end 2358.64971875
transcript.pyannote[135].speaker SPEAKER_03
transcript.pyannote[135].start 2359.02096875
transcript.pyannote[135].end 2361.85596875
transcript.pyannote[136].speaker SPEAKER_03
transcript.pyannote[136].start 2362.05846875
transcript.pyannote[136].end 2365.24784375
transcript.pyannote[137].speaker SPEAKER_03
transcript.pyannote[137].start 2365.48409375
transcript.pyannote[137].end 2372.13284375
transcript.pyannote[138].speaker SPEAKER_11
transcript.pyannote[138].start 2378.05596875
transcript.pyannote[138].end 2379.25409375
transcript.pyannote[139].speaker SPEAKER_11
transcript.pyannote[139].start 2379.70971875
transcript.pyannote[139].end 2381.61659375
transcript.pyannote[140].speaker SPEAKER_03
transcript.pyannote[140].start 2379.92909375
transcript.pyannote[140].end 2380.78971875
transcript.pyannote[141].speaker SPEAKER_11
transcript.pyannote[141].start 2385.24471875
transcript.pyannote[141].end 2386.56096875
transcript.pyannote[142].speaker SPEAKER_00
transcript.pyannote[142].start 2385.32909375
transcript.pyannote[142].end 2386.03784375
transcript.pyannote[143].speaker SPEAKER_11
transcript.pyannote[143].start 2387.05034375
transcript.pyannote[143].end 2387.53971875
transcript.pyannote[144].speaker SPEAKER_11
transcript.pyannote[144].start 2387.84346875
transcript.pyannote[144].end 2397.31034375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 2394.18846875
transcript.pyannote[145].end 2394.20534375
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 2394.35721875
transcript.pyannote[146].end 2394.61034375
transcript.pyannote[147].speaker SPEAKER_11
transcript.pyannote[147].start 2397.37784375
transcript.pyannote[147].end 2402.15346875
transcript.pyannote[148].speaker SPEAKER_11
transcript.pyannote[148].start 2402.47409375
transcript.pyannote[148].end 2407.92471875
transcript.pyannote[149].speaker SPEAKER_11
transcript.pyannote[149].start 2408.22846875
transcript.pyannote[149].end 2413.18971875
transcript.pyannote[150].speaker SPEAKER_11
transcript.pyannote[150].start 2413.66221875
transcript.pyannote[150].end 2458.92096875
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 2424.98534375
transcript.pyannote[151].end 2425.01909375
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 2425.01909375
transcript.pyannote[152].end 2425.55909375
transcript.pyannote[153].speaker SPEAKER_11
transcript.pyannote[153].start 2459.34284375
transcript.pyannote[153].end 2460.70971875
transcript.pyannote[154].speaker SPEAKER_11
transcript.pyannote[154].start 2461.38471875
transcript.pyannote[154].end 2465.45159375
transcript.pyannote[155].speaker SPEAKER_02
transcript.pyannote[155].start 2465.45159375
transcript.pyannote[155].end 2465.80596875
transcript.pyannote[156].speaker SPEAKER_11
transcript.pyannote[156].start 2465.97471875
transcript.pyannote[156].end 2471.37471875
transcript.pyannote[157].speaker SPEAKER_11
transcript.pyannote[157].start 2471.86409375
transcript.pyannote[157].end 2480.31846875
transcript.pyannote[158].speaker SPEAKER_27
transcript.pyannote[158].start 2481.26346875
transcript.pyannote[158].end 2484.94221875
transcript.pyannote[159].speaker SPEAKER_11
transcript.pyannote[159].start 2481.29721875
transcript.pyannote[159].end 2483.03534375
transcript.pyannote[160].speaker SPEAKER_23
transcript.pyannote[160].start 2483.03534375
transcript.pyannote[160].end 2483.13659375
transcript.pyannote[161].speaker SPEAKER_11
transcript.pyannote[161].start 2483.13659375
transcript.pyannote[161].end 2483.15346875
transcript.pyannote[162].speaker SPEAKER_23
transcript.pyannote[162].start 2484.08159375
transcript.pyannote[162].end 2497.21034375
transcript.pyannote[163].speaker SPEAKER_27
transcript.pyannote[163].start 2486.08971875
transcript.pyannote[163].end 2486.84909375
transcript.pyannote[164].speaker SPEAKER_11
transcript.pyannote[164].start 2487.49034375
transcript.pyannote[164].end 2487.65909375
transcript.pyannote[165].speaker SPEAKER_11
transcript.pyannote[165].start 2491.15221875
transcript.pyannote[165].end 2494.22346875
transcript.pyannote[166].speaker SPEAKER_11
transcript.pyannote[166].start 2495.06721875
transcript.pyannote[166].end 2497.15971875
transcript.pyannote[167].speaker SPEAKER_11
transcript.pyannote[167].start 2497.21034375
transcript.pyannote[167].end 2497.27784375
transcript.pyannote[168].speaker SPEAKER_23
transcript.pyannote[168].start 2497.27784375
transcript.pyannote[168].end 2497.63221875
transcript.pyannote[169].speaker SPEAKER_11
transcript.pyannote[169].start 2497.32846875
transcript.pyannote[169].end 2505.86721875
transcript.pyannote[170].speaker SPEAKER_02
transcript.pyannote[170].start 2505.85034375
transcript.pyannote[170].end 2506.13721875
transcript.pyannote[171].speaker SPEAKER_11
transcript.pyannote[171].start 2506.13721875
transcript.pyannote[171].end 2507.79096875
transcript.pyannote[172].speaker SPEAKER_11
transcript.pyannote[172].start 2508.17909375
transcript.pyannote[172].end 2514.50721875
transcript.pyannote[173].speaker SPEAKER_11
transcript.pyannote[173].start 2515.23284375
transcript.pyannote[173].end 2525.83034375
transcript.pyannote[174].speaker SPEAKER_11
transcript.pyannote[174].start 2526.15096875
transcript.pyannote[174].end 2531.82096875
transcript.pyannote[175].speaker SPEAKER_11
transcript.pyannote[175].start 2532.34409375
transcript.pyannote[175].end 2533.67721875
transcript.pyannote[176].speaker SPEAKER_11
transcript.pyannote[176].start 2534.06534375
transcript.pyannote[176].end 2537.15346875
transcript.pyannote[177].speaker SPEAKER_27
transcript.pyannote[177].start 2537.15346875
transcript.pyannote[177].end 2537.96346875
transcript.pyannote[178].speaker SPEAKER_11
transcript.pyannote[178].start 2538.09846875
transcript.pyannote[178].end 2538.43596875
transcript.pyannote[179].speaker SPEAKER_11
transcript.pyannote[179].start 2538.52034375
transcript.pyannote[179].end 2545.30409375
transcript.pyannote[180].speaker SPEAKER_11
transcript.pyannote[180].start 2545.82721875
transcript.pyannote[180].end 2546.33346875
transcript.pyannote[181].speaker SPEAKER_11
transcript.pyannote[181].start 2546.94096875
transcript.pyannote[181].end 2552.98221875
transcript.pyannote[182].speaker SPEAKER_02
transcript.pyannote[182].start 2552.98221875
transcript.pyannote[182].end 2553.18471875
transcript.pyannote[183].speaker SPEAKER_11
transcript.pyannote[183].start 2553.21846875
transcript.pyannote[183].end 2556.50909375
transcript.pyannote[184].speaker SPEAKER_11
transcript.pyannote[184].start 2556.66096875
transcript.pyannote[184].end 2557.16721875
transcript.pyannote[185].speaker SPEAKER_11
transcript.pyannote[185].start 2557.62284375
transcript.pyannote[185].end 2558.33159375
transcript.pyannote[186].speaker SPEAKER_11
transcript.pyannote[186].start 2558.34846875
transcript.pyannote[186].end 2563.47846875
transcript.pyannote[187].speaker SPEAKER_11
transcript.pyannote[187].start 2563.76534375
transcript.pyannote[187].end 2569.19909375
transcript.pyannote[188].speaker SPEAKER_02
transcript.pyannote[188].start 2569.33409375
transcript.pyannote[188].end 2569.53659375
transcript.pyannote[189].speaker SPEAKER_11
transcript.pyannote[189].start 2569.53659375
transcript.pyannote[189].end 2570.16096875
transcript.pyannote[190].speaker SPEAKER_02
transcript.pyannote[190].start 2569.57034375
transcript.pyannote[190].end 2569.70534375
transcript.pyannote[191].speaker SPEAKER_11
transcript.pyannote[191].start 2570.48159375
transcript.pyannote[191].end 2572.89471875
transcript.pyannote[192].speaker SPEAKER_11
transcript.pyannote[192].start 2573.23221875
transcript.pyannote[192].end 2576.23596875
transcript.pyannote[193].speaker SPEAKER_27
transcript.pyannote[193].start 2576.37096875
transcript.pyannote[193].end 2597.17784375
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 2588.72346875
transcript.pyannote[194].end 2588.97659375
transcript.pyannote[195].speaker SPEAKER_11
transcript.pyannote[195].start 2588.97659375
transcript.pyannote[195].end 2589.66846875
transcript.pyannote[196].speaker SPEAKER_23
transcript.pyannote[196].start 2590.25909375
transcript.pyannote[196].end 2590.61346875
transcript.pyannote[197].speaker SPEAKER_11
transcript.pyannote[197].start 2590.61346875
transcript.pyannote[197].end 2591.23784375
transcript.pyannote[198].speaker SPEAKER_11
transcript.pyannote[198].start 2591.91284375
transcript.pyannote[198].end 2591.94659375
transcript.pyannote[199].speaker SPEAKER_23
transcript.pyannote[199].start 2591.94659375
transcript.pyannote[199].end 2592.21659375
transcript.pyannote[200].speaker SPEAKER_23
transcript.pyannote[200].start 2596.78971875
transcript.pyannote[200].end 2631.19784375
transcript.pyannote[201].speaker SPEAKER_02
transcript.pyannote[201].start 2620.92096875
transcript.pyannote[201].end 2621.86596875
transcript.pyannote[202].speaker SPEAKER_11
transcript.pyannote[202].start 2626.47284375
transcript.pyannote[202].end 2627.18159375
transcript.pyannote[203].speaker SPEAKER_11
transcript.pyannote[203].start 2630.16846875
transcript.pyannote[203].end 2644.93409375
transcript.pyannote[204].speaker SPEAKER_23
transcript.pyannote[204].start 2631.88971875
transcript.pyannote[204].end 2632.32846875
transcript.pyannote[205].speaker SPEAKER_23
transcript.pyannote[205].start 2643.78659375
transcript.pyannote[205].end 2665.26846875
transcript.pyannote[206].speaker SPEAKER_01
transcript.pyannote[206].start 2653.91159375
transcript.pyannote[206].end 2655.80159375
transcript.pyannote[207].speaker SPEAKER_02
transcript.pyannote[207].start 2655.80159375
transcript.pyannote[207].end 2656.12221875
transcript.pyannote[208].speaker SPEAKER_02
transcript.pyannote[208].start 2658.16409375
transcript.pyannote[208].end 2658.21471875
transcript.pyannote[209].speaker SPEAKER_11
transcript.pyannote[209].start 2658.21471875
transcript.pyannote[209].end 2659.78409375
transcript.pyannote[210].speaker SPEAKER_11
transcript.pyannote[210].start 2660.57721875
transcript.pyannote[210].end 2661.08346875
transcript.pyannote[211].speaker SPEAKER_11
transcript.pyannote[211].start 2663.68221875
transcript.pyannote[211].end 2667.20909375
transcript.pyannote[212].speaker SPEAKER_11
transcript.pyannote[212].start 2667.29346875
transcript.pyannote[212].end 2697.06096875
transcript.pyannote[213].speaker SPEAKER_11
transcript.pyannote[213].start 2697.80346875
transcript.pyannote[213].end 2705.51534375
transcript.pyannote[214].speaker SPEAKER_11
transcript.pyannote[214].start 2706.10596875
transcript.pyannote[214].end 2719.72409375
transcript.pyannote[215].speaker SPEAKER_23
transcript.pyannote[215].start 2719.06596875
transcript.pyannote[215].end 2738.32034375
transcript.pyannote[216].speaker SPEAKER_11
transcript.pyannote[216].start 2737.51034375
transcript.pyannote[216].end 2752.54596875
transcript.pyannote[217].speaker SPEAKER_23
transcript.pyannote[217].start 2749.32284375
transcript.pyannote[217].end 2750.35221875
transcript.pyannote[218].speaker SPEAKER_23
transcript.pyannote[218].start 2751.65159375
transcript.pyannote[218].end 2769.35346875
transcript.pyannote[219].speaker SPEAKER_11
transcript.pyannote[219].start 2755.70159375
transcript.pyannote[219].end 2756.02221875
transcript.pyannote[220].speaker SPEAKER_11
transcript.pyannote[220].start 2757.81096875
transcript.pyannote[220].end 2759.49846875
transcript.pyannote[221].speaker SPEAKER_02
transcript.pyannote[221].start 2759.49846875
transcript.pyannote[221].end 2759.56596875
transcript.pyannote[222].speaker SPEAKER_02
transcript.pyannote[222].start 2760.66284375
transcript.pyannote[222].end 2761.20284375
transcript.pyannote[223].speaker SPEAKER_02
transcript.pyannote[223].start 2761.47284375
transcript.pyannote[223].end 2762.09721875
transcript.pyannote[224].speaker SPEAKER_11
transcript.pyannote[224].start 2762.09721875
transcript.pyannote[224].end 2764.84784375
transcript.pyannote[225].speaker SPEAKER_11
transcript.pyannote[225].start 2766.53534375
transcript.pyannote[225].end 2794.71659375
transcript.pyannote[226].speaker SPEAKER_23
transcript.pyannote[226].start 2769.65721875
transcript.pyannote[226].end 2770.12971875
transcript.pyannote[227].speaker SPEAKER_02
transcript.pyannote[227].start 2776.42409375
transcript.pyannote[227].end 2776.50846875
transcript.pyannote[228].speaker SPEAKER_09
transcript.pyannote[228].start 2776.50846875
transcript.pyannote[228].end 2776.89659375
transcript.pyannote[229].speaker SPEAKER_02
transcript.pyannote[229].start 2776.89659375
transcript.pyannote[229].end 2776.93034375
transcript.pyannote[230].speaker SPEAKER_02
transcript.pyannote[230].start 2779.12409375
transcript.pyannote[230].end 2780.08596875
transcript.pyannote[231].speaker SPEAKER_02
transcript.pyannote[231].start 2780.44034375
transcript.pyannote[231].end 2780.82846875
transcript.pyannote[232].speaker SPEAKER_02
transcript.pyannote[232].start 2781.23346875
transcript.pyannote[232].end 2782.04346875
transcript.pyannote[233].speaker SPEAKER_11
transcript.pyannote[233].start 2794.81784375
transcript.pyannote[233].end 2815.21971875
transcript.pyannote[234].speaker SPEAKER_28
transcript.pyannote[234].start 2815.16909375
transcript.pyannote[234].end 2815.50659375
transcript.pyannote[235].speaker SPEAKER_11
transcript.pyannote[235].start 2815.38846875
transcript.pyannote[235].end 2830.74471875
transcript.pyannote[236].speaker SPEAKER_11
transcript.pyannote[236].start 2831.26784375
transcript.pyannote[236].end 2833.10721875
transcript.pyannote[237].speaker SPEAKER_11
transcript.pyannote[237].start 2833.52909375
transcript.pyannote[237].end 2836.65096875
transcript.pyannote[238].speaker SPEAKER_27
transcript.pyannote[238].start 2837.52846875
transcript.pyannote[238].end 2843.83971875
transcript.pyannote[239].speaker SPEAKER_11
transcript.pyannote[239].start 2838.81096875
transcript.pyannote[239].end 2839.11471875
transcript.pyannote[240].speaker SPEAKER_11
transcript.pyannote[240].start 2839.90784375
transcript.pyannote[240].end 2839.99221875
transcript.pyannote[241].speaker SPEAKER_11
transcript.pyannote[241].start 2842.23659375
transcript.pyannote[241].end 2873.74221875
transcript.pyannote[242].speaker SPEAKER_11
transcript.pyannote[242].start 2874.29909375
transcript.pyannote[242].end 2891.71409375
transcript.pyannote[243].speaker SPEAKER_27
transcript.pyannote[243].start 2892.37221875
transcript.pyannote[243].end 2894.19471875
transcript.pyannote[244].speaker SPEAKER_11
transcript.pyannote[244].start 2893.30034375
transcript.pyannote[244].end 2894.27909375
transcript.pyannote[245].speaker SPEAKER_27
transcript.pyannote[245].start 2894.27909375
transcript.pyannote[245].end 2902.32846875
transcript.pyannote[246].speaker SPEAKER_11
transcript.pyannote[246].start 2895.00471875
transcript.pyannote[246].end 2895.47721875
transcript.pyannote[247].speaker SPEAKER_11
transcript.pyannote[247].start 2896.20284375
transcript.pyannote[247].end 2896.45596875
transcript.pyannote[248].speaker SPEAKER_11
transcript.pyannote[248].start 2896.54034375
transcript.pyannote[248].end 2898.93659375
transcript.pyannote[249].speaker SPEAKER_11
transcript.pyannote[249].start 2901.36659375
transcript.pyannote[249].end 2919.45659375
transcript.pyannote[250].speaker SPEAKER_27
transcript.pyannote[250].start 2920.04721875
transcript.pyannote[250].end 2923.77659375
transcript.pyannote[251].speaker SPEAKER_11
transcript.pyannote[251].start 2922.86534375
transcript.pyannote[251].end 2923.82721875
transcript.pyannote[252].speaker SPEAKER_27
transcript.pyannote[252].start 2923.82721875
transcript.pyannote[252].end 2924.41784375
transcript.pyannote[253].speaker SPEAKER_11
transcript.pyannote[253].start 2924.41784375
transcript.pyannote[253].end 2924.43471875
transcript.pyannote[254].speaker SPEAKER_27
transcript.pyannote[254].start 2924.43471875
transcript.pyannote[254].end 2924.60346875
transcript.pyannote[255].speaker SPEAKER_11
transcript.pyannote[255].start 2924.60346875
transcript.pyannote[255].end 2924.62034375
transcript.pyannote[256].speaker SPEAKER_27
transcript.pyannote[256].start 2924.62034375
transcript.pyannote[256].end 2924.73846875
transcript.pyannote[257].speaker SPEAKER_11
transcript.pyannote[257].start 2924.73846875
transcript.pyannote[257].end 2924.80596875
transcript.pyannote[258].speaker SPEAKER_27
transcript.pyannote[258].start 2924.80596875
transcript.pyannote[258].end 2924.87346875
transcript.pyannote[259].speaker SPEAKER_11
transcript.pyannote[259].start 2924.87346875
transcript.pyannote[259].end 2929.44659375
transcript.pyannote[260].speaker SPEAKER_27
transcript.pyannote[260].start 2925.34596875
transcript.pyannote[260].end 2925.36284375
transcript.pyannote[261].speaker SPEAKER_27
transcript.pyannote[261].start 2929.44659375
transcript.pyannote[261].end 2935.26846875
transcript.pyannote[262].speaker SPEAKER_11
transcript.pyannote[262].start 2929.61534375
transcript.pyannote[262].end 2930.30721875
transcript.pyannote[263].speaker SPEAKER_27
transcript.pyannote[263].start 2935.42034375
transcript.pyannote[263].end 2936.26409375
transcript.pyannote[264].speaker SPEAKER_11
transcript.pyannote[264].start 2935.53846875
transcript.pyannote[264].end 2942.03534375
transcript.pyannote[265].speaker SPEAKER_27
transcript.pyannote[265].start 2936.60159375
transcript.pyannote[265].end 2936.97284375
transcript.pyannote[266].speaker SPEAKER_27
transcript.pyannote[266].start 2937.76596875
transcript.pyannote[266].end 2938.45784375
transcript.pyannote[267].speaker SPEAKER_27
transcript.pyannote[267].start 2939.55471875
transcript.pyannote[267].end 2939.72346875
transcript.pyannote[268].speaker SPEAKER_27
transcript.pyannote[268].start 2940.56721875
transcript.pyannote[268].end 2941.07346875
transcript.pyannote[269].speaker SPEAKER_00
transcript.pyannote[269].start 2941.07346875
transcript.pyannote[269].end 2941.12409375
transcript.pyannote[270].speaker SPEAKER_11
transcript.pyannote[270].start 2943.46971875
transcript.pyannote[270].end 2943.52034375
transcript.pyannote[271].speaker SPEAKER_11
transcript.pyannote[271].start 2943.72284375
transcript.pyannote[271].end 2947.40159375
transcript.pyannote[272].speaker SPEAKER_27
transcript.pyannote[272].start 2946.06846875
transcript.pyannote[272].end 2946.38909375
transcript.pyannote[273].speaker SPEAKER_27
transcript.pyannote[273].start 2946.82784375
transcript.pyannote[273].end 2947.33409375
transcript.pyannote[274].speaker SPEAKER_27
transcript.pyannote[274].start 2947.40159375
transcript.pyannote[274].end 2951.13096875
transcript.pyannote[275].speaker SPEAKER_11
transcript.pyannote[275].start 2948.75159375
transcript.pyannote[275].end 2950.18596875
transcript.pyannote[276].speaker SPEAKER_11
transcript.pyannote[276].start 2950.99596875
transcript.pyannote[276].end 2980.05471875
transcript.pyannote[277].speaker SPEAKER_00
transcript.pyannote[277].start 2962.18409375
transcript.pyannote[277].end 2962.21784375
transcript.pyannote[278].speaker SPEAKER_27
transcript.pyannote[278].start 2962.21784375
transcript.pyannote[278].end 2963.97284375
transcript.pyannote[279].speaker SPEAKER_00
transcript.pyannote[279].start 2963.97284375
transcript.pyannote[279].end 2964.91784375
transcript.pyannote[280].speaker SPEAKER_11
transcript.pyannote[280].start 2981.08409375
transcript.pyannote[280].end 2985.01596875
transcript.pyannote[281].speaker SPEAKER_28
transcript.pyannote[281].start 2984.83034375
transcript.pyannote[281].end 2985.60659375
transcript.pyannote[282].speaker SPEAKER_11
transcript.pyannote[282].start 2985.25221875
transcript.pyannote[282].end 3021.34784375
transcript.pyannote[283].speaker SPEAKER_02
transcript.pyannote[283].start 3011.56034375
transcript.pyannote[283].end 3011.96534375
transcript.pyannote[284].speaker SPEAKER_00
transcript.pyannote[284].start 3011.96534375
transcript.pyannote[284].end 3012.38721875
transcript.pyannote[285].speaker SPEAKER_00
transcript.pyannote[285].start 3013.97346875
transcript.pyannote[285].end 3014.02409375
transcript.pyannote[286].speaker SPEAKER_03
transcript.pyannote[286].start 3014.02409375
transcript.pyannote[286].end 3014.66534375
transcript.pyannote[287].speaker SPEAKER_03
transcript.pyannote[287].start 3016.87596875
transcript.pyannote[287].end 3018.56346875
transcript.pyannote[288].speaker SPEAKER_03
transcript.pyannote[288].start 3018.90096875
transcript.pyannote[288].end 3020.36909375
transcript.pyannote[289].speaker SPEAKER_03
transcript.pyannote[289].start 3022.15784375
transcript.pyannote[289].end 3027.00096875
transcript.pyannote[290].speaker SPEAKER_09
transcript.pyannote[290].start 3032.68784375
transcript.pyannote[290].end 3033.14346875
transcript.pyannote[291].speaker SPEAKER_09
transcript.pyannote[291].start 3033.83534375
transcript.pyannote[291].end 3039.08346875
transcript.pyannote[292].speaker SPEAKER_09
transcript.pyannote[292].start 3039.45471875
transcript.pyannote[292].end 3040.43346875
transcript.pyannote[293].speaker SPEAKER_09
transcript.pyannote[293].start 3043.25159375
transcript.pyannote[293].end 3053.07284375
transcript.pyannote[294].speaker SPEAKER_00
transcript.pyannote[294].start 3043.96034375
transcript.pyannote[294].end 3044.02784375
transcript.pyannote[295].speaker SPEAKER_02
transcript.pyannote[295].start 3044.02784375
transcript.pyannote[295].end 3044.55096875
transcript.pyannote[296].speaker SPEAKER_02
transcript.pyannote[296].start 3048.61784375
transcript.pyannote[296].end 3048.63471875
transcript.pyannote[297].speaker SPEAKER_02
transcript.pyannote[297].start 3048.65159375
transcript.pyannote[297].end 3048.70221875
transcript.pyannote[298].speaker SPEAKER_09
transcript.pyannote[298].start 3053.08971875
transcript.pyannote[298].end 3056.88659375
transcript.pyannote[299].speaker SPEAKER_27
transcript.pyannote[299].start 3058.32096875
transcript.pyannote[299].end 3065.05409375
transcript.pyannote[300].speaker SPEAKER_27
transcript.pyannote[300].start 3065.40846875
transcript.pyannote[300].end 3069.71159375
transcript.pyannote[301].speaker SPEAKER_09
transcript.pyannote[301].start 3069.71159375
transcript.pyannote[301].end 3074.77409375
transcript.pyannote[302].speaker SPEAKER_09
transcript.pyannote[302].start 3075.33096875
transcript.pyannote[302].end 3081.18659375
transcript.pyannote[303].speaker SPEAKER_02
transcript.pyannote[303].start 3081.45659375
transcript.pyannote[303].end 3081.47346875
transcript.pyannote[304].speaker SPEAKER_09
transcript.pyannote[304].start 3081.47346875
transcript.pyannote[304].end 3090.41721875
transcript.pyannote[305].speaker SPEAKER_27
transcript.pyannote[305].start 3091.44659375
transcript.pyannote[305].end 3091.80096875
transcript.pyannote[306].speaker SPEAKER_09
transcript.pyannote[306].start 3091.80096875
transcript.pyannote[306].end 3093.08346875
transcript.pyannote[307].speaker SPEAKER_27
transcript.pyannote[307].start 3091.81784375
transcript.pyannote[307].end 3091.83471875
transcript.pyannote[308].speaker SPEAKER_27
transcript.pyannote[308].start 3091.85159375
transcript.pyannote[308].end 3092.07096875
transcript.pyannote[309].speaker SPEAKER_27
transcript.pyannote[309].start 3093.08346875
transcript.pyannote[309].end 3093.18471875
transcript.pyannote[310].speaker SPEAKER_09
transcript.pyannote[310].start 3093.18471875
transcript.pyannote[310].end 3093.26909375
transcript.pyannote[311].speaker SPEAKER_27
transcript.pyannote[311].start 3093.26909375
transcript.pyannote[311].end 3093.35346875
transcript.pyannote[312].speaker SPEAKER_09
transcript.pyannote[312].start 3093.35346875
transcript.pyannote[312].end 3093.40409375
transcript.pyannote[313].speaker SPEAKER_27
transcript.pyannote[313].start 3093.40409375
transcript.pyannote[313].end 3102.97221875
transcript.pyannote[314].speaker SPEAKER_09
transcript.pyannote[314].start 3093.42096875
transcript.pyannote[314].end 3094.88909375
transcript.pyannote[315].speaker SPEAKER_09
transcript.pyannote[315].start 3102.97221875
transcript.pyannote[315].end 3109.24971875
transcript.pyannote[316].speaker SPEAKER_27
transcript.pyannote[316].start 3110.07659375
transcript.pyannote[316].end 3128.35221875
transcript.pyannote[317].speaker SPEAKER_09
transcript.pyannote[317].start 3128.35221875
transcript.pyannote[317].end 3135.86159375
transcript.pyannote[318].speaker SPEAKER_09
transcript.pyannote[318].start 3136.62096875
transcript.pyannote[318].end 3138.37596875
transcript.pyannote[319].speaker SPEAKER_09
transcript.pyannote[319].start 3139.15221875
transcript.pyannote[319].end 3140.82284375
transcript.pyannote[320].speaker SPEAKER_09
transcript.pyannote[320].start 3141.73409375
transcript.pyannote[320].end 3155.18346875
transcript.pyannote[321].speaker SPEAKER_09
transcript.pyannote[321].start 3156.49971875
transcript.pyannote[321].end 3158.76096875
transcript.pyannote[322].speaker SPEAKER_09
transcript.pyannote[322].start 3159.11534375
transcript.pyannote[322].end 3168.02534375
transcript.pyannote[323].speaker SPEAKER_09
transcript.pyannote[323].start 3168.80159375
transcript.pyannote[323].end 3174.40409375
transcript.pyannote[324].speaker SPEAKER_09
transcript.pyannote[324].start 3175.23096875
transcript.pyannote[324].end 3175.28159375
transcript.pyannote[325].speaker SPEAKER_27
transcript.pyannote[325].start 3175.28159375
transcript.pyannote[325].end 3175.80471875
transcript.pyannote[326].speaker SPEAKER_09
transcript.pyannote[326].start 3175.80471875
transcript.pyannote[326].end 3176.14221875
transcript.pyannote[327].speaker SPEAKER_27
transcript.pyannote[327].start 3176.14221875
transcript.pyannote[327].end 3176.20971875
transcript.pyannote[328].speaker SPEAKER_09
transcript.pyannote[328].start 3176.20971875
transcript.pyannote[328].end 3176.46284375
transcript.pyannote[329].speaker SPEAKER_27
transcript.pyannote[329].start 3176.46284375
transcript.pyannote[329].end 3176.51346875
transcript.pyannote[330].speaker SPEAKER_09
transcript.pyannote[330].start 3176.51346875
transcript.pyannote[330].end 3176.54721875
transcript.pyannote[331].speaker SPEAKER_27
transcript.pyannote[331].start 3176.54721875
transcript.pyannote[331].end 3186.13221875
transcript.pyannote[332].speaker SPEAKER_27
transcript.pyannote[332].start 3186.18284375
transcript.pyannote[332].end 3189.64221875
transcript.pyannote[333].speaker SPEAKER_27
transcript.pyannote[333].start 3190.11471875
transcript.pyannote[333].end 3207.15846875
transcript.pyannote[334].speaker SPEAKER_09
transcript.pyannote[334].start 3206.14596875
transcript.pyannote[334].end 3208.74471875
transcript.pyannote[335].speaker SPEAKER_09
transcript.pyannote[335].start 3208.96409375
transcript.pyannote[335].end 3234.83346875
transcript.pyannote[336].speaker SPEAKER_27
transcript.pyannote[336].start 3237.63471875
transcript.pyannote[336].end 3241.34721875
transcript.pyannote[337].speaker SPEAKER_27
transcript.pyannote[337].start 3242.39346875
transcript.pyannote[337].end 3247.84409375
transcript.pyannote[338].speaker SPEAKER_00
transcript.pyannote[338].start 3242.51159375
transcript.pyannote[338].end 3243.50721875
transcript.pyannote[339].speaker SPEAKER_27
transcript.pyannote[339].start 3247.96221875
transcript.pyannote[339].end 3261.58034375
transcript.pyannote[340].speaker SPEAKER_10
transcript.pyannote[340].start 3253.36221875
transcript.pyannote[340].end 3254.03721875
transcript.pyannote[341].speaker SPEAKER_09
transcript.pyannote[341].start 3254.03721875
transcript.pyannote[341].end 3254.25659375
transcript.pyannote[342].speaker SPEAKER_09
transcript.pyannote[342].start 3255.06659375
transcript.pyannote[342].end 3257.96909375
transcript.pyannote[343].speaker SPEAKER_09
transcript.pyannote[343].start 3258.96471875
transcript.pyannote[343].end 3263.16659375
transcript.pyannote[344].speaker SPEAKER_27
transcript.pyannote[344].start 3262.03596875
transcript.pyannote[344].end 3262.10346875
transcript.pyannote[345].speaker SPEAKER_09
transcript.pyannote[345].start 3263.58846875
transcript.pyannote[345].end 3269.74784375
transcript.pyannote[346].speaker SPEAKER_09
transcript.pyannote[346].start 3270.45659375
transcript.pyannote[346].end 3283.24784375
transcript.pyannote[347].speaker SPEAKER_09
transcript.pyannote[347].start 3283.38284375
transcript.pyannote[347].end 3292.32659375
transcript.pyannote[348].speaker SPEAKER_27
transcript.pyannote[348].start 3293.30534375
transcript.pyannote[348].end 3293.65971875
transcript.pyannote[349].speaker SPEAKER_27
transcript.pyannote[349].start 3294.04784375
transcript.pyannote[349].end 3296.00534375
transcript.pyannote[350].speaker SPEAKER_27
transcript.pyannote[350].start 3296.30909375
transcript.pyannote[350].end 3299.86971875
transcript.pyannote[351].speaker SPEAKER_27
transcript.pyannote[351].start 3300.20721875
transcript.pyannote[351].end 3300.42659375
transcript.pyannote[352].speaker SPEAKER_27
transcript.pyannote[352].start 3301.00034375
transcript.pyannote[352].end 3301.35471875
transcript.pyannote[353].speaker SPEAKER_09
transcript.pyannote[353].start 3301.35471875
transcript.pyannote[353].end 3301.37159375
transcript.pyannote[354].speaker SPEAKER_27
transcript.pyannote[354].start 3302.26596875
transcript.pyannote[354].end 3302.97471875
transcript.pyannote[355].speaker SPEAKER_09
transcript.pyannote[355].start 3302.97471875
transcript.pyannote[355].end 3320.55846875
transcript.pyannote[356].speaker SPEAKER_09
transcript.pyannote[356].start 3321.25034375
transcript.pyannote[356].end 3323.52846875
transcript.pyannote[357].speaker SPEAKER_09
transcript.pyannote[357].start 3323.76471875
transcript.pyannote[357].end 3331.64534375
transcript.pyannote[358].speaker SPEAKER_09
transcript.pyannote[358].start 3332.21909375
transcript.pyannote[358].end 3334.32846875
transcript.pyannote[359].speaker SPEAKER_09
transcript.pyannote[359].start 3334.44659375
transcript.pyannote[359].end 3338.24346875
transcript.pyannote[360].speaker SPEAKER_27
transcript.pyannote[360].start 3338.96909375
transcript.pyannote[360].end 3341.46659375
transcript.pyannote[361].speaker SPEAKER_27
transcript.pyannote[361].start 3341.56784375
transcript.pyannote[361].end 3348.52034375
transcript.pyannote[362].speaker SPEAKER_09
transcript.pyannote[362].start 3347.98034375
transcript.pyannote[362].end 3351.30471875
transcript.pyannote[363].speaker SPEAKER_09
transcript.pyannote[363].start 3352.08096875
transcript.pyannote[363].end 3354.00471875
transcript.pyannote[364].speaker SPEAKER_09
transcript.pyannote[364].start 3354.57846875
transcript.pyannote[364].end 3366.22221875
transcript.pyannote[365].speaker SPEAKER_09
transcript.pyannote[365].start 3367.38659375
transcript.pyannote[365].end 3369.66471875
transcript.pyannote[366].speaker SPEAKER_09
transcript.pyannote[366].start 3370.05284375
transcript.pyannote[366].end 3374.54159375
transcript.pyannote[367].speaker SPEAKER_09
transcript.pyannote[367].start 3374.60909375
transcript.pyannote[367].end 3375.75659375
transcript.pyannote[368].speaker SPEAKER_09
transcript.pyannote[368].start 3376.04346875
transcript.pyannote[368].end 3376.80284375
transcript.pyannote[369].speaker SPEAKER_09
transcript.pyannote[369].start 3377.27534375
transcript.pyannote[369].end 3377.91659375
transcript.pyannote[370].speaker SPEAKER_09
transcript.pyannote[370].start 3379.55346875
transcript.pyannote[370].end 3380.46471875
transcript.pyannote[371].speaker SPEAKER_09
transcript.pyannote[371].start 3380.76846875
transcript.pyannote[371].end 3382.54034375
transcript.pyannote[372].speaker SPEAKER_27
transcript.pyannote[372].start 3384.04221875
transcript.pyannote[372].end 3384.43034375
transcript.pyannote[373].speaker SPEAKER_27
transcript.pyannote[373].start 3384.48096875
transcript.pyannote[373].end 3386.77596875
transcript.pyannote[374].speaker SPEAKER_27
transcript.pyannote[374].start 3386.96159375
transcript.pyannote[374].end 3388.76721875
transcript.pyannote[375].speaker SPEAKER_27
transcript.pyannote[375].start 3389.12159375
transcript.pyannote[375].end 3392.39534375
transcript.pyannote[376].speaker SPEAKER_27
transcript.pyannote[376].start 3392.81721875
transcript.pyannote[376].end 3395.58471875
transcript.pyannote[377].speaker SPEAKER_27
transcript.pyannote[377].start 3395.97284375
transcript.pyannote[377].end 3400.52909375
transcript.pyannote[378].speaker SPEAKER_09
transcript.pyannote[378].start 3399.19596875
transcript.pyannote[378].end 3400.96784375
transcript.pyannote[379].speaker SPEAKER_27
transcript.pyannote[379].start 3400.96784375
transcript.pyannote[379].end 3401.33909375
transcript.pyannote[380].speaker SPEAKER_09
transcript.pyannote[380].start 3401.06909375
transcript.pyannote[380].end 3401.32221875
transcript.pyannote[381].speaker SPEAKER_09
transcript.pyannote[381].start 3401.33909375
transcript.pyannote[381].end 3405.37221875
transcript.pyannote[382].speaker SPEAKER_27
transcript.pyannote[382].start 3402.33471875
transcript.pyannote[382].end 3402.43596875
transcript.pyannote[383].speaker SPEAKER_09
transcript.pyannote[383].start 3406.01346875
transcript.pyannote[383].end 3420.32346875
transcript.pyannote[384].speaker SPEAKER_09
transcript.pyannote[384].start 3420.77909375
transcript.pyannote[384].end 3441.01221875
transcript.pyannote[385].speaker SPEAKER_09
transcript.pyannote[385].start 3441.65346875
transcript.pyannote[385].end 3452.47034375
transcript.pyannote[386].speaker SPEAKER_27
transcript.pyannote[386].start 3453.65159375
transcript.pyannote[386].end 3457.04346875
transcript.pyannote[387].speaker SPEAKER_27
transcript.pyannote[387].start 3457.78596875
transcript.pyannote[387].end 3459.74346875
transcript.pyannote[388].speaker SPEAKER_27
transcript.pyannote[388].start 3459.91221875
transcript.pyannote[388].end 3462.59534375
transcript.pyannote[389].speaker SPEAKER_27
transcript.pyannote[389].start 3462.73034375
transcript.pyannote[389].end 3466.99971875
transcript.pyannote[390].speaker SPEAKER_27
transcript.pyannote[390].start 3467.40471875
transcript.pyannote[390].end 3471.42096875
transcript.pyannote[391].speaker SPEAKER_27
transcript.pyannote[391].start 3471.79221875
transcript.pyannote[391].end 3482.71034375
transcript.pyannote[392].speaker SPEAKER_26
transcript.pyannote[392].start 3474.28971875
transcript.pyannote[392].end 3476.02784375
transcript.pyannote[393].speaker SPEAKER_26
transcript.pyannote[393].start 3476.11221875
transcript.pyannote[393].end 3479.57159375
transcript.pyannote[394].speaker SPEAKER_26
transcript.pyannote[394].start 3482.23784375
transcript.pyannote[394].end 3483.03096875
transcript.pyannote[395].speaker SPEAKER_27
transcript.pyannote[395].start 3483.03096875
transcript.pyannote[395].end 3488.36346875
transcript.pyannote[396].speaker SPEAKER_26
transcript.pyannote[396].start 3483.06471875
transcript.pyannote[396].end 3483.57096875
transcript.pyannote[397].speaker SPEAKER_26
transcript.pyannote[397].start 3484.22909375
transcript.pyannote[397].end 3484.24596875
transcript.pyannote[398].speaker SPEAKER_09
transcript.pyannote[398].start 3484.24596875
transcript.pyannote[398].end 3486.70971875
transcript.pyannote[399].speaker SPEAKER_09
transcript.pyannote[399].start 3487.51971875
transcript.pyannote[399].end 3487.67159375
transcript.pyannote[400].speaker SPEAKER_09
transcript.pyannote[400].start 3488.36346875
transcript.pyannote[400].end 3507.19596875
transcript.pyannote[401].speaker SPEAKER_27
transcript.pyannote[401].start 3488.49846875
transcript.pyannote[401].end 3488.98784375
transcript.pyannote[402].speaker SPEAKER_27
transcript.pyannote[402].start 3508.03971875
transcript.pyannote[402].end 3519.59909375
transcript.pyannote[403].speaker SPEAKER_09
transcript.pyannote[403].start 3512.44409375
transcript.pyannote[403].end 3513.42284375
transcript.pyannote[404].speaker SPEAKER_09
transcript.pyannote[404].start 3513.94596875
transcript.pyannote[404].end 3515.19471875
transcript.pyannote[405].speaker SPEAKER_09
transcript.pyannote[405].start 3515.93721875
transcript.pyannote[405].end 3517.20284375
transcript.pyannote[406].speaker SPEAKER_09
transcript.pyannote[406].start 3517.79346875
transcript.pyannote[406].end 3518.73846875
transcript.pyannote[407].speaker SPEAKER_09
transcript.pyannote[407].start 3521.82659375
transcript.pyannote[407].end 3533.58846875
transcript.pyannote[408].speaker SPEAKER_09
transcript.pyannote[408].start 3534.04409375
transcript.pyannote[408].end 3540.16971875
transcript.pyannote[409].speaker SPEAKER_27
transcript.pyannote[409].start 3539.07284375
transcript.pyannote[409].end 3540.92909375
transcript.pyannote[410].speaker SPEAKER_09
transcript.pyannote[410].start 3540.60846875
transcript.pyannote[410].end 3541.65471875
transcript.pyannote[411].speaker SPEAKER_27
transcript.pyannote[411].start 3541.99221875
transcript.pyannote[411].end 3542.31284375
transcript.pyannote[412].speaker SPEAKER_09
transcript.pyannote[412].start 3542.31284375
transcript.pyannote[412].end 3542.83596875
transcript.pyannote[413].speaker SPEAKER_27
transcript.pyannote[413].start 3542.39721875
transcript.pyannote[413].end 3542.46471875
transcript.pyannote[414].speaker SPEAKER_27
transcript.pyannote[414].start 3543.24096875
transcript.pyannote[414].end 3543.39284375
transcript.pyannote[415].speaker SPEAKER_09
transcript.pyannote[415].start 3544.10159375
transcript.pyannote[415].end 3548.84346875
transcript.pyannote[416].speaker SPEAKER_09
transcript.pyannote[416].start 3549.11346875
transcript.pyannote[416].end 3559.84596875
transcript.pyannote[417].speaker SPEAKER_02
transcript.pyannote[417].start 3560.85846875
transcript.pyannote[417].end 3561.43221875
transcript.pyannote[418].speaker SPEAKER_09
transcript.pyannote[418].start 3561.29721875
transcript.pyannote[418].end 3567.01784375
transcript.pyannote[419].speaker SPEAKER_27
transcript.pyannote[419].start 3561.43221875
transcript.pyannote[419].end 3561.61784375
transcript.pyannote[420].speaker SPEAKER_27
transcript.pyannote[420].start 3565.04346875
transcript.pyannote[420].end 3589.03971875
transcript.pyannote[421].speaker SPEAKER_09
transcript.pyannote[421].start 3588.80346875
transcript.pyannote[421].end 3606.77534375
transcript.pyannote[422].speaker SPEAKER_27
transcript.pyannote[422].start 3605.29034375
transcript.pyannote[422].end 3613.17096875
transcript.pyannote[423].speaker SPEAKER_09
transcript.pyannote[423].start 3610.50471875
transcript.pyannote[423].end 3610.53846875
transcript.pyannote[424].speaker SPEAKER_27
transcript.pyannote[424].start 3613.54221875
transcript.pyannote[424].end 3621.96284375
transcript.pyannote[425].speaker SPEAKER_09
transcript.pyannote[425].start 3617.71034375
transcript.pyannote[425].end 3617.79471875
transcript.pyannote[426].speaker SPEAKER_09
transcript.pyannote[426].start 3618.01409375
transcript.pyannote[426].end 3618.58784375
transcript.pyannote[427].speaker SPEAKER_02
transcript.pyannote[427].start 3618.58784375
transcript.pyannote[427].end 3618.60471875
transcript.pyannote[428].speaker SPEAKER_09
transcript.pyannote[428].start 3621.70971875
transcript.pyannote[428].end 3621.91221875
transcript.pyannote[429].speaker SPEAKER_09
transcript.pyannote[429].start 3621.96284375
transcript.pyannote[429].end 3630.07971875
transcript.pyannote[430].speaker SPEAKER_09
transcript.pyannote[430].start 3630.19784375
transcript.pyannote[430].end 3632.07096875
transcript.pyannote[431].speaker SPEAKER_03
transcript.pyannote[431].start 3630.41721875
transcript.pyannote[431].end 3630.72096875
transcript.pyannote[432].speaker SPEAKER_03
transcript.pyannote[432].start 3630.88971875
transcript.pyannote[432].end 3632.50971875
transcript.pyannote[433].speaker SPEAKER_03
transcript.pyannote[433].start 3633.79221875
transcript.pyannote[433].end 3638.41596875
transcript.pyannote[434].speaker SPEAKER_25
transcript.pyannote[434].start 3656.33721875
transcript.pyannote[434].end 3657.21471875
transcript.pyannote[435].speaker SPEAKER_03
transcript.pyannote[435].start 3657.73784375
transcript.pyannote[435].end 3658.63221875
transcript.pyannote[436].speaker SPEAKER_25
transcript.pyannote[436].start 3662.58096875
transcript.pyannote[436].end 3663.34034375
transcript.pyannote[437].speaker SPEAKER_25
transcript.pyannote[437].start 3664.13346875
transcript.pyannote[437].end 3664.84221875
transcript.pyannote[438].speaker SPEAKER_25
transcript.pyannote[438].start 3664.99409375
transcript.pyannote[438].end 3665.56784375
transcript.pyannote[439].speaker SPEAKER_25
transcript.pyannote[439].start 3667.72784375
transcript.pyannote[439].end 3676.16534375
transcript.pyannote[440].speaker SPEAKER_25
transcript.pyannote[440].start 3676.31721875
transcript.pyannote[440].end 3681.10971875
transcript.pyannote[441].speaker SPEAKER_25
transcript.pyannote[441].start 3681.80159375
transcript.pyannote[441].end 3682.34159375
transcript.pyannote[442].speaker SPEAKER_25
transcript.pyannote[442].start 3682.83096875
transcript.pyannote[442].end 3683.69159375
transcript.pyannote[443].speaker SPEAKER_25
transcript.pyannote[443].start 3684.29909375
transcript.pyannote[443].end 3686.08784375
transcript.pyannote[444].speaker SPEAKER_25
transcript.pyannote[444].start 3686.79659375
transcript.pyannote[444].end 3687.97784375
transcript.pyannote[445].speaker SPEAKER_27
transcript.pyannote[445].start 3687.97784375
transcript.pyannote[445].end 3691.89284375
transcript.pyannote[446].speaker SPEAKER_27
transcript.pyannote[446].start 3692.51721875
transcript.pyannote[446].end 3706.42221875
transcript.pyannote[447].speaker SPEAKER_00
transcript.pyannote[447].start 3702.40596875
transcript.pyannote[447].end 3703.04721875
transcript.pyannote[448].speaker SPEAKER_27
transcript.pyannote[448].start 3706.97909375
transcript.pyannote[448].end 3712.85159375
transcript.pyannote[449].speaker SPEAKER_02
transcript.pyannote[449].start 3712.85159375
transcript.pyannote[449].end 3713.54346875
transcript.pyannote[450].speaker SPEAKER_02
transcript.pyannote[450].start 3713.62784375
transcript.pyannote[450].end 3713.64471875
transcript.pyannote[451].speaker SPEAKER_27
transcript.pyannote[451].start 3713.64471875
transcript.pyannote[451].end 3719.83784375
transcript.pyannote[452].speaker SPEAKER_28
transcript.pyannote[452].start 3719.83784375
transcript.pyannote[452].end 3720.12471875
transcript.pyannote[453].speaker SPEAKER_25
transcript.pyannote[453].start 3720.12471875
transcript.pyannote[453].end 3720.15846875
transcript.pyannote[454].speaker SPEAKER_27
transcript.pyannote[454].start 3720.12471875
transcript.pyannote[454].end 3725.45721875
transcript.pyannote[455].speaker SPEAKER_25
transcript.pyannote[455].start 3722.68971875
transcript.pyannote[455].end 3728.07284375
transcript.pyannote[456].speaker SPEAKER_27
transcript.pyannote[456].start 3727.88721875
transcript.pyannote[456].end 3729.55784375
transcript.pyannote[457].speaker SPEAKER_25
transcript.pyannote[457].start 3729.55784375
transcript.pyannote[457].end 3729.97971875
transcript.pyannote[458].speaker SPEAKER_27
transcript.pyannote[458].start 3729.97971875
transcript.pyannote[458].end 3737.55659375
transcript.pyannote[459].speaker SPEAKER_25
transcript.pyannote[459].start 3737.55659375
transcript.pyannote[459].end 3741.94409375
transcript.pyannote[460].speaker SPEAKER_27
transcript.pyannote[460].start 3740.64471875
transcript.pyannote[460].end 3744.49221875
transcript.pyannote[461].speaker SPEAKER_25
transcript.pyannote[461].start 3743.12534375
transcript.pyannote[461].end 3743.29409375
transcript.pyannote[462].speaker SPEAKER_25
transcript.pyannote[462].start 3744.49221875
transcript.pyannote[462].end 3746.95596875
transcript.pyannote[463].speaker SPEAKER_27
transcript.pyannote[463].start 3744.98159375
transcript.pyannote[463].end 3749.16659375
transcript.pyannote[464].speaker SPEAKER_25
transcript.pyannote[464].start 3748.62659375
transcript.pyannote[464].end 3757.38471875
transcript.pyannote[465].speaker SPEAKER_25
transcript.pyannote[465].start 3758.09346875
transcript.pyannote[465].end 3766.04159375
transcript.pyannote[466].speaker SPEAKER_25
transcript.pyannote[466].start 3766.41284375
transcript.pyannote[466].end 3770.24346875
transcript.pyannote[467].speaker SPEAKER_25
transcript.pyannote[467].start 3772.21784375
transcript.pyannote[467].end 3774.19221875
transcript.pyannote[468].speaker SPEAKER_27
transcript.pyannote[468].start 3774.19221875
transcript.pyannote[468].end 3774.51284375
transcript.pyannote[469].speaker SPEAKER_27
transcript.pyannote[469].start 3774.76596875
transcript.pyannote[469].end 3775.28909375
transcript.pyannote[470].speaker SPEAKER_27
transcript.pyannote[470].start 3775.86284375
transcript.pyannote[470].end 3780.04784375
transcript.pyannote[471].speaker SPEAKER_25
transcript.pyannote[471].start 3780.04784375
transcript.pyannote[471].end 3780.08159375
transcript.pyannote[472].speaker SPEAKER_02
transcript.pyannote[472].start 3780.08159375
transcript.pyannote[472].end 3780.38534375
transcript.pyannote[473].speaker SPEAKER_27
transcript.pyannote[473].start 3780.60471875
transcript.pyannote[473].end 3789.12659375
transcript.pyannote[474].speaker SPEAKER_25
transcript.pyannote[474].start 3787.37159375
transcript.pyannote[474].end 3799.65659375
transcript.pyannote[475].speaker SPEAKER_27
transcript.pyannote[475].start 3793.34534375
transcript.pyannote[475].end 3795.53909375
transcript.pyannote[476].speaker SPEAKER_27
transcript.pyannote[476].start 3796.58534375
transcript.pyannote[476].end 3796.88909375
transcript.pyannote[477].speaker SPEAKER_27
transcript.pyannote[477].start 3797.61471875
transcript.pyannote[477].end 3799.62284375
transcript.pyannote[478].speaker SPEAKER_27
transcript.pyannote[478].start 3799.65659375
transcript.pyannote[478].end 3800.02784375
transcript.pyannote[479].speaker SPEAKER_25
transcript.pyannote[479].start 3800.02784375
transcript.pyannote[479].end 3815.02971875
transcript.pyannote[480].speaker SPEAKER_27
transcript.pyannote[480].start 3800.95596875
transcript.pyannote[480].end 3801.19221875
transcript.pyannote[481].speaker SPEAKER_27
transcript.pyannote[481].start 3802.20471875
transcript.pyannote[481].end 3803.09909375
transcript.pyannote[482].speaker SPEAKER_25
transcript.pyannote[482].start 3815.48534375
transcript.pyannote[482].end 3816.04221875
transcript.pyannote[483].speaker SPEAKER_25
transcript.pyannote[483].start 3816.48096875
transcript.pyannote[483].end 3826.97721875
transcript.pyannote[484].speaker SPEAKER_27
transcript.pyannote[484].start 3823.60221875
transcript.pyannote[484].end 3824.27721875
transcript.pyannote[485].speaker SPEAKER_27
transcript.pyannote[485].start 3824.58096875
transcript.pyannote[485].end 3826.89284375
transcript.pyannote[486].speaker SPEAKER_25
transcript.pyannote[486].start 3828.19221875
transcript.pyannote[486].end 3840.96659375
transcript.pyannote[487].speaker SPEAKER_27
transcript.pyannote[487].start 3842.51909375
transcript.pyannote[487].end 3842.83971875
transcript.pyannote[488].speaker SPEAKER_25
transcript.pyannote[488].start 3843.14346875
transcript.pyannote[488].end 3845.40471875
transcript.pyannote[489].speaker SPEAKER_27
transcript.pyannote[489].start 3843.59909375
transcript.pyannote[489].end 3846.36659375
transcript.pyannote[490].speaker SPEAKER_25
transcript.pyannote[490].start 3846.36659375
transcript.pyannote[490].end 3864.67596875
transcript.pyannote[491].speaker SPEAKER_27
transcript.pyannote[491].start 3859.05659375
transcript.pyannote[491].end 3859.17471875
transcript.pyannote[492].speaker SPEAKER_27
transcript.pyannote[492].start 3861.60471875
transcript.pyannote[492].end 3862.07721875
transcript.pyannote[493].speaker SPEAKER_27
transcript.pyannote[493].start 3863.62971875
transcript.pyannote[493].end 3864.08534375
transcript.pyannote[494].speaker SPEAKER_25
transcript.pyannote[494].start 3865.63784375
transcript.pyannote[494].end 3895.20284375
transcript.pyannote[495].speaker SPEAKER_02
transcript.pyannote[495].start 3893.53221875
transcript.pyannote[495].end 3894.08909375
transcript.pyannote[496].speaker SPEAKER_02
transcript.pyannote[496].start 3895.01721875
transcript.pyannote[496].end 3895.40534375
transcript.pyannote[497].speaker SPEAKER_25
transcript.pyannote[497].start 3895.28721875
transcript.pyannote[497].end 3909.02346875
transcript.pyannote[498].speaker SPEAKER_25
transcript.pyannote[498].start 3909.79971875
transcript.pyannote[498].end 3914.67659375
transcript.pyannote[499].speaker SPEAKER_25
transcript.pyannote[499].start 3915.16596875
transcript.pyannote[499].end 3919.94159375
transcript.pyannote[500].speaker SPEAKER_25
transcript.pyannote[500].start 3920.32971875
transcript.pyannote[500].end 3925.32471875
transcript.pyannote[501].speaker SPEAKER_25
transcript.pyannote[501].start 3925.61159375
transcript.pyannote[501].end 3926.43846875
transcript.pyannote[502].speaker SPEAKER_25
transcript.pyannote[502].start 3926.77596875
transcript.pyannote[502].end 3928.64909375
transcript.pyannote[503].speaker SPEAKER_25
transcript.pyannote[503].start 3928.76721875
transcript.pyannote[503].end 3929.99909375
transcript.pyannote[504].speaker SPEAKER_25
transcript.pyannote[504].start 3930.75846875
transcript.pyannote[504].end 3933.69471875
transcript.pyannote[505].speaker SPEAKER_25
transcript.pyannote[505].start 3934.01534375
transcript.pyannote[505].end 3936.12471875
transcript.pyannote[506].speaker SPEAKER_25
transcript.pyannote[506].start 3936.32721875
transcript.pyannote[506].end 3939.85409375
transcript.pyannote[507].speaker SPEAKER_25
transcript.pyannote[507].start 3940.27596875
transcript.pyannote[507].end 3944.96721875
transcript.pyannote[508].speaker SPEAKER_27
transcript.pyannote[508].start 3942.92534375
transcript.pyannote[508].end 3942.94221875
transcript.pyannote[509].speaker SPEAKER_02
transcript.pyannote[509].start 3942.94221875
transcript.pyannote[509].end 3943.27971875
transcript.pyannote[510].speaker SPEAKER_27
transcript.pyannote[510].start 3943.27971875
transcript.pyannote[510].end 3943.33034375
transcript.pyannote[511].speaker SPEAKER_27
transcript.pyannote[511].start 3944.96721875
transcript.pyannote[511].end 3945.62534375
transcript.pyannote[512].speaker SPEAKER_25
transcript.pyannote[512].start 3945.62534375
transcript.pyannote[512].end 3945.67596875
transcript.pyannote[513].speaker SPEAKER_27
transcript.pyannote[513].start 3945.67596875
transcript.pyannote[513].end 3946.45221875
transcript.pyannote[514].speaker SPEAKER_25
transcript.pyannote[514].start 3946.78971875
transcript.pyannote[514].end 3946.80659375
transcript.pyannote[515].speaker SPEAKER_27
transcript.pyannote[515].start 3946.80659375
transcript.pyannote[515].end 3951.95346875
transcript.pyannote[516].speaker SPEAKER_27
transcript.pyannote[516].start 3952.12221875
transcript.pyannote[516].end 3953.35409375
transcript.pyannote[517].speaker SPEAKER_27
transcript.pyannote[517].start 3953.43846875
transcript.pyannote[517].end 3960.79596875
transcript.pyannote[518].speaker SPEAKER_27
transcript.pyannote[518].start 3961.04909375
transcript.pyannote[518].end 3961.72409375
transcript.pyannote[519].speaker SPEAKER_27
transcript.pyannote[519].start 3962.23034375
transcript.pyannote[519].end 3965.31846875
transcript.pyannote[520].speaker SPEAKER_27
transcript.pyannote[520].start 3965.85846875
transcript.pyannote[520].end 3967.32659375
transcript.pyannote[521].speaker SPEAKER_25
transcript.pyannote[521].start 3965.92596875
transcript.pyannote[521].end 3969.45284375
transcript.pyannote[522].speaker SPEAKER_27
transcript.pyannote[522].start 3967.93409375
transcript.pyannote[522].end 3968.33909375
transcript.pyannote[523].speaker SPEAKER_27
transcript.pyannote[523].start 3968.91284375
transcript.pyannote[523].end 3972.03471875
transcript.pyannote[524].speaker SPEAKER_25
transcript.pyannote[524].start 3972.03471875
transcript.pyannote[524].end 3972.28784375
transcript.pyannote[525].speaker SPEAKER_27
transcript.pyannote[525].start 3972.28784375
transcript.pyannote[525].end 3972.94596875
transcript.pyannote[526].speaker SPEAKER_25
transcript.pyannote[526].start 3972.94596875
transcript.pyannote[526].end 3975.42659375
transcript.pyannote[527].speaker SPEAKER_27
transcript.pyannote[527].start 3973.65471875
transcript.pyannote[527].end 3974.11034375
transcript.pyannote[528].speaker SPEAKER_27
transcript.pyannote[528].start 3975.42659375
transcript.pyannote[528].end 3975.52784375
transcript.pyannote[529].speaker SPEAKER_25
transcript.pyannote[529].start 3975.52784375
transcript.pyannote[529].end 3976.18596875
transcript.pyannote[530].speaker SPEAKER_27
transcript.pyannote[530].start 3975.54471875
transcript.pyannote[530].end 3979.79721875
transcript.pyannote[531].speaker SPEAKER_25
transcript.pyannote[531].start 3979.49346875
transcript.pyannote[531].end 3979.54409375
transcript.pyannote[532].speaker SPEAKER_02
transcript.pyannote[532].start 3979.54409375
transcript.pyannote[532].end 3979.59471875
transcript.pyannote[533].speaker SPEAKER_25
transcript.pyannote[533].start 3979.59471875
transcript.pyannote[533].end 3979.61159375
transcript.pyannote[534].speaker SPEAKER_02
transcript.pyannote[534].start 3979.61159375
transcript.pyannote[534].end 3980.18534375
transcript.pyannote[535].speaker SPEAKER_25
transcript.pyannote[535].start 3979.79721875
transcript.pyannote[535].end 3979.81409375
transcript.pyannote[536].speaker SPEAKER_27
transcript.pyannote[536].start 3980.13471875
transcript.pyannote[536].end 3983.03721875
transcript.pyannote[537].speaker SPEAKER_25
transcript.pyannote[537].start 3983.03721875
transcript.pyannote[537].end 3998.96721875
transcript.pyannote[538].speaker SPEAKER_27
transcript.pyannote[538].start 3983.29034375
transcript.pyannote[538].end 3983.30721875
transcript.pyannote[539].speaker SPEAKER_02
transcript.pyannote[539].start 3983.30721875
transcript.pyannote[539].end 3983.99909375
transcript.pyannote[540].speaker SPEAKER_27
transcript.pyannote[540].start 3995.38971875
transcript.pyannote[540].end 3996.79034375
transcript.pyannote[541].speaker SPEAKER_27
transcript.pyannote[541].start 3998.96721875
transcript.pyannote[541].end 4000.03034375
transcript.pyannote[542].speaker SPEAKER_25
transcript.pyannote[542].start 3999.42284375
transcript.pyannote[542].end 4000.13159375
transcript.pyannote[543].speaker SPEAKER_27
transcript.pyannote[543].start 4000.13159375
transcript.pyannote[543].end 4001.49846875
transcript.pyannote[544].speaker SPEAKER_25
transcript.pyannote[544].start 4001.49846875
transcript.pyannote[544].end 4002.37596875
transcript.pyannote[545].speaker SPEAKER_27
transcript.pyannote[545].start 4001.63346875
transcript.pyannote[545].end 4002.35909375
transcript.pyannote[546].speaker SPEAKER_25
transcript.pyannote[546].start 4003.72596875
transcript.pyannote[546].end 4008.94034375
transcript.pyannote[547].speaker SPEAKER_25
transcript.pyannote[547].start 4009.63221875
transcript.pyannote[547].end 4016.80409375
transcript.pyannote[548].speaker SPEAKER_25
transcript.pyannote[548].start 4017.25971875
transcript.pyannote[548].end 4026.40596875
transcript.pyannote[549].speaker SPEAKER_25
transcript.pyannote[549].start 4026.74346875
transcript.pyannote[549].end 4039.02846875
transcript.pyannote[550].speaker SPEAKER_27
transcript.pyannote[550].start 4039.02846875
transcript.pyannote[550].end 4039.53471875
transcript.pyannote[551].speaker SPEAKER_25
transcript.pyannote[551].start 4039.53471875
transcript.pyannote[551].end 4039.97346875
transcript.pyannote[552].speaker SPEAKER_02
transcript.pyannote[552].start 4039.80471875
transcript.pyannote[552].end 4040.02409375
transcript.pyannote[553].speaker SPEAKER_27
transcript.pyannote[553].start 4039.97346875
transcript.pyannote[553].end 4049.37284375
transcript.pyannote[554].speaker SPEAKER_25
transcript.pyannote[554].start 4057.65846875
transcript.pyannote[554].end 4062.34971875
transcript.pyannote[555].speaker SPEAKER_02
transcript.pyannote[555].start 4062.33284375
transcript.pyannote[555].end 4062.68721875
transcript.pyannote[556].speaker SPEAKER_25
transcript.pyannote[556].start 4062.68721875
transcript.pyannote[556].end 4063.37909375
transcript.pyannote[557].speaker SPEAKER_25
transcript.pyannote[557].start 4063.54784375
transcript.pyannote[557].end 4067.80034375
transcript.pyannote[558].speaker SPEAKER_25
transcript.pyannote[558].start 4067.95221875
transcript.pyannote[558].end 4079.61284375
transcript.pyannote[559].speaker SPEAKER_25
transcript.pyannote[559].start 4079.74784375
transcript.pyannote[559].end 4087.05471875
transcript.pyannote[560].speaker SPEAKER_25
transcript.pyannote[560].start 4087.20659375
transcript.pyannote[560].end 4088.74221875
transcript.pyannote[561].speaker SPEAKER_25
transcript.pyannote[561].start 4088.92784375
transcript.pyannote[561].end 4102.10721875
transcript.pyannote[562].speaker SPEAKER_25
transcript.pyannote[562].start 4102.47846875
transcript.pyannote[562].end 4110.29159375
transcript.pyannote[563].speaker SPEAKER_25
transcript.pyannote[563].start 4110.67971875
transcript.pyannote[563].end 4116.78846875
transcript.pyannote[564].speaker SPEAKER_27
transcript.pyannote[564].start 4116.90659375
transcript.pyannote[564].end 4127.38596875
transcript.pyannote[565].speaker SPEAKER_25
transcript.pyannote[565].start 4127.38596875
transcript.pyannote[565].end 4127.41971875
transcript.pyannote[566].speaker SPEAKER_02
transcript.pyannote[566].start 4127.41971875
transcript.pyannote[566].end 4127.60534375
transcript.pyannote[567].speaker SPEAKER_27
transcript.pyannote[567].start 4127.60534375
transcript.pyannote[567].end 4128.02721875
transcript.pyannote[568].speaker SPEAKER_25
transcript.pyannote[568].start 4128.02721875
transcript.pyannote[568].end 4132.41471875
transcript.pyannote[569].speaker SPEAKER_27
transcript.pyannote[569].start 4129.54596875
transcript.pyannote[569].end 4129.81596875
transcript.pyannote[570].speaker SPEAKER_25
transcript.pyannote[570].start 4132.85346875
transcript.pyannote[570].end 4137.71346875
transcript.pyannote[571].speaker SPEAKER_27
transcript.pyannote[571].start 4137.15659375
transcript.pyannote[571].end 4137.66284375
transcript.pyannote[572].speaker SPEAKER_27
transcript.pyannote[572].start 4137.71346875
transcript.pyannote[572].end 4137.79784375
transcript.pyannote[573].speaker SPEAKER_25
transcript.pyannote[573].start 4137.79784375
transcript.pyannote[573].end 4137.83159375
transcript.pyannote[574].speaker SPEAKER_27
transcript.pyannote[574].start 4137.83159375
transcript.pyannote[574].end 4137.91596875
transcript.pyannote[575].speaker SPEAKER_25
transcript.pyannote[575].start 4137.91596875
transcript.pyannote[575].end 4137.96659375
transcript.pyannote[576].speaker SPEAKER_27
transcript.pyannote[576].start 4137.96659375
transcript.pyannote[576].end 4138.40534375
transcript.pyannote[577].speaker SPEAKER_25
transcript.pyannote[577].start 4138.40534375
transcript.pyannote[577].end 4138.57409375
transcript.pyannote[578].speaker SPEAKER_27
transcript.pyannote[578].start 4138.57409375
transcript.pyannote[578].end 4139.38409375
transcript.pyannote[579].speaker SPEAKER_25
transcript.pyannote[579].start 4138.82721875
transcript.pyannote[579].end 4139.26596875
transcript.pyannote[580].speaker SPEAKER_25
transcript.pyannote[580].start 4139.38409375
transcript.pyannote[580].end 4139.97471875
transcript.pyannote[581].speaker SPEAKER_27
transcript.pyannote[581].start 4139.97471875
transcript.pyannote[581].end 4145.72909375
transcript.pyannote[582].speaker SPEAKER_25
transcript.pyannote[582].start 4142.30346875
transcript.pyannote[582].end 4142.67471875
transcript.pyannote[583].speaker SPEAKER_25
transcript.pyannote[583].start 4145.05409375
transcript.pyannote[583].end 4145.35784375
transcript.pyannote[584].speaker SPEAKER_27
transcript.pyannote[584].start 4145.98221875
transcript.pyannote[584].end 4149.01971875
transcript.pyannote[585].speaker SPEAKER_25
transcript.pyannote[585].start 4146.18471875
transcript.pyannote[585].end 4148.07471875
transcript.pyannote[586].speaker SPEAKER_25
transcript.pyannote[586].start 4148.24346875
transcript.pyannote[586].end 4155.19596875
transcript.pyannote[587].speaker SPEAKER_27
transcript.pyannote[587].start 4151.38221875
transcript.pyannote[587].end 4153.77846875
transcript.pyannote[588].speaker SPEAKER_27
transcript.pyannote[588].start 4154.63909375
transcript.pyannote[588].end 4159.88721875
transcript.pyannote[589].speaker SPEAKER_25
transcript.pyannote[589].start 4157.17034375
transcript.pyannote[589].end 4157.33909375
transcript.pyannote[590].speaker SPEAKER_25
transcript.pyannote[590].start 4159.88721875
transcript.pyannote[590].end 4162.78971875
transcript.pyannote[591].speaker SPEAKER_27
transcript.pyannote[591].start 4160.84909375
transcript.pyannote[591].end 4161.11909375
transcript.pyannote[592].speaker SPEAKER_27
transcript.pyannote[592].start 4161.86159375
transcript.pyannote[592].end 4161.97971875
transcript.pyannote[593].speaker SPEAKER_27
transcript.pyannote[593].start 4162.09784375
transcript.pyannote[593].end 4166.46846875
transcript.pyannote[594].speaker SPEAKER_25
transcript.pyannote[594].start 4164.05534375
transcript.pyannote[594].end 4164.98346875
transcript.pyannote[595].speaker SPEAKER_25
transcript.pyannote[595].start 4165.33784375
transcript.pyannote[595].end 4174.65284375
transcript.pyannote[596].speaker SPEAKER_27
transcript.pyannote[596].start 4170.53534375
transcript.pyannote[596].end 4170.94034375
transcript.pyannote[597].speaker SPEAKER_27
transcript.pyannote[597].start 4172.98221875
transcript.pyannote[597].end 4173.16784375
transcript.pyannote[598].speaker SPEAKER_03
transcript.pyannote[598].start 4174.65284375
transcript.pyannote[598].end 4175.07471875
transcript.pyannote[599].speaker SPEAKER_03
transcript.pyannote[599].start 4177.06596875
transcript.pyannote[599].end 4178.82096875
transcript.pyannote[600].speaker SPEAKER_03
transcript.pyannote[600].start 4179.25971875
transcript.pyannote[600].end 4180.22159375
transcript.pyannote[601].speaker SPEAKER_03
transcript.pyannote[601].start 4180.44096875
transcript.pyannote[601].end 4181.87534375
transcript.pyannote[602].speaker SPEAKER_18
transcript.pyannote[602].start 4192.54034375
transcript.pyannote[602].end 4193.99159375
transcript.pyannote[603].speaker SPEAKER_03
transcript.pyannote[603].start 4194.12659375
transcript.pyannote[603].end 4194.93659375
transcript.pyannote[604].speaker SPEAKER_18
transcript.pyannote[604].start 4198.71659375
transcript.pyannote[604].end 4201.45034375
transcript.pyannote[605].speaker SPEAKER_18
transcript.pyannote[605].start 4201.75409375
transcript.pyannote[605].end 4206.93471875
transcript.pyannote[606].speaker SPEAKER_02
transcript.pyannote[606].start 4206.93471875
transcript.pyannote[606].end 4207.35659375
transcript.pyannote[607].speaker SPEAKER_18
transcript.pyannote[607].start 4207.35659375
transcript.pyannote[607].end 4209.51659375
transcript.pyannote[608].speaker SPEAKER_18
transcript.pyannote[608].start 4210.12409375
transcript.pyannote[608].end 4214.47784375
transcript.pyannote[609].speaker SPEAKER_18
transcript.pyannote[609].start 4214.89971875
transcript.pyannote[609].end 4217.71784375
transcript.pyannote[610].speaker SPEAKER_18
transcript.pyannote[610].start 4218.15659375
transcript.pyannote[610].end 4222.56096875
transcript.pyannote[611].speaker SPEAKER_18
transcript.pyannote[611].start 4223.35409375
transcript.pyannote[611].end 4224.34971875
transcript.pyannote[612].speaker SPEAKER_18
transcript.pyannote[612].start 4224.87284375
transcript.pyannote[612].end 4225.56471875
transcript.pyannote[613].speaker SPEAKER_18
transcript.pyannote[613].start 4225.90221875
transcript.pyannote[613].end 4227.11721875
transcript.pyannote[614].speaker SPEAKER_27
transcript.pyannote[614].start 4227.75846875
transcript.pyannote[614].end 4228.97346875
transcript.pyannote[615].speaker SPEAKER_27
transcript.pyannote[615].start 4229.29409375
transcript.pyannote[615].end 4229.54721875
transcript.pyannote[616].speaker SPEAKER_27
transcript.pyannote[616].start 4229.71596875
transcript.pyannote[616].end 4251.99096875
transcript.pyannote[617].speaker SPEAKER_18
transcript.pyannote[617].start 4232.61846875
transcript.pyannote[617].end 4232.95596875
transcript.pyannote[618].speaker SPEAKER_18
transcript.pyannote[618].start 4251.99096875
transcript.pyannote[618].end 4254.38721875
transcript.pyannote[619].speaker SPEAKER_27
transcript.pyannote[619].start 4254.65721875
transcript.pyannote[619].end 4266.30096875
transcript.pyannote[620].speaker SPEAKER_27
transcript.pyannote[620].start 4266.82409375
transcript.pyannote[620].end 4269.23721875
transcript.pyannote[621].speaker SPEAKER_27
transcript.pyannote[621].start 4269.81096875
transcript.pyannote[621].end 4272.73034375
transcript.pyannote[622].speaker SPEAKER_18
transcript.pyannote[622].start 4272.73034375
transcript.pyannote[622].end 4274.70471875
transcript.pyannote[623].speaker SPEAKER_27
transcript.pyannote[623].start 4272.74721875
transcript.pyannote[623].end 4273.27034375
transcript.pyannote[624].speaker SPEAKER_27
transcript.pyannote[624].start 4274.26596875
transcript.pyannote[624].end 4275.78471875
transcript.pyannote[625].speaker SPEAKER_27
transcript.pyannote[625].start 4276.00409375
transcript.pyannote[625].end 4286.51721875
transcript.pyannote[626].speaker SPEAKER_18
transcript.pyannote[626].start 4276.22346875
transcript.pyannote[626].end 4278.36659375
transcript.pyannote[627].speaker SPEAKER_18
transcript.pyannote[627].start 4283.09159375
transcript.pyannote[627].end 4283.73284375
transcript.pyannote[628].speaker SPEAKER_18
transcript.pyannote[628].start 4284.18846875
transcript.pyannote[628].end 4286.19659375
transcript.pyannote[629].speaker SPEAKER_18
transcript.pyannote[629].start 4286.51721875
transcript.pyannote[629].end 4287.34409375
transcript.pyannote[630].speaker SPEAKER_27
transcript.pyannote[630].start 4287.91784375
transcript.pyannote[630].end 4293.46971875
transcript.pyannote[631].speaker SPEAKER_27
transcript.pyannote[631].start 4293.90846875
transcript.pyannote[631].end 4295.20784375
transcript.pyannote[632].speaker SPEAKER_18
transcript.pyannote[632].start 4294.12784375
transcript.pyannote[632].end 4302.46409375
transcript.pyannote[633].speaker SPEAKER_27
transcript.pyannote[633].start 4297.58721875
transcript.pyannote[633].end 4297.90784375
transcript.pyannote[634].speaker SPEAKER_27
transcript.pyannote[634].start 4298.38034375
transcript.pyannote[634].end 4298.90346875
transcript.pyannote[635].speaker SPEAKER_27
transcript.pyannote[635].start 4303.20659375
transcript.pyannote[635].end 4312.87596875
transcript.pyannote[636].speaker SPEAKER_18
transcript.pyannote[636].start 4312.16721875
transcript.pyannote[636].end 4316.90909375
transcript.pyannote[637].speaker SPEAKER_27
transcript.pyannote[637].start 4313.98971875
transcript.pyannote[637].end 4314.29346875
transcript.pyannote[638].speaker SPEAKER_18
transcript.pyannote[638].start 4317.61784375
transcript.pyannote[638].end 4326.03846875
transcript.pyannote[639].speaker SPEAKER_27
transcript.pyannote[639].start 4317.82034375
transcript.pyannote[639].end 4318.22534375
transcript.pyannote[640].speaker SPEAKER_27
transcript.pyannote[640].start 4318.83284375
transcript.pyannote[640].end 4319.47409375
transcript.pyannote[641].speaker SPEAKER_18
transcript.pyannote[641].start 4326.12284375
transcript.pyannote[641].end 4331.05034375
transcript.pyannote[642].speaker SPEAKER_27
transcript.pyannote[642].start 4331.33721875
transcript.pyannote[642].end 4331.42159375
transcript.pyannote[643].speaker SPEAKER_18
transcript.pyannote[643].start 4331.42159375
transcript.pyannote[643].end 4331.52284375
transcript.pyannote[644].speaker SPEAKER_27
transcript.pyannote[644].start 4331.52284375
transcript.pyannote[644].end 4331.62409375
transcript.pyannote[645].speaker SPEAKER_18
transcript.pyannote[645].start 4331.62409375
transcript.pyannote[645].end 4331.65784375
transcript.pyannote[646].speaker SPEAKER_18
transcript.pyannote[646].start 4332.61971875
transcript.pyannote[646].end 4332.88971875
transcript.pyannote[647].speaker SPEAKER_18
transcript.pyannote[647].start 4333.24409375
transcript.pyannote[647].end 4335.21846875
transcript.pyannote[648].speaker SPEAKER_18
transcript.pyannote[648].start 4335.97784375
transcript.pyannote[648].end 4342.54221875
transcript.pyannote[649].speaker SPEAKER_18
transcript.pyannote[649].start 4343.30159375
transcript.pyannote[649].end 4351.43534375
transcript.pyannote[650].speaker SPEAKER_02
transcript.pyannote[650].start 4345.09034375
transcript.pyannote[650].end 4345.47846875
transcript.pyannote[651].speaker SPEAKER_27
transcript.pyannote[651].start 4349.62971875
transcript.pyannote[651].end 4349.74784375
transcript.pyannote[652].speaker SPEAKER_27
transcript.pyannote[652].start 4351.94159375
transcript.pyannote[652].end 4357.24034375
transcript.pyannote[653].speaker SPEAKER_18
transcript.pyannote[653].start 4354.50659375
transcript.pyannote[653].end 4354.77659375
transcript.pyannote[654].speaker SPEAKER_18
transcript.pyannote[654].start 4356.90284375
transcript.pyannote[654].end 4360.15971875
transcript.pyannote[655].speaker SPEAKER_27
transcript.pyannote[655].start 4358.18534375
transcript.pyannote[655].end 4360.53096875
transcript.pyannote[656].speaker SPEAKER_27
transcript.pyannote[656].start 4360.96971875
transcript.pyannote[656].end 4373.64284375
transcript.pyannote[657].speaker SPEAKER_18
transcript.pyannote[657].start 4373.18721875
transcript.pyannote[657].end 4378.43534375
transcript.pyannote[658].speaker SPEAKER_18
transcript.pyannote[658].start 4378.60409375
transcript.pyannote[658].end 4383.02534375
transcript.pyannote[659].speaker SPEAKER_18
transcript.pyannote[659].start 4383.75096875
transcript.pyannote[659].end 4386.38346875
transcript.pyannote[660].speaker SPEAKER_28
transcript.pyannote[660].start 4386.56909375
transcript.pyannote[660].end 4386.58596875
transcript.pyannote[661].speaker SPEAKER_27
transcript.pyannote[661].start 4386.58596875
transcript.pyannote[661].end 4386.82221875
transcript.pyannote[662].speaker SPEAKER_18
transcript.pyannote[662].start 4386.78846875
transcript.pyannote[662].end 4390.77096875
transcript.pyannote[663].speaker SPEAKER_28
transcript.pyannote[663].start 4386.82221875
transcript.pyannote[663].end 4386.85596875
transcript.pyannote[664].speaker SPEAKER_27
transcript.pyannote[664].start 4391.56409375
transcript.pyannote[664].end 4392.01971875
transcript.pyannote[665].speaker SPEAKER_18
transcript.pyannote[665].start 4392.01971875
transcript.pyannote[665].end 4393.67346875
transcript.pyannote[666].speaker SPEAKER_27
transcript.pyannote[666].start 4393.74096875
transcript.pyannote[666].end 4395.36096875
transcript.pyannote[667].speaker SPEAKER_27
transcript.pyannote[667].start 4395.76596875
transcript.pyannote[667].end 4397.08221875
transcript.pyannote[668].speaker SPEAKER_27
transcript.pyannote[668].start 4397.65596875
transcript.pyannote[668].end 4399.57971875
transcript.pyannote[669].speaker SPEAKER_27
transcript.pyannote[669].start 4399.69784375
transcript.pyannote[669].end 4402.78596875
transcript.pyannote[670].speaker SPEAKER_27
transcript.pyannote[670].start 4403.19096875
transcript.pyannote[670].end 4405.14846875
transcript.pyannote[671].speaker SPEAKER_27
transcript.pyannote[671].start 4406.16096875
transcript.pyannote[671].end 4410.19409375
transcript.pyannote[672].speaker SPEAKER_27
transcript.pyannote[672].start 4410.61596875
transcript.pyannote[672].end 4419.57659375
transcript.pyannote[673].speaker SPEAKER_18
transcript.pyannote[673].start 4418.22659375
transcript.pyannote[673].end 4425.39846875
transcript.pyannote[674].speaker SPEAKER_27
transcript.pyannote[674].start 4423.03596875
transcript.pyannote[674].end 4423.28909375
transcript.pyannote[675].speaker SPEAKER_27
transcript.pyannote[675].start 4424.06534375
transcript.pyannote[675].end 4424.50409375
transcript.pyannote[676].speaker SPEAKER_27
transcript.pyannote[676].start 4425.09471875
transcript.pyannote[676].end 4429.85346875
transcript.pyannote[677].speaker SPEAKER_27
transcript.pyannote[677].start 4430.68034375
transcript.pyannote[677].end 4437.09284375
transcript.pyannote[678].speaker SPEAKER_27
transcript.pyannote[678].start 4437.24471875
transcript.pyannote[678].end 4438.93221875
transcript.pyannote[679].speaker SPEAKER_27
transcript.pyannote[679].start 4439.06721875
transcript.pyannote[679].end 4443.82596875
transcript.pyannote[680].speaker SPEAKER_27
transcript.pyannote[680].start 4443.99471875
transcript.pyannote[680].end 4447.30221875
transcript.pyannote[681].speaker SPEAKER_27
transcript.pyannote[681].start 4447.84221875
transcript.pyannote[681].end 4452.33096875
transcript.pyannote[682].speaker SPEAKER_18
transcript.pyannote[682].start 4451.97659375
transcript.pyannote[682].end 4454.20409375
transcript.pyannote[683].speaker SPEAKER_27
transcript.pyannote[683].start 4454.74409375
transcript.pyannote[683].end 4461.02159375
transcript.pyannote[684].speaker SPEAKER_18
transcript.pyannote[684].start 4457.10659375
transcript.pyannote[684].end 4465.45971875
transcript.pyannote[685].speaker SPEAKER_02
transcript.pyannote[685].start 4461.66284375
transcript.pyannote[685].end 4461.71346875
transcript.pyannote[686].speaker SPEAKER_27
transcript.pyannote[686].start 4461.71346875
transcript.pyannote[686].end 4461.88221875
transcript.pyannote[687].speaker SPEAKER_02
transcript.pyannote[687].start 4461.88221875
transcript.pyannote[687].end 4461.89909375
transcript.pyannote[688].speaker SPEAKER_18
transcript.pyannote[688].start 4465.88159375
transcript.pyannote[688].end 4467.97409375
transcript.pyannote[689].speaker SPEAKER_27
transcript.pyannote[689].start 4470.43784375
transcript.pyannote[689].end 4471.18034375
transcript.pyannote[690].speaker SPEAKER_27
transcript.pyannote[690].start 4472.02409375
transcript.pyannote[690].end 4472.42909375
transcript.pyannote[691].speaker SPEAKER_18
transcript.pyannote[691].start 4473.64409375
transcript.pyannote[691].end 4475.51721875
transcript.pyannote[692].speaker SPEAKER_27
transcript.pyannote[692].start 4475.12909375
transcript.pyannote[692].end 4476.19221875
transcript.pyannote[693].speaker SPEAKER_18
transcript.pyannote[693].start 4476.36096875
transcript.pyannote[693].end 4476.79971875
transcript.pyannote[694].speaker SPEAKER_18
transcript.pyannote[694].start 4477.98096875
transcript.pyannote[694].end 4479.65159375
transcript.pyannote[695].speaker SPEAKER_18
transcript.pyannote[695].start 4479.92159375
transcript.pyannote[695].end 4483.17846875
transcript.pyannote[696].speaker SPEAKER_18
transcript.pyannote[696].start 4483.38096875
transcript.pyannote[696].end 4490.51909375
transcript.pyannote[697].speaker SPEAKER_02
transcript.pyannote[697].start 4490.51909375
transcript.pyannote[697].end 4490.92409375
transcript.pyannote[698].speaker SPEAKER_18
transcript.pyannote[698].start 4490.92409375
transcript.pyannote[698].end 4495.80096875
transcript.pyannote[699].speaker SPEAKER_02
transcript.pyannote[699].start 4490.94096875
transcript.pyannote[699].end 4491.00846875
transcript.pyannote[700].speaker SPEAKER_27
transcript.pyannote[700].start 4495.80096875
transcript.pyannote[700].end 4495.81784375
transcript.pyannote[701].speaker SPEAKER_02
transcript.pyannote[701].start 4495.81784375
transcript.pyannote[701].end 4495.96971875
transcript.pyannote[702].speaker SPEAKER_27
transcript.pyannote[702].start 4495.96971875
transcript.pyannote[702].end 4496.15534375
transcript.pyannote[703].speaker SPEAKER_18
transcript.pyannote[703].start 4496.07096875
transcript.pyannote[703].end 4499.09159375
transcript.pyannote[704].speaker SPEAKER_02
transcript.pyannote[704].start 4496.15534375
transcript.pyannote[704].end 4496.17221875
transcript.pyannote[705].speaker SPEAKER_27
transcript.pyannote[705].start 4496.17221875
transcript.pyannote[705].end 4496.20596875
transcript.pyannote[706].speaker SPEAKER_27
transcript.pyannote[706].start 4499.39534375
transcript.pyannote[706].end 4501.84221875
transcript.pyannote[707].speaker SPEAKER_27
transcript.pyannote[707].start 4502.02784375
transcript.pyannote[707].end 4512.84471875
transcript.pyannote[708].speaker SPEAKER_02
transcript.pyannote[708].start 4512.86159375
transcript.pyannote[708].end 4513.35096875
transcript.pyannote[709].speaker SPEAKER_27
transcript.pyannote[709].start 4513.48596875
transcript.pyannote[709].end 4529.34846875
transcript.pyannote[710].speaker SPEAKER_18
transcript.pyannote[710].start 4527.18846875
transcript.pyannote[710].end 4532.47034375
transcript.pyannote[711].speaker SPEAKER_27
transcript.pyannote[711].start 4530.52971875
transcript.pyannote[711].end 4530.96846875
transcript.pyannote[712].speaker SPEAKER_18
transcript.pyannote[712].start 4533.48284375
transcript.pyannote[712].end 4535.06909375
transcript.pyannote[713].speaker SPEAKER_27
transcript.pyannote[713].start 4535.76096875
transcript.pyannote[713].end 4536.99284375
transcript.pyannote[714].speaker SPEAKER_18
transcript.pyannote[714].start 4537.09409375
transcript.pyannote[714].end 4538.08971875
transcript.pyannote[715].speaker SPEAKER_23
transcript.pyannote[715].start 4538.08971875
transcript.pyannote[715].end 4538.10659375
transcript.pyannote[716].speaker SPEAKER_18
transcript.pyannote[716].start 4538.10659375
transcript.pyannote[716].end 4538.12346875
transcript.pyannote[717].speaker SPEAKER_23
transcript.pyannote[717].start 4538.12346875
transcript.pyannote[717].end 4538.14034375
transcript.pyannote[718].speaker SPEAKER_27
transcript.pyannote[718].start 4538.64659375
transcript.pyannote[718].end 4539.28784375
transcript.pyannote[719].speaker SPEAKER_27
transcript.pyannote[719].start 4539.67596875
transcript.pyannote[719].end 4542.05534375
transcript.pyannote[720].speaker SPEAKER_23
transcript.pyannote[720].start 4541.65034375
transcript.pyannote[720].end 4547.70846875
transcript.pyannote[721].speaker SPEAKER_23
transcript.pyannote[721].start 4548.34971875
transcript.pyannote[721].end 4559.14971875
transcript.pyannote[722].speaker SPEAKER_23
transcript.pyannote[722].start 4559.31846875
transcript.pyannote[722].end 4560.82034375
transcript.pyannote[723].speaker SPEAKER_23
transcript.pyannote[723].start 4561.09034375
transcript.pyannote[723].end 4561.64721875
transcript.pyannote[724].speaker SPEAKER_23
transcript.pyannote[724].start 4561.79909375
transcript.pyannote[724].end 4567.68846875
transcript.pyannote[725].speaker SPEAKER_23
transcript.pyannote[725].start 4567.95846875
transcript.pyannote[725].end 4573.74659375
transcript.pyannote[726].speaker SPEAKER_18
transcript.pyannote[726].start 4570.94534375
transcript.pyannote[726].end 4587.44909375
transcript.pyannote[727].speaker SPEAKER_02
transcript.pyannote[727].start 4587.44909375
transcript.pyannote[727].end 4588.07346875
transcript.pyannote[728].speaker SPEAKER_18
transcript.pyannote[728].start 4587.98909375
transcript.pyannote[728].end 4588.30971875
transcript.pyannote[729].speaker SPEAKER_18
transcript.pyannote[729].start 4589.11971875
transcript.pyannote[729].end 4595.19471875
transcript.pyannote[730].speaker SPEAKER_18
transcript.pyannote[730].start 4595.41409375
transcript.pyannote[730].end 4598.65409375
transcript.pyannote[731].speaker SPEAKER_18
transcript.pyannote[731].start 4598.99159375
transcript.pyannote[731].end 4614.33096875
transcript.pyannote[732].speaker SPEAKER_27
transcript.pyannote[732].start 4614.92159375
transcript.pyannote[732].end 4616.15346875
transcript.pyannote[733].speaker SPEAKER_27
transcript.pyannote[733].start 4618.26284375
transcript.pyannote[733].end 4627.03784375
transcript.pyannote[734].speaker SPEAKER_27
transcript.pyannote[734].start 4627.67909375
transcript.pyannote[734].end 4638.44534375
transcript.pyannote[735].speaker SPEAKER_27
transcript.pyannote[735].start 4638.81659375
transcript.pyannote[735].end 4644.73971875
transcript.pyannote[736].speaker SPEAKER_27
transcript.pyannote[736].start 4645.39784375
transcript.pyannote[736].end 4647.94596875
transcript.pyannote[737].speaker SPEAKER_27
transcript.pyannote[737].start 4648.36784375
transcript.pyannote[737].end 4653.46409375
transcript.pyannote[738].speaker SPEAKER_18
transcript.pyannote[738].start 4652.73846875
transcript.pyannote[738].end 4675.85721875
transcript.pyannote[739].speaker SPEAKER_28
transcript.pyannote[739].start 4668.55034375
transcript.pyannote[739].end 4668.60096875
transcript.pyannote[740].speaker SPEAKER_00
transcript.pyannote[740].start 4668.60096875
transcript.pyannote[740].end 4668.65159375
transcript.pyannote[741].speaker SPEAKER_28
transcript.pyannote[741].start 4668.65159375
transcript.pyannote[741].end 4668.75284375
transcript.pyannote[742].speaker SPEAKER_00
transcript.pyannote[742].start 4668.75284375
transcript.pyannote[742].end 4668.83721875
transcript.pyannote[743].speaker SPEAKER_18
transcript.pyannote[743].start 4678.13534375
transcript.pyannote[743].end 4679.33346875
transcript.pyannote[744].speaker SPEAKER_27
transcript.pyannote[744].start 4679.33346875
transcript.pyannote[744].end 4679.70471875
transcript.pyannote[745].speaker SPEAKER_12
transcript.pyannote[745].start 4680.85221875
transcript.pyannote[745].end 4684.64909375
transcript.pyannote[746].speaker SPEAKER_12
transcript.pyannote[746].start 4684.66596875
transcript.pyannote[746].end 4688.90159375
transcript.pyannote[747].speaker SPEAKER_27
transcript.pyannote[747].start 4684.73346875
transcript.pyannote[747].end 4684.85159375
transcript.pyannote[748].speaker SPEAKER_03
transcript.pyannote[748].start 4684.85159375
transcript.pyannote[748].end 4684.90221875
transcript.pyannote[749].speaker SPEAKER_03
transcript.pyannote[749].start 4692.71534375
transcript.pyannote[749].end 4694.13284375
transcript.pyannote[750].speaker SPEAKER_03
transcript.pyannote[750].start 4699.31346875
transcript.pyannote[750].end 4720.86284375
transcript.pyannote[751].speaker SPEAKER_00
transcript.pyannote[751].start 4700.14034375
transcript.pyannote[751].end 4700.81534375
transcript.pyannote[752].speaker SPEAKER_00
transcript.pyannote[752].start 4700.96721875
transcript.pyannote[752].end 4701.27096875
transcript.pyannote[753].speaker SPEAKER_03
transcript.pyannote[753].start 4720.93034375
transcript.pyannote[753].end 4720.99784375
transcript.pyannote[754].speaker SPEAKER_27
transcript.pyannote[754].start 4720.99784375
transcript.pyannote[754].end 4721.09909375
transcript.pyannote[755].speaker SPEAKER_03
transcript.pyannote[755].start 4721.09909375
transcript.pyannote[755].end 4721.18346875
transcript.pyannote[756].speaker SPEAKER_27
transcript.pyannote[756].start 4721.18346875
transcript.pyannote[756].end 4724.69346875
transcript.pyannote[757].speaker SPEAKER_03
transcript.pyannote[757].start 4721.70659375
transcript.pyannote[757].end 4722.56721875
transcript.pyannote[758].speaker SPEAKER_03
transcript.pyannote[758].start 4723.05659375
transcript.pyannote[758].end 4734.71721875
transcript.pyannote[759].speaker SPEAKER_27
transcript.pyannote[759].start 4726.88721875
transcript.pyannote[759].end 4727.24159375
transcript.pyannote[760].speaker SPEAKER_03
transcript.pyannote[760].start 4735.20659375
transcript.pyannote[760].end 4749.90471875
transcript.pyannote[761].speaker SPEAKER_03
transcript.pyannote[761].start 4750.51221875
transcript.pyannote[761].end 4752.62159375
transcript.pyannote[762].speaker SPEAKER_27
transcript.pyannote[762].start 4752.62159375
transcript.pyannote[762].end 4753.02659375
transcript.pyannote[763].speaker SPEAKER_27
transcript.pyannote[763].start 4753.17846875
transcript.pyannote[763].end 4759.33784375
transcript.pyannote[764].speaker SPEAKER_03
transcript.pyannote[764].start 4753.83659375
transcript.pyannote[764].end 4754.83221875
transcript.pyannote[765].speaker SPEAKER_03
transcript.pyannote[765].start 4756.55346875
transcript.pyannote[765].end 4757.41409375
transcript.pyannote[766].speaker SPEAKER_03
transcript.pyannote[766].start 4758.88221875
transcript.pyannote[766].end 4799.16284375
transcript.pyannote[767].speaker SPEAKER_27
transcript.pyannote[767].start 4759.75971875
transcript.pyannote[767].end 4760.53596875
transcript.pyannote[768].speaker SPEAKER_03
transcript.pyannote[768].start 4799.58471875
transcript.pyannote[768].end 4818.41721875
transcript.pyannote[769].speaker SPEAKER_27
transcript.pyannote[769].start 4817.72534375
transcript.pyannote[769].end 4818.36659375
transcript.pyannote[770].speaker SPEAKER_27
transcript.pyannote[770].start 4818.41721875
transcript.pyannote[770].end 4827.09096875
transcript.pyannote[771].speaker SPEAKER_27
transcript.pyannote[771].start 4827.52971875
transcript.pyannote[771].end 4841.65409375
transcript.pyannote[772].speaker SPEAKER_00
transcript.pyannote[772].start 4829.40284375
transcript.pyannote[772].end 4829.41971875
transcript.pyannote[773].speaker SPEAKER_28
transcript.pyannote[773].start 4829.41971875
transcript.pyannote[773].end 4829.45346875
transcript.pyannote[774].speaker SPEAKER_02
transcript.pyannote[774].start 4829.45346875
transcript.pyannote[774].end 4829.84159375
transcript.pyannote[775].speaker SPEAKER_28
transcript.pyannote[775].start 4829.84159375
transcript.pyannote[775].end 4829.85846875
transcript.pyannote[776].speaker SPEAKER_02
transcript.pyannote[776].start 4829.85846875
transcript.pyannote[776].end 4829.87534375
transcript.pyannote[777].speaker SPEAKER_00
transcript.pyannote[777].start 4839.62909375
transcript.pyannote[777].end 4840.11846875
transcript.pyannote[778].speaker SPEAKER_27
transcript.pyannote[778].start 4842.17721875
transcript.pyannote[778].end 4844.28659375
transcript.pyannote[779].speaker SPEAKER_27
transcript.pyannote[779].start 4844.30346875
transcript.pyannote[779].end 4859.94659375
transcript.pyannote[780].speaker SPEAKER_02
transcript.pyannote[780].start 4846.07534375
transcript.pyannote[780].end 4846.10909375
transcript.pyannote[781].speaker SPEAKER_03
transcript.pyannote[781].start 4853.26409375
transcript.pyannote[781].end 4853.28096875
transcript.pyannote[782].speaker SPEAKER_02
transcript.pyannote[782].start 4853.28096875
transcript.pyannote[782].end 4853.56784375
transcript.pyannote[783].speaker SPEAKER_03
transcript.pyannote[783].start 4853.56784375
transcript.pyannote[783].end 4853.60159375
transcript.pyannote[784].speaker SPEAKER_03
transcript.pyannote[784].start 4855.20471875
transcript.pyannote[784].end 4855.79534375
transcript.pyannote[785].speaker SPEAKER_03
transcript.pyannote[785].start 4856.92596875
transcript.pyannote[785].end 4857.66846875
transcript.pyannote[786].speaker SPEAKER_03
transcript.pyannote[786].start 4858.10721875
transcript.pyannote[786].end 4876.31534375
transcript.pyannote[787].speaker SPEAKER_27
transcript.pyannote[787].start 4861.24596875
transcript.pyannote[787].end 4861.66784375
transcript.pyannote[788].speaker SPEAKER_27
transcript.pyannote[788].start 4864.94159375
transcript.pyannote[788].end 4865.26221875
transcript.pyannote[789].speaker SPEAKER_28
transcript.pyannote[789].start 4866.86534375
transcript.pyannote[789].end 4867.27034375
transcript.pyannote[790].speaker SPEAKER_00
transcript.pyannote[790].start 4867.27034375
transcript.pyannote[790].end 4867.30409375
transcript.pyannote[791].speaker SPEAKER_00
transcript.pyannote[791].start 4868.23221875
transcript.pyannote[791].end 4868.65409375
transcript.pyannote[792].speaker SPEAKER_27
transcript.pyannote[792].start 4876.31534375
transcript.pyannote[792].end 4876.58534375
transcript.pyannote[793].speaker SPEAKER_03
transcript.pyannote[793].start 4876.41659375
transcript.pyannote[793].end 4876.50096875
transcript.pyannote[794].speaker SPEAKER_03
transcript.pyannote[794].start 4876.58534375
transcript.pyannote[794].end 4876.97346875
transcript.pyannote[795].speaker SPEAKER_27
transcript.pyannote[795].start 4876.97346875
transcript.pyannote[795].end 4905.23909375
transcript.pyannote[796].speaker SPEAKER_27
transcript.pyannote[796].start 4905.79596875
transcript.pyannote[796].end 4907.34846875
transcript.pyannote[797].speaker SPEAKER_27
transcript.pyannote[797].start 4907.39909375
transcript.pyannote[797].end 4911.51659375
transcript.pyannote[798].speaker SPEAKER_27
transcript.pyannote[798].start 4911.76971875
transcript.pyannote[798].end 4920.91596875
transcript.pyannote[799].speaker SPEAKER_03
transcript.pyannote[799].start 4920.07221875
transcript.pyannote[799].end 4929.01596875
transcript.pyannote[800].speaker SPEAKER_27
transcript.pyannote[800].start 4927.54784375
transcript.pyannote[800].end 4934.41596875
transcript.pyannote[801].speaker SPEAKER_03
transcript.pyannote[801].start 4932.61034375
transcript.pyannote[801].end 4933.74096875
transcript.pyannote[802].speaker SPEAKER_27
transcript.pyannote[802].start 4934.71971875
transcript.pyannote[802].end 4944.81096875
transcript.pyannote[803].speaker SPEAKER_03
transcript.pyannote[803].start 4937.11596875
transcript.pyannote[803].end 4937.60534375
transcript.pyannote[804].speaker SPEAKER_04
transcript.pyannote[804].start 4937.60534375
transcript.pyannote[804].end 4937.62221875
transcript.pyannote[805].speaker SPEAKER_27
transcript.pyannote[805].start 4945.38471875
transcript.pyannote[805].end 4950.64971875
transcript.pyannote[806].speaker SPEAKER_00
transcript.pyannote[806].start 4950.64971875
transcript.pyannote[806].end 4950.95346875
transcript.pyannote[807].speaker SPEAKER_27
transcript.pyannote[807].start 4950.95346875
transcript.pyannote[807].end 4955.94846875
transcript.pyannote[808].speaker SPEAKER_27
transcript.pyannote[808].start 4956.52221875
transcript.pyannote[808].end 4988.24721875
transcript.pyannote[809].speaker SPEAKER_03
transcript.pyannote[809].start 4959.35721875
transcript.pyannote[809].end 4959.59346875
transcript.pyannote[810].speaker SPEAKER_03
transcript.pyannote[810].start 4964.35221875
transcript.pyannote[810].end 4966.15784375
transcript.pyannote[811].speaker SPEAKER_03
transcript.pyannote[811].start 4967.17034375
transcript.pyannote[811].end 4969.41471875
transcript.pyannote[812].speaker SPEAKER_03
transcript.pyannote[812].start 4970.68034375
transcript.pyannote[812].end 4971.00096875
transcript.pyannote[813].speaker SPEAKER_00
transcript.pyannote[813].start 4983.03284375
transcript.pyannote[813].end 4983.47159375
transcript.pyannote[814].speaker SPEAKER_27
transcript.pyannote[814].start 4988.60159375
transcript.pyannote[814].end 5012.02409375
transcript.pyannote[815].speaker SPEAKER_28
transcript.pyannote[815].start 4990.33971875
transcript.pyannote[815].end 4990.42409375
transcript.pyannote[816].speaker SPEAKER_03
transcript.pyannote[816].start 5012.02409375
transcript.pyannote[816].end 5054.12721875
transcript.pyannote[817].speaker SPEAKER_27
transcript.pyannote[817].start 5013.59346875
transcript.pyannote[817].end 5013.91409375
transcript.pyannote[818].speaker SPEAKER_00
transcript.pyannote[818].start 5029.82721875
transcript.pyannote[818].end 5030.02971875
transcript.pyannote[819].speaker SPEAKER_02
transcript.pyannote[819].start 5030.02971875
transcript.pyannote[819].end 5030.41784375
transcript.pyannote[820].speaker SPEAKER_00
transcript.pyannote[820].start 5030.41784375
transcript.pyannote[820].end 5030.45159375
transcript.pyannote[821].speaker SPEAKER_04
transcript.pyannote[821].start 5046.71909375
transcript.pyannote[821].end 5047.49534375
transcript.pyannote[822].speaker SPEAKER_27
transcript.pyannote[822].start 5047.49534375
transcript.pyannote[822].end 5047.56284375
transcript.pyannote[823].speaker SPEAKER_03
transcript.pyannote[823].start 5054.22846875
transcript.pyannote[823].end 5057.01284375
transcript.pyannote[824].speaker SPEAKER_03
transcript.pyannote[824].start 5058.10971875
transcript.pyannote[824].end 5065.06221875
transcript.pyannote[825].speaker SPEAKER_28
transcript.pyannote[825].start 5059.78034375
transcript.pyannote[825].end 5059.79721875
transcript.pyannote[826].speaker SPEAKER_27
transcript.pyannote[826].start 5059.83096875
transcript.pyannote[826].end 5059.91534375
transcript.pyannote[827].speaker SPEAKER_27
transcript.pyannote[827].start 5065.45034375
transcript.pyannote[827].end 5069.29784375
transcript.pyannote[828].speaker SPEAKER_27
transcript.pyannote[828].start 5069.77034375
transcript.pyannote[828].end 5072.06534375
transcript.pyannote[829].speaker SPEAKER_27
transcript.pyannote[829].start 5072.79096875
transcript.pyannote[829].end 5077.92096875
transcript.pyannote[830].speaker SPEAKER_27
transcript.pyannote[830].start 5078.12346875
transcript.pyannote[830].end 5084.35034375
transcript.pyannote[831].speaker SPEAKER_28
transcript.pyannote[831].start 5081.38034375
transcript.pyannote[831].end 5081.39721875
transcript.pyannote[832].speaker SPEAKER_27
transcript.pyannote[832].start 5084.68784375
transcript.pyannote[832].end 5087.80971875
transcript.pyannote[833].speaker SPEAKER_27
transcript.pyannote[833].start 5087.96159375
transcript.pyannote[833].end 5104.71846875
transcript.pyannote[834].speaker SPEAKER_28
transcript.pyannote[834].start 5089.71659375
transcript.pyannote[834].end 5089.93596875
transcript.pyannote[835].speaker SPEAKER_28
transcript.pyannote[835].start 5099.09909375
transcript.pyannote[835].end 5099.11596875
transcript.pyannote[836].speaker SPEAKER_02
transcript.pyannote[836].start 5099.11596875
transcript.pyannote[836].end 5099.65596875
transcript.pyannote[837].speaker SPEAKER_28
transcript.pyannote[837].start 5099.65596875
transcript.pyannote[837].end 5099.67284375
transcript.pyannote[838].speaker SPEAKER_27
transcript.pyannote[838].start 5105.05596875
transcript.pyannote[838].end 5116.14284375
transcript.pyannote[839].speaker SPEAKER_00
transcript.pyannote[839].start 5109.30846875
transcript.pyannote[839].end 5109.64596875
transcript.pyannote[840].speaker SPEAKER_27
transcript.pyannote[840].start 5116.15971875
transcript.pyannote[840].end 5116.17659375
transcript.pyannote[841].speaker SPEAKER_27
transcript.pyannote[841].start 5116.34534375
transcript.pyannote[841].end 5122.65659375
transcript.pyannote[842].speaker SPEAKER_00
transcript.pyannote[842].start 5121.32346875
transcript.pyannote[842].end 5121.76221875
transcript.pyannote[843].speaker SPEAKER_27
transcript.pyannote[843].start 5122.97721875
transcript.pyannote[843].end 5126.03159375
transcript.pyannote[844].speaker SPEAKER_03
transcript.pyannote[844].start 5126.03159375
transcript.pyannote[844].end 5178.34409375
transcript.pyannote[845].speaker SPEAKER_27
transcript.pyannote[845].start 5127.21284375
transcript.pyannote[845].end 5127.38159375
transcript.pyannote[846].speaker SPEAKER_28
transcript.pyannote[846].start 5136.02159375
transcript.pyannote[846].end 5136.07221875
transcript.pyannote[847].speaker SPEAKER_25
transcript.pyannote[847].start 5136.07221875
transcript.pyannote[847].end 5136.13971875
transcript.pyannote[848].speaker SPEAKER_28
transcript.pyannote[848].start 5136.13971875
transcript.pyannote[848].end 5136.17346875
transcript.pyannote[849].speaker SPEAKER_00
transcript.pyannote[849].start 5136.17346875
transcript.pyannote[849].end 5136.19034375
transcript.pyannote[850].speaker SPEAKER_28
transcript.pyannote[850].start 5137.74284375
transcript.pyannote[850].end 5137.89471875
transcript.pyannote[851].speaker SPEAKER_28
transcript.pyannote[851].start 5138.83971875
transcript.pyannote[851].end 5138.85659375
transcript.pyannote[852].speaker SPEAKER_00
transcript.pyannote[852].start 5164.03409375
transcript.pyannote[852].end 5164.05096875
transcript.pyannote[853].speaker SPEAKER_28
transcript.pyannote[853].start 5164.05096875
transcript.pyannote[853].end 5164.43909375
transcript.pyannote[854].speaker SPEAKER_03
transcript.pyannote[854].start 5178.73221875
transcript.pyannote[854].end 5187.50721875
transcript.pyannote[855].speaker SPEAKER_03
transcript.pyannote[855].start 5187.79409375
transcript.pyannote[855].end 5211.84096875
transcript.pyannote[856].speaker SPEAKER_00
transcript.pyannote[856].start 5203.89284375
transcript.pyannote[856].end 5203.96034375
transcript.pyannote[857].speaker SPEAKER_28
transcript.pyannote[857].start 5203.96034375
transcript.pyannote[857].end 5204.31471875
transcript.pyannote[858].speaker SPEAKER_28
transcript.pyannote[858].start 5211.84096875
transcript.pyannote[858].end 5211.99284375
transcript.pyannote[859].speaker SPEAKER_03
transcript.pyannote[859].start 5211.99284375
transcript.pyannote[859].end 5213.35971875
transcript.pyannote[860].speaker SPEAKER_03
transcript.pyannote[860].start 5213.88284375
transcript.pyannote[860].end 5227.34909375
transcript.pyannote[861].speaker SPEAKER_27
transcript.pyannote[861].start 5223.94034375
transcript.pyannote[861].end 5229.49221875
transcript.pyannote[862].speaker SPEAKER_03
transcript.pyannote[862].start 5228.02409375
transcript.pyannote[862].end 5229.42471875
transcript.pyannote[863].speaker SPEAKER_02
transcript.pyannote[863].start 5229.49221875
transcript.pyannote[863].end 5229.50909375
transcript.pyannote[864].speaker SPEAKER_12
transcript.pyannote[864].start 5230.13346875
transcript.pyannote[864].end 5233.93034375
transcript.pyannote[865].speaker SPEAKER_03
transcript.pyannote[865].start 5243.32971875
transcript.pyannote[865].end 5246.18159375
transcript.pyannote[866].speaker SPEAKER_01
transcript.pyannote[866].start 5253.08346875
transcript.pyannote[866].end 5257.21784375
transcript.pyannote[867].speaker SPEAKER_03
transcript.pyannote[867].start 5257.90971875
transcript.pyannote[867].end 5258.34846875
transcript.pyannote[868].speaker SPEAKER_01
transcript.pyannote[868].start 5258.83784375
transcript.pyannote[868].end 5261.82471875
transcript.pyannote[869].speaker SPEAKER_03
transcript.pyannote[869].start 5259.17534375
transcript.pyannote[869].end 5259.20909375
transcript.pyannote[870].speaker SPEAKER_27
transcript.pyannote[870].start 5259.20909375
transcript.pyannote[870].end 5261.16659375
transcript.pyannote[871].speaker SPEAKER_01
transcript.pyannote[871].start 5261.99346875
transcript.pyannote[871].end 5262.19596875
transcript.pyannote[872].speaker SPEAKER_27
transcript.pyannote[872].start 5264.22096875
transcript.pyannote[872].end 5264.89596875
transcript.pyannote[873].speaker SPEAKER_01
transcript.pyannote[873].start 5267.78159375
transcript.pyannote[873].end 5268.11909375
transcript.pyannote[874].speaker SPEAKER_01
transcript.pyannote[874].start 5268.70971875
transcript.pyannote[874].end 5269.99221875
transcript.pyannote[875].speaker SPEAKER_02
transcript.pyannote[875].start 5270.07659375
transcript.pyannote[875].end 5270.36346875
transcript.pyannote[876].speaker SPEAKER_01
transcript.pyannote[876].start 5270.65034375
transcript.pyannote[876].end 5273.68784375
transcript.pyannote[877].speaker SPEAKER_01
transcript.pyannote[877].start 5274.37971875
transcript.pyannote[877].end 5277.09659375
transcript.pyannote[878].speaker SPEAKER_01
transcript.pyannote[878].start 5277.60284375
transcript.pyannote[878].end 5279.45909375
transcript.pyannote[879].speaker SPEAKER_01
transcript.pyannote[879].start 5280.48846875
transcript.pyannote[879].end 5288.80784375
transcript.pyannote[880].speaker SPEAKER_01
transcript.pyannote[880].start 5288.95971875
transcript.pyannote[880].end 5289.38159375
transcript.pyannote[881].speaker SPEAKER_01
transcript.pyannote[881].start 5290.56284375
transcript.pyannote[881].end 5290.61346875
transcript.pyannote[882].speaker SPEAKER_01
transcript.pyannote[882].start 5290.68096875
transcript.pyannote[882].end 5291.96346875
transcript.pyannote[883].speaker SPEAKER_01
transcript.pyannote[883].start 5292.73971875
transcript.pyannote[883].end 5296.80659375
transcript.pyannote[884].speaker SPEAKER_01
transcript.pyannote[884].start 5297.39721875
transcript.pyannote[884].end 5301.90284375
transcript.pyannote[885].speaker SPEAKER_01
transcript.pyannote[885].start 5302.25721875
transcript.pyannote[885].end 5303.21909375
transcript.pyannote[886].speaker SPEAKER_01
transcript.pyannote[886].start 5303.89409375
transcript.pyannote[886].end 5304.77159375
transcript.pyannote[887].speaker SPEAKER_01
transcript.pyannote[887].start 5305.24409375
transcript.pyannote[887].end 5306.74596875
transcript.pyannote[888].speaker SPEAKER_01
transcript.pyannote[888].start 5307.91034375
transcript.pyannote[888].end 5310.76221875
transcript.pyannote[889].speaker SPEAKER_01
transcript.pyannote[889].start 5311.97721875
transcript.pyannote[889].end 5316.43221875
transcript.pyannote[890].speaker SPEAKER_01
transcript.pyannote[890].start 5316.97221875
transcript.pyannote[890].end 5317.76534375
transcript.pyannote[891].speaker SPEAKER_01
transcript.pyannote[891].start 5318.86221875
transcript.pyannote[891].end 5324.39721875
transcript.pyannote[892].speaker SPEAKER_01
transcript.pyannote[892].start 5327.04659375
transcript.pyannote[892].end 5328.16034375
transcript.pyannote[893].speaker SPEAKER_01
transcript.pyannote[893].start 5328.73409375
transcript.pyannote[893].end 5330.55659375
transcript.pyannote[894].speaker SPEAKER_01
transcript.pyannote[894].start 5330.96159375
transcript.pyannote[894].end 5331.18096875
transcript.pyannote[895].speaker SPEAKER_01
transcript.pyannote[895].start 5331.60284375
transcript.pyannote[895].end 5333.00346875
transcript.pyannote[896].speaker SPEAKER_01
transcript.pyannote[896].start 5333.52659375
transcript.pyannote[896].end 5335.19721875
transcript.pyannote[897].speaker SPEAKER_01
transcript.pyannote[897].start 5336.53034375
transcript.pyannote[897].end 5336.86784375
transcript.pyannote[898].speaker SPEAKER_23
transcript.pyannote[898].start 5336.86784375
transcript.pyannote[898].end 5337.86346875
transcript.pyannote[899].speaker SPEAKER_01
transcript.pyannote[899].start 5339.43284375
transcript.pyannote[899].end 5340.09096875
transcript.pyannote[900].speaker SPEAKER_01
transcript.pyannote[900].start 5342.31846875
transcript.pyannote[900].end 5345.69346875
transcript.pyannote[901].speaker SPEAKER_01
transcript.pyannote[901].start 5345.96346875
transcript.pyannote[901].end 5347.71846875
transcript.pyannote[902].speaker SPEAKER_01
transcript.pyannote[902].start 5348.39346875
transcript.pyannote[902].end 5357.91096875
transcript.pyannote[903].speaker SPEAKER_01
transcript.pyannote[903].start 5358.60284375
transcript.pyannote[903].end 5361.55596875
transcript.pyannote[904].speaker SPEAKER_01
transcript.pyannote[904].start 5362.48409375
transcript.pyannote[904].end 5365.20096875
transcript.pyannote[905].speaker SPEAKER_02
transcript.pyannote[905].start 5365.20096875
transcript.pyannote[905].end 5365.40346875
transcript.pyannote[906].speaker SPEAKER_01
transcript.pyannote[906].start 5365.79159375
transcript.pyannote[906].end 5371.69784375
transcript.pyannote[907].speaker SPEAKER_01
transcript.pyannote[907].start 5372.03534375
transcript.pyannote[907].end 5381.13096875
transcript.pyannote[908].speaker SPEAKER_01
transcript.pyannote[908].start 5381.60346875
transcript.pyannote[908].end 5382.49784375
transcript.pyannote[909].speaker SPEAKER_02
transcript.pyannote[909].start 5384.32034375
transcript.pyannote[909].end 5384.33721875
transcript.pyannote[910].speaker SPEAKER_27
transcript.pyannote[910].start 5384.33721875
transcript.pyannote[910].end 5385.60284375
transcript.pyannote[911].speaker SPEAKER_27
transcript.pyannote[911].start 5385.90659375
transcript.pyannote[911].end 5391.84659375
transcript.pyannote[912].speaker SPEAKER_02
transcript.pyannote[912].start 5391.84659375
transcript.pyannote[912].end 5392.01534375
transcript.pyannote[913].speaker SPEAKER_27
transcript.pyannote[913].start 5392.01534375
transcript.pyannote[913].end 5405.70096875
transcript.pyannote[914].speaker SPEAKER_27
transcript.pyannote[914].start 5406.00471875
transcript.pyannote[914].end 5410.00409375
transcript.pyannote[915].speaker SPEAKER_27
transcript.pyannote[915].start 5410.45971875
transcript.pyannote[915].end 5413.83471875
transcript.pyannote[916].speaker SPEAKER_23
transcript.pyannote[916].start 5413.39596875
transcript.pyannote[916].end 5414.40846875
transcript.pyannote[917].speaker SPEAKER_27
transcript.pyannote[917].start 5414.30721875
transcript.pyannote[917].end 5418.13784375
transcript.pyannote[918].speaker SPEAKER_27
transcript.pyannote[918].start 5418.57659375
transcript.pyannote[918].end 5431.16534375
transcript.pyannote[919].speaker SPEAKER_01
transcript.pyannote[919].start 5429.78159375
transcript.pyannote[919].end 5434.21971875
transcript.pyannote[920].speaker SPEAKER_01
transcript.pyannote[920].start 5434.65846875
transcript.pyannote[920].end 5441.88096875
transcript.pyannote[921].speaker SPEAKER_01
transcript.pyannote[921].start 5442.85971875
transcript.pyannote[921].end 5443.97346875
transcript.pyannote[922].speaker SPEAKER_23
transcript.pyannote[922].start 5443.97346875
transcript.pyannote[922].end 5444.44596875
transcript.pyannote[923].speaker SPEAKER_01
transcript.pyannote[923].start 5444.44596875
transcript.pyannote[923].end 5444.46284375
transcript.pyannote[924].speaker SPEAKER_01
transcript.pyannote[924].start 5444.91846875
transcript.pyannote[924].end 5444.93534375
transcript.pyannote[925].speaker SPEAKER_23
transcript.pyannote[925].start 5444.93534375
transcript.pyannote[925].end 5447.58471875
transcript.pyannote[926].speaker SPEAKER_23
transcript.pyannote[926].start 5447.60159375
transcript.pyannote[926].end 5459.78534375
transcript.pyannote[927].speaker SPEAKER_23
transcript.pyannote[927].start 5460.03846875
transcript.pyannote[927].end 5461.91159375
transcript.pyannote[928].speaker SPEAKER_23
transcript.pyannote[928].start 5461.97909375
transcript.pyannote[928].end 5480.99721875
transcript.pyannote[929].speaker SPEAKER_01
transcript.pyannote[929].start 5478.51659375
transcript.pyannote[929].end 5487.03846875
transcript.pyannote[930].speaker SPEAKER_23
transcript.pyannote[930].start 5481.19971875
transcript.pyannote[930].end 5481.28409375
transcript.pyannote[931].speaker SPEAKER_01
transcript.pyannote[931].start 5487.13971875
transcript.pyannote[931].end 5490.88596875
transcript.pyannote[932].speaker SPEAKER_01
transcript.pyannote[932].start 5491.52721875
transcript.pyannote[932].end 5495.74596875
transcript.pyannote[933].speaker SPEAKER_01
transcript.pyannote[933].start 5496.35346875
transcript.pyannote[933].end 5497.73721875
transcript.pyannote[934].speaker SPEAKER_01
transcript.pyannote[934].start 5498.83409375
transcript.pyannote[934].end 5501.26409375
transcript.pyannote[935].speaker SPEAKER_01
transcript.pyannote[935].start 5501.50034375
transcript.pyannote[935].end 5502.54659375
transcript.pyannote[936].speaker SPEAKER_01
transcript.pyannote[936].start 5504.60534375
transcript.pyannote[936].end 5507.13659375
transcript.pyannote[937].speaker SPEAKER_01
transcript.pyannote[937].start 5507.45721875
transcript.pyannote[937].end 5509.83659375
transcript.pyannote[938].speaker SPEAKER_01
transcript.pyannote[938].start 5510.25846875
transcript.pyannote[938].end 5510.88284375
transcript.pyannote[939].speaker SPEAKER_01
transcript.pyannote[939].start 5511.74346875
transcript.pyannote[939].end 5518.34159375
transcript.pyannote[940].speaker SPEAKER_23
transcript.pyannote[940].start 5519.62409375
transcript.pyannote[940].end 5534.28846875
transcript.pyannote[941].speaker SPEAKER_01
transcript.pyannote[941].start 5520.24846875
transcript.pyannote[941].end 5521.24409375
transcript.pyannote[942].speaker SPEAKER_23
transcript.pyannote[942].start 5534.50784375
transcript.pyannote[942].end 5536.51596875
transcript.pyannote[943].speaker SPEAKER_23
transcript.pyannote[943].start 5537.00534375
transcript.pyannote[943].end 5543.02971875
transcript.pyannote[944].speaker SPEAKER_01
transcript.pyannote[944].start 5542.25346875
transcript.pyannote[944].end 5546.48909375
transcript.pyannote[945].speaker SPEAKER_01
transcript.pyannote[945].start 5547.75471875
transcript.pyannote[945].end 5549.12159375
transcript.pyannote[946].speaker SPEAKER_01
transcript.pyannote[946].start 5549.88096875
transcript.pyannote[946].end 5551.58534375
transcript.pyannote[947].speaker SPEAKER_01
transcript.pyannote[947].start 5551.95659375
transcript.pyannote[947].end 5556.24284375
transcript.pyannote[948].speaker SPEAKER_23
transcript.pyannote[948].start 5556.24284375
transcript.pyannote[948].end 5574.67034375
transcript.pyannote[949].speaker SPEAKER_01
transcript.pyannote[949].start 5573.05034375
transcript.pyannote[949].end 5573.53971875
transcript.pyannote[950].speaker SPEAKER_01
transcript.pyannote[950].start 5574.67034375
transcript.pyannote[950].end 5577.35346875
transcript.pyannote[951].speaker SPEAKER_23
transcript.pyannote[951].start 5576.23971875
transcript.pyannote[951].end 5583.91784375
transcript.pyannote[952].speaker SPEAKER_01
transcript.pyannote[952].start 5581.79159375
transcript.pyannote[952].end 5582.28096875
transcript.pyannote[953].speaker SPEAKER_01
transcript.pyannote[953].start 5582.33159375
transcript.pyannote[953].end 5583.34409375
transcript.pyannote[954].speaker SPEAKER_01
transcript.pyannote[954].start 5583.91784375
transcript.pyannote[954].end 5588.54159375
transcript.pyannote[955].speaker SPEAKER_01
transcript.pyannote[955].start 5588.84534375
transcript.pyannote[955].end 5590.21221875
transcript.pyannote[956].speaker SPEAKER_01
transcript.pyannote[956].start 5591.08971875
transcript.pyannote[956].end 5595.69659375
transcript.pyannote[957].speaker SPEAKER_01
transcript.pyannote[957].start 5596.18596875
transcript.pyannote[957].end 5598.58221875
transcript.pyannote[958].speaker SPEAKER_01
transcript.pyannote[958].start 5598.91971875
transcript.pyannote[958].end 5603.18909375
transcript.pyannote[959].speaker SPEAKER_01
transcript.pyannote[959].start 5603.50971875
transcript.pyannote[959].end 5605.23096875
transcript.pyannote[960].speaker SPEAKER_01
transcript.pyannote[960].start 5605.63596875
transcript.pyannote[960].end 5606.39534375
transcript.pyannote[961].speaker SPEAKER_01
transcript.pyannote[961].start 5606.88471875
transcript.pyannote[961].end 5607.96471875
transcript.pyannote[962].speaker SPEAKER_01
transcript.pyannote[962].start 5608.79159375
transcript.pyannote[962].end 5609.36534375
transcript.pyannote[963].speaker SPEAKER_01
transcript.pyannote[963].start 5609.87159375
transcript.pyannote[963].end 5613.71909375
transcript.pyannote[964].speaker SPEAKER_01
transcript.pyannote[964].start 5614.71471875
transcript.pyannote[964].end 5616.31784375
transcript.pyannote[965].speaker SPEAKER_01
transcript.pyannote[965].start 5617.39784375
transcript.pyannote[965].end 5619.03471875
transcript.pyannote[966].speaker SPEAKER_01
transcript.pyannote[966].start 5619.87846875
transcript.pyannote[966].end 5621.31284375
transcript.pyannote[967].speaker SPEAKER_01
transcript.pyannote[967].start 5621.81909375
transcript.pyannote[967].end 5623.81034375
transcript.pyannote[968].speaker SPEAKER_01
transcript.pyannote[968].start 5624.21534375
transcript.pyannote[968].end 5628.06284375
transcript.pyannote[969].speaker SPEAKER_01
transcript.pyannote[969].start 5628.80534375
transcript.pyannote[969].end 5632.23096875
transcript.pyannote[970].speaker SPEAKER_01
transcript.pyannote[970].start 5632.95659375
transcript.pyannote[970].end 5634.45846875
transcript.pyannote[971].speaker SPEAKER_01
transcript.pyannote[971].start 5634.71159375
transcript.pyannote[971].end 5636.07846875
transcript.pyannote[972].speaker SPEAKER_01
transcript.pyannote[972].start 5636.68596875
transcript.pyannote[972].end 5643.99284375
transcript.pyannote[973].speaker SPEAKER_01
transcript.pyannote[973].start 5644.87034375
transcript.pyannote[973].end 5646.25409375
transcript.pyannote[974].speaker SPEAKER_01
transcript.pyannote[974].start 5646.59159375
transcript.pyannote[974].end 5647.16534375
transcript.pyannote[975].speaker SPEAKER_01
transcript.pyannote[975].start 5647.94159375
transcript.pyannote[975].end 5649.98346875
transcript.pyannote[976].speaker SPEAKER_01
transcript.pyannote[976].start 5650.28721875
transcript.pyannote[976].end 5653.98284375
transcript.pyannote[977].speaker SPEAKER_01
transcript.pyannote[977].start 5654.32034375
transcript.pyannote[977].end 5655.40034375
transcript.pyannote[978].speaker SPEAKER_01
transcript.pyannote[978].start 5655.88971875
transcript.pyannote[978].end 5658.48846875
transcript.pyannote[979].speaker SPEAKER_01
transcript.pyannote[979].start 5659.16346875
transcript.pyannote[979].end 5662.13346875
transcript.pyannote[980].speaker SPEAKER_01
transcript.pyannote[980].start 5663.07846875
transcript.pyannote[980].end 5663.51721875
transcript.pyannote[981].speaker SPEAKER_01
transcript.pyannote[981].start 5663.82096875
transcript.pyannote[981].end 5667.43221875
transcript.pyannote[982].speaker SPEAKER_01
transcript.pyannote[982].start 5668.15784375
transcript.pyannote[982].end 5669.20409375
transcript.pyannote[983].speaker SPEAKER_01
transcript.pyannote[983].start 5670.06471875
transcript.pyannote[983].end 5676.86534375
transcript.pyannote[984].speaker SPEAKER_01
transcript.pyannote[984].start 5677.59096875
transcript.pyannote[984].end 5679.19409375
transcript.pyannote[985].speaker SPEAKER_01
transcript.pyannote[985].start 5679.36284375
transcript.pyannote[985].end 5680.22346875
transcript.pyannote[986].speaker SPEAKER_23
transcript.pyannote[986].start 5680.22346875
transcript.pyannote[986].end 5680.25721875
transcript.pyannote[987].speaker SPEAKER_02
transcript.pyannote[987].start 5680.98284375
transcript.pyannote[987].end 5681.20221875
transcript.pyannote[988].speaker SPEAKER_01
transcript.pyannote[988].start 5681.20221875
transcript.pyannote[988].end 5681.21909375
transcript.pyannote[989].speaker SPEAKER_23
transcript.pyannote[989].start 5681.21909375
transcript.pyannote[989].end 5681.23596875
transcript.pyannote[990].speaker SPEAKER_01
transcript.pyannote[990].start 5681.23596875
transcript.pyannote[990].end 5681.97846875
transcript.pyannote[991].speaker SPEAKER_23
transcript.pyannote[991].start 5681.97846875
transcript.pyannote[991].end 5700.96284375
transcript.pyannote[992].speaker SPEAKER_01
transcript.pyannote[992].start 5700.45659375
transcript.pyannote[992].end 5705.56971875
transcript.pyannote[993].speaker SPEAKER_01
transcript.pyannote[993].start 5706.14346875
transcript.pyannote[993].end 5708.42159375
transcript.pyannote[994].speaker SPEAKER_01
transcript.pyannote[994].start 5708.72534375
transcript.pyannote[994].end 5719.20471875
transcript.pyannote[995].speaker SPEAKER_01
transcript.pyannote[995].start 5719.81221875
transcript.pyannote[995].end 5722.76534375
transcript.pyannote[996].speaker SPEAKER_02
transcript.pyannote[996].start 5722.76534375
transcript.pyannote[996].end 5723.13659375
transcript.pyannote[997].speaker SPEAKER_01
transcript.pyannote[997].start 5723.23784375
transcript.pyannote[997].end 5725.53284375
transcript.pyannote[998].speaker SPEAKER_02
transcript.pyannote[998].start 5725.53284375
transcript.pyannote[998].end 5725.65096875
transcript.pyannote[999].speaker SPEAKER_01
transcript.pyannote[999].start 5726.12346875
transcript.pyannote[999].end 5744.38221875
transcript.pyannote[1000].speaker SPEAKER_23
transcript.pyannote[1000].start 5738.88096875
transcript.pyannote[1000].end 5739.50534375
transcript.pyannote[1001].speaker SPEAKER_02
transcript.pyannote[1001].start 5744.33159375
transcript.pyannote[1001].end 5744.80409375
transcript.pyannote[1002].speaker SPEAKER_01
transcript.pyannote[1002].start 5744.60159375
transcript.pyannote[1002].end 5748.28034375
transcript.pyannote[1003].speaker SPEAKER_02
transcript.pyannote[1003].start 5748.16221875
transcript.pyannote[1003].end 5748.58409375
transcript.pyannote[1004].speaker SPEAKER_01
transcript.pyannote[1004].start 5748.43221875
transcript.pyannote[1004].end 5756.11034375
transcript.pyannote[1005].speaker SPEAKER_27
transcript.pyannote[1005].start 5756.26221875
transcript.pyannote[1005].end 5758.43909375
transcript.pyannote[1006].speaker SPEAKER_01
transcript.pyannote[1006].start 5758.43909375
transcript.pyannote[1006].end 5759.63721875
transcript.pyannote[1007].speaker SPEAKER_01
transcript.pyannote[1007].start 5759.97471875
transcript.pyannote[1007].end 5760.81846875
transcript.pyannote[1008].speaker SPEAKER_01
transcript.pyannote[1008].start 5761.52721875
transcript.pyannote[1008].end 5762.15159375
transcript.pyannote[1009].speaker SPEAKER_01
transcript.pyannote[1009].start 5762.38784375
transcript.pyannote[1009].end 5763.16409375
transcript.pyannote[1010].speaker SPEAKER_03
transcript.pyannote[1010].start 5765.81346875
transcript.pyannote[1010].end 5770.40346875
transcript.pyannote[1011].speaker SPEAKER_12
transcript.pyannote[1011].start 5778.55409375
transcript.pyannote[1011].end 5779.83659375
transcript.pyannote[1012].speaker SPEAKER_13
transcript.pyannote[1012].start 5787.17721875
transcript.pyannote[1012].end 5788.47659375
transcript.pyannote[1013].speaker SPEAKER_02
transcript.pyannote[1013].start 5794.18034375
transcript.pyannote[1013].end 5796.03659375
transcript.pyannote[1014].speaker SPEAKER_13
transcript.pyannote[1014].start 5797.65659375
transcript.pyannote[1014].end 5798.36534375
transcript.pyannote[1015].speaker SPEAKER_13
transcript.pyannote[1015].start 5799.85034375
transcript.pyannote[1015].end 5801.89221875
transcript.pyannote[1016].speaker SPEAKER_03
transcript.pyannote[1016].start 5802.19596875
transcript.pyannote[1016].end 5802.98909375
transcript.pyannote[1017].speaker SPEAKER_13
transcript.pyannote[1017].start 5806.61721875
transcript.pyannote[1017].end 5807.22471875
transcript.pyannote[1018].speaker SPEAKER_13
transcript.pyannote[1018].start 5807.64659375
transcript.pyannote[1018].end 5808.67596875
transcript.pyannote[1019].speaker SPEAKER_13
transcript.pyannote[1019].start 5808.77721875
transcript.pyannote[1019].end 5854.84596875
transcript.pyannote[1020].speaker SPEAKER_02
transcript.pyannote[1020].start 5815.89846875
transcript.pyannote[1020].end 5816.37096875
transcript.pyannote[1021].speaker SPEAKER_21
transcript.pyannote[1021].start 5826.27659375
transcript.pyannote[1021].end 5826.69846875
transcript.pyannote[1022].speaker SPEAKER_02
transcript.pyannote[1022].start 5854.77846875
transcript.pyannote[1022].end 5855.20034375
transcript.pyannote[1023].speaker SPEAKER_13
transcript.pyannote[1023].start 5855.58846875
transcript.pyannote[1023].end 5858.11971875
transcript.pyannote[1024].speaker SPEAKER_13
transcript.pyannote[1024].start 5858.49096875
transcript.pyannote[1024].end 5862.11909375
transcript.pyannote[1025].speaker SPEAKER_27
transcript.pyannote[1025].start 5863.09784375
transcript.pyannote[1025].end 5865.13971875
transcript.pyannote[1026].speaker SPEAKER_27
transcript.pyannote[1026].start 5865.39284375
transcript.pyannote[1026].end 5866.27034375
transcript.pyannote[1027].speaker SPEAKER_13
transcript.pyannote[1027].start 5866.21971875
transcript.pyannote[1027].end 5868.32909375
transcript.pyannote[1028].speaker SPEAKER_27
transcript.pyannote[1028].start 5868.22784375
transcript.pyannote[1028].end 5868.46409375
transcript.pyannote[1029].speaker SPEAKER_13
transcript.pyannote[1029].start 5868.46409375
transcript.pyannote[1029].end 5872.46346875
transcript.pyannote[1030].speaker SPEAKER_27
transcript.pyannote[1030].start 5868.48096875
transcript.pyannote[1030].end 5868.54846875
transcript.pyannote[1031].speaker SPEAKER_27
transcript.pyannote[1031].start 5871.58596875
transcript.pyannote[1031].end 5873.18909375
transcript.pyannote[1032].speaker SPEAKER_27
transcript.pyannote[1032].start 5873.96534375
transcript.pyannote[1032].end 5874.16784375
transcript.pyannote[1033].speaker SPEAKER_13
transcript.pyannote[1033].start 5874.03284375
transcript.pyannote[1033].end 5882.63909375
transcript.pyannote[1034].speaker SPEAKER_02
transcript.pyannote[1034].start 5882.57159375
transcript.pyannote[1034].end 5882.95971875
transcript.pyannote[1035].speaker SPEAKER_13
transcript.pyannote[1035].start 5882.85846875
transcript.pyannote[1035].end 5905.72409375
transcript.pyannote[1036].speaker SPEAKER_02
transcript.pyannote[1036].start 5892.98346875
transcript.pyannote[1036].end 5893.33784375
transcript.pyannote[1037].speaker SPEAKER_13
transcript.pyannote[1037].start 5905.82534375
transcript.pyannote[1037].end 5919.22409375
transcript.pyannote[1038].speaker SPEAKER_27
transcript.pyannote[1038].start 5919.22409375
transcript.pyannote[1038].end 5919.57846875
transcript.pyannote[1039].speaker SPEAKER_27
transcript.pyannote[1039].start 5920.03409375
transcript.pyannote[1039].end 5920.35471875
transcript.pyannote[1040].speaker SPEAKER_27
transcript.pyannote[1040].start 5920.87784375
transcript.pyannote[1040].end 5932.47096875
transcript.pyannote[1041].speaker SPEAKER_27
transcript.pyannote[1041].start 5932.67346875
transcript.pyannote[1041].end 5934.22596875
transcript.pyannote[1042].speaker SPEAKER_13
transcript.pyannote[1042].start 5934.22596875
transcript.pyannote[1042].end 5971.35096875
transcript.pyannote[1043].speaker SPEAKER_00
transcript.pyannote[1043].start 5941.38096875
transcript.pyannote[1043].end 5941.41471875
transcript.pyannote[1044].speaker SPEAKER_02
transcript.pyannote[1044].start 5941.41471875
transcript.pyannote[1044].end 5941.93784375
transcript.pyannote[1045].speaker SPEAKER_13
transcript.pyannote[1045].start 5972.21159375
transcript.pyannote[1045].end 5989.86284375
transcript.pyannote[1046].speaker SPEAKER_13
transcript.pyannote[1046].start 5990.36909375
transcript.pyannote[1046].end 6026.22846875
transcript.pyannote[1047].speaker SPEAKER_00
transcript.pyannote[1047].start 6005.30346875
transcript.pyannote[1047].end 6005.35409375
transcript.pyannote[1048].speaker SPEAKER_00
transcript.pyannote[1048].start 6005.60721875
transcript.pyannote[1048].end 6005.69159375
transcript.pyannote[1049].speaker SPEAKER_13
transcript.pyannote[1049].start 6026.24534375
transcript.pyannote[1049].end 6026.26221875
transcript.pyannote[1050].speaker SPEAKER_13
transcript.pyannote[1050].start 6026.29596875
transcript.pyannote[1050].end 6026.85284375
transcript.pyannote[1051].speaker SPEAKER_02
transcript.pyannote[1051].start 6026.61659375
transcript.pyannote[1051].end 6027.47721875
transcript.pyannote[1052].speaker SPEAKER_13
transcript.pyannote[1052].start 6027.12284375
transcript.pyannote[1052].end 6029.11409375
transcript.pyannote[1053].speaker SPEAKER_13
transcript.pyannote[1053].start 6029.31659375
transcript.pyannote[1053].end 6034.78409375
transcript.pyannote[1054].speaker SPEAKER_13
transcript.pyannote[1054].start 6035.18909375
transcript.pyannote[1054].end 6037.53471875
transcript.pyannote[1055].speaker SPEAKER_13
transcript.pyannote[1055].start 6037.83846875
transcript.pyannote[1055].end 6057.64971875
transcript.pyannote[1056].speaker SPEAKER_27
transcript.pyannote[1056].start 6054.44346875
transcript.pyannote[1056].end 6054.49409375
transcript.pyannote[1057].speaker SPEAKER_27
transcript.pyannote[1057].start 6056.72159375
transcript.pyannote[1057].end 6057.31221875
transcript.pyannote[1058].speaker SPEAKER_27
transcript.pyannote[1058].start 6057.64971875
transcript.pyannote[1058].end 6059.94471875
transcript.pyannote[1059].speaker SPEAKER_27
transcript.pyannote[1059].start 6060.24846875
transcript.pyannote[1059].end 6064.48409375
transcript.pyannote[1060].speaker SPEAKER_27
transcript.pyannote[1060].start 6064.95659375
transcript.pyannote[1060].end 6066.13784375
transcript.pyannote[1061].speaker SPEAKER_27
transcript.pyannote[1061].start 6066.89721875
transcript.pyannote[1061].end 6073.29284375
transcript.pyannote[1062].speaker SPEAKER_02
transcript.pyannote[1062].start 6073.29284375
transcript.pyannote[1062].end 6073.66409375
transcript.pyannote[1063].speaker SPEAKER_27
transcript.pyannote[1063].start 6073.59659375
transcript.pyannote[1063].end 6082.72596875
transcript.pyannote[1064].speaker SPEAKER_02
transcript.pyannote[1064].start 6075.80721875
transcript.pyannote[1064].end 6076.07721875
transcript.pyannote[1065].speaker SPEAKER_13
transcript.pyannote[1065].start 6080.98784375
transcript.pyannote[1065].end 6109.11846875
transcript.pyannote[1066].speaker SPEAKER_27
transcript.pyannote[1066].start 6084.27846875
transcript.pyannote[1066].end 6084.64971875
transcript.pyannote[1067].speaker SPEAKER_27
transcript.pyannote[1067].start 6105.42284375
transcript.pyannote[1067].end 6106.89096875
transcript.pyannote[1068].speaker SPEAKER_27
transcript.pyannote[1068].start 6109.11846875
transcript.pyannote[1068].end 6109.15221875
transcript.pyannote[1069].speaker SPEAKER_13
transcript.pyannote[1069].start 6109.15221875
transcript.pyannote[1069].end 6109.16909375
transcript.pyannote[1070].speaker SPEAKER_27
transcript.pyannote[1070].start 6109.16909375
transcript.pyannote[1070].end 6127.07346875
transcript.pyannote[1071].speaker SPEAKER_13
transcript.pyannote[1071].start 6112.96596875
transcript.pyannote[1071].end 6113.92784375
transcript.pyannote[1072].speaker SPEAKER_13
transcript.pyannote[1072].start 6120.22221875
transcript.pyannote[1072].end 6120.47534375
transcript.pyannote[1073].speaker SPEAKER_13
transcript.pyannote[1073].start 6125.52096875
transcript.pyannote[1073].end 6148.57221875
transcript.pyannote[1074].speaker SPEAKER_13
transcript.pyannote[1074].start 6148.82534375
transcript.pyannote[1074].end 6234.06096875
transcript.pyannote[1075].speaker SPEAKER_02
transcript.pyannote[1075].start 6173.64846875
transcript.pyannote[1075].end 6174.05346875
transcript.pyannote[1076].speaker SPEAKER_00
transcript.pyannote[1076].start 6216.69659375
transcript.pyannote[1076].end 6217.05096875
transcript.pyannote[1077].speaker SPEAKER_02
transcript.pyannote[1077].start 6224.44221875
transcript.pyannote[1077].end 6224.52659375
transcript.pyannote[1078].speaker SPEAKER_02
transcript.pyannote[1078].start 6224.59409375
transcript.pyannote[1078].end 6224.89784375
transcript.pyannote[1079].speaker SPEAKER_02
transcript.pyannote[1079].start 6226.48409375
transcript.pyannote[1079].end 6226.83846875
transcript.pyannote[1080].speaker SPEAKER_13
transcript.pyannote[1080].start 6234.19596875
transcript.pyannote[1080].end 6234.43221875
transcript.pyannote[1081].speaker SPEAKER_02
transcript.pyannote[1081].start 6234.43221875
transcript.pyannote[1081].end 6234.51659375
transcript.pyannote[1082].speaker SPEAKER_13
transcript.pyannote[1082].start 6235.59659375
transcript.pyannote[1082].end 6236.23784375
transcript.pyannote[1083].speaker SPEAKER_13
transcript.pyannote[1083].start 6236.38971875
transcript.pyannote[1083].end 6241.50284375
transcript.pyannote[1084].speaker SPEAKER_13
transcript.pyannote[1084].start 6242.26221875
transcript.pyannote[1084].end 6243.51096875
transcript.pyannote[1085].speaker SPEAKER_13
transcript.pyannote[1085].start 6243.74721875
transcript.pyannote[1085].end 6245.28284375
transcript.pyannote[1086].speaker SPEAKER_13
transcript.pyannote[1086].start 6245.46846875
transcript.pyannote[1086].end 6247.54409375
transcript.pyannote[1087].speaker SPEAKER_13
transcript.pyannote[1087].start 6247.91534375
transcript.pyannote[1087].end 6256.65659375
transcript.pyannote[1088].speaker SPEAKER_13
transcript.pyannote[1088].start 6256.94346875
transcript.pyannote[1088].end 6264.33471875
transcript.pyannote[1089].speaker SPEAKER_27
transcript.pyannote[1089].start 6264.58784375
transcript.pyannote[1089].end 6275.48909375
transcript.pyannote[1090].speaker SPEAKER_27
transcript.pyannote[1090].start 6275.53971875
transcript.pyannote[1090].end 6281.61471875
transcript.pyannote[1091].speaker SPEAKER_27
transcript.pyannote[1091].start 6281.78346875
transcript.pyannote[1091].end 6284.83784375
transcript.pyannote[1092].speaker SPEAKER_13
transcript.pyannote[1092].start 6282.79596875
transcript.pyannote[1092].end 6285.86721875
transcript.pyannote[1093].speaker SPEAKER_27
transcript.pyannote[1093].start 6285.86721875
transcript.pyannote[1093].end 6285.95159375
transcript.pyannote[1094].speaker SPEAKER_13
transcript.pyannote[1094].start 6285.95159375
transcript.pyannote[1094].end 6287.38596875
transcript.pyannote[1095].speaker SPEAKER_27
transcript.pyannote[1095].start 6286.00221875
transcript.pyannote[1095].end 6309.81284375
transcript.pyannote[1096].speaker SPEAKER_02
transcript.pyannote[1096].start 6299.26596875
transcript.pyannote[1096].end 6299.67096875
transcript.pyannote[1097].speaker SPEAKER_13
transcript.pyannote[1097].start 6309.81284375
transcript.pyannote[1097].end 6359.77971875
transcript.pyannote[1098].speaker SPEAKER_27
transcript.pyannote[1098].start 6359.91471875
transcript.pyannote[1098].end 6366.34409375
transcript.pyannote[1099].speaker SPEAKER_27
transcript.pyannote[1099].start 6366.61409375
transcript.pyannote[1099].end 6384.19784375
transcript.pyannote[1100].speaker SPEAKER_13
transcript.pyannote[1100].start 6384.19784375
transcript.pyannote[1100].end 6386.03721875
transcript.pyannote[1101].speaker SPEAKER_13
transcript.pyannote[1101].start 6386.22284375
transcript.pyannote[1101].end 6391.48784375
transcript.pyannote[1102].speaker SPEAKER_13
transcript.pyannote[1102].start 6391.89284375
transcript.pyannote[1102].end 6392.66909375
transcript.pyannote[1103].speaker SPEAKER_03
transcript.pyannote[1103].start 6394.23846875
transcript.pyannote[1103].end 6404.65034375
transcript.pyannote[1104].speaker SPEAKER_12
transcript.pyannote[1104].start 6411.95721875
transcript.pyannote[1104].end 6412.91909375
transcript.pyannote[1105].speaker SPEAKER_12
transcript.pyannote[1105].start 6412.96971875
transcript.pyannote[1105].end 6412.98659375
transcript.pyannote[1106].speaker SPEAKER_12
transcript.pyannote[1106].start 6413.17221875
transcript.pyannote[1106].end 6415.99034375
transcript.pyannote[1107].speaker SPEAKER_12
transcript.pyannote[1107].start 6416.15909375
transcript.pyannote[1107].end 6416.98596875
transcript.pyannote[1108].speaker SPEAKER_03
transcript.pyannote[1108].start 6417.01971875
transcript.pyannote[1108].end 6418.63971875
transcript.pyannote[1109].speaker SPEAKER_12
transcript.pyannote[1109].start 6419.04471875
transcript.pyannote[1109].end 6419.50034375
transcript.pyannote[1110].speaker SPEAKER_03
transcript.pyannote[1110].start 6419.82096875
transcript.pyannote[1110].end 6420.41159375
transcript.pyannote[1111].speaker SPEAKER_12
transcript.pyannote[1111].start 6420.41159375
transcript.pyannote[1111].end 6422.33534375
transcript.pyannote[1112].speaker SPEAKER_12
transcript.pyannote[1112].start 6423.29721875
transcript.pyannote[1112].end 6492.51846875
transcript.pyannote[1113].speaker SPEAKER_27
transcript.pyannote[1113].start 6491.35409375
transcript.pyannote[1113].end 6491.59034375
transcript.pyannote[1114].speaker SPEAKER_27
transcript.pyannote[1114].start 6492.94034375
transcript.pyannote[1114].end 6505.66409375
transcript.pyannote[1115].speaker SPEAKER_02
transcript.pyannote[1115].start 6502.10346875
transcript.pyannote[1115].end 6502.39034375
transcript.pyannote[1116].speaker SPEAKER_02
transcript.pyannote[1116].start 6505.84971875
transcript.pyannote[1116].end 6506.22096875
transcript.pyannote[1117].speaker SPEAKER_27
transcript.pyannote[1117].start 6506.13659375
transcript.pyannote[1117].end 6510.81096875
transcript.pyannote[1118].speaker SPEAKER_02
transcript.pyannote[1118].start 6510.81096875
transcript.pyannote[1118].end 6511.18221875
transcript.pyannote[1119].speaker SPEAKER_27
transcript.pyannote[1119].start 6510.96284375
transcript.pyannote[1119].end 6524.86784375
transcript.pyannote[1120].speaker SPEAKER_27
transcript.pyannote[1120].start 6525.15471875
transcript.pyannote[1120].end 6536.54534375
transcript.pyannote[1121].speaker SPEAKER_27
transcript.pyannote[1121].start 6536.73096875
transcript.pyannote[1121].end 6538.87409375
transcript.pyannote[1122].speaker SPEAKER_27
transcript.pyannote[1122].start 6539.12721875
transcript.pyannote[1122].end 6541.82721875
transcript.pyannote[1123].speaker SPEAKER_27
transcript.pyannote[1123].start 6542.19846875
transcript.pyannote[1123].end 6571.34159375
transcript.pyannote[1124].speaker SPEAKER_25
transcript.pyannote[1124].start 6560.15346875
transcript.pyannote[1124].end 6560.54159375
transcript.pyannote[1125].speaker SPEAKER_00
transcript.pyannote[1125].start 6560.54159375
transcript.pyannote[1125].end 6560.64284375
transcript.pyannote[1126].speaker SPEAKER_25
transcript.pyannote[1126].start 6563.78159375
transcript.pyannote[1126].end 6563.81534375
transcript.pyannote[1127].speaker SPEAKER_28
transcript.pyannote[1127].start 6563.81534375
transcript.pyannote[1127].end 6564.84471875
transcript.pyannote[1128].speaker SPEAKER_27
transcript.pyannote[1128].start 6571.52721875
transcript.pyannote[1128].end 6575.96534375
transcript.pyannote[1129].speaker SPEAKER_12
transcript.pyannote[1129].start 6574.86846875
transcript.pyannote[1129].end 6580.57221875
transcript.pyannote[1130].speaker SPEAKER_12
transcript.pyannote[1130].start 6580.89284375
transcript.pyannote[1130].end 6605.36159375
transcript.pyannote[1131].speaker SPEAKER_12
transcript.pyannote[1131].start 6605.69909375
transcript.pyannote[1131].end 6620.29596875
transcript.pyannote[1132].speaker SPEAKER_05
transcript.pyannote[1132].start 6620.29596875
transcript.pyannote[1132].end 6620.58284375
transcript.pyannote[1133].speaker SPEAKER_12
transcript.pyannote[1133].start 6620.46471875
transcript.pyannote[1133].end 6621.67971875
transcript.pyannote[1134].speaker SPEAKER_05
transcript.pyannote[1134].start 6621.37596875
transcript.pyannote[1134].end 6625.24034375
transcript.pyannote[1135].speaker SPEAKER_12
transcript.pyannote[1135].start 6622.59096875
transcript.pyannote[1135].end 6628.02471875
transcript.pyannote[1136].speaker SPEAKER_05
transcript.pyannote[1136].start 6625.69596875
transcript.pyannote[1136].end 6626.53971875
transcript.pyannote[1137].speaker SPEAKER_12
transcript.pyannote[1137].start 6628.58159375
transcript.pyannote[1137].end 6661.60596875
transcript.pyannote[1138].speaker SPEAKER_12
transcript.pyannote[1138].start 6661.96034375
transcript.pyannote[1138].end 6669.04784375
transcript.pyannote[1139].speaker SPEAKER_12
transcript.pyannote[1139].start 6669.87471875
transcript.pyannote[1139].end 6670.87034375
transcript.pyannote[1140].speaker SPEAKER_12
transcript.pyannote[1140].start 6671.10659375
transcript.pyannote[1140].end 6694.15784375
transcript.pyannote[1141].speaker SPEAKER_12
transcript.pyannote[1141].start 6694.24221875
transcript.pyannote[1141].end 6708.58596875
transcript.pyannote[1142].speaker SPEAKER_27
transcript.pyannote[1142].start 6708.95721875
transcript.pyannote[1142].end 6711.55596875
transcript.pyannote[1143].speaker SPEAKER_23
transcript.pyannote[1143].start 6711.28596875
transcript.pyannote[1143].end 6718.69409375
transcript.pyannote[1144].speaker SPEAKER_12
transcript.pyannote[1144].start 6711.55596875
transcript.pyannote[1144].end 6711.58971875
transcript.pyannote[1145].speaker SPEAKER_27
transcript.pyannote[1145].start 6711.58971875
transcript.pyannote[1145].end 6711.62346875
transcript.pyannote[1146].speaker SPEAKER_12
transcript.pyannote[1146].start 6711.62346875
transcript.pyannote[1146].end 6711.67409375
transcript.pyannote[1147].speaker SPEAKER_27
transcript.pyannote[1147].start 6711.67409375
transcript.pyannote[1147].end 6711.85971875
transcript.pyannote[1148].speaker SPEAKER_02
transcript.pyannote[1148].start 6718.67721875
transcript.pyannote[1148].end 6719.08221875
transcript.pyannote[1149].speaker SPEAKER_23
transcript.pyannote[1149].start 6718.98096875
transcript.pyannote[1149].end 6729.51096875
transcript.pyannote[1150].speaker SPEAKER_23
transcript.pyannote[1150].start 6729.61221875
transcript.pyannote[1150].end 6736.37909375
transcript.pyannote[1151].speaker SPEAKER_23
transcript.pyannote[1151].start 6736.81784375
transcript.pyannote[1151].end 6759.88596875
transcript.pyannote[1152].speaker SPEAKER_23
transcript.pyannote[1152].start 6760.10534375
transcript.pyannote[1152].end 6764.86409375
transcript.pyannote[1153].speaker SPEAKER_12
transcript.pyannote[1153].start 6764.93159375
transcript.pyannote[1153].end 6781.38471875
transcript.pyannote[1154].speaker SPEAKER_28
transcript.pyannote[1154].start 6771.83346875
transcript.pyannote[1154].end 6771.90096875
transcript.pyannote[1155].speaker SPEAKER_12
transcript.pyannote[1155].start 6781.90784375
transcript.pyannote[1155].end 6803.28846875
transcript.pyannote[1156].speaker SPEAKER_23
transcript.pyannote[1156].start 6803.28846875
transcript.pyannote[1156].end 6814.84784375
transcript.pyannote[1157].speaker SPEAKER_23
transcript.pyannote[1157].start 6815.40471875
transcript.pyannote[1157].end 6819.03284375
transcript.pyannote[1158].speaker SPEAKER_23
transcript.pyannote[1158].start 6819.57284375
transcript.pyannote[1158].end 6820.88909375
transcript.pyannote[1159].speaker SPEAKER_23
transcript.pyannote[1159].start 6821.36159375
transcript.pyannote[1159].end 6822.52596875
transcript.pyannote[1160].speaker SPEAKER_23
transcript.pyannote[1160].start 6822.76221875
transcript.pyannote[1160].end 6828.39846875
transcript.pyannote[1161].speaker SPEAKER_23
transcript.pyannote[1161].start 6828.53346875
transcript.pyannote[1161].end 6833.86596875
transcript.pyannote[1162].speaker SPEAKER_23
transcript.pyannote[1162].start 6834.20346875
transcript.pyannote[1162].end 6838.47284375
transcript.pyannote[1163].speaker SPEAKER_12
transcript.pyannote[1163].start 6838.47284375
transcript.pyannote[1163].end 6871.54784375
transcript.pyannote[1164].speaker SPEAKER_23
transcript.pyannote[1164].start 6872.49284375
transcript.pyannote[1164].end 6889.18221875
transcript.pyannote[1165].speaker SPEAKER_23
transcript.pyannote[1165].start 6889.43534375
transcript.pyannote[1165].end 6911.89596875
transcript.pyannote[1166].speaker SPEAKER_23
transcript.pyannote[1166].start 6912.46971875
transcript.pyannote[1166].end 6916.89096875
transcript.pyannote[1167].speaker SPEAKER_12
transcript.pyannote[1167].start 6916.43534375
transcript.pyannote[1167].end 6935.53784375
transcript.pyannote[1168].speaker SPEAKER_12
transcript.pyannote[1168].start 6935.97659375
transcript.pyannote[1168].end 6943.51971875
transcript.pyannote[1169].speaker SPEAKER_12
transcript.pyannote[1169].start 6943.94159375
transcript.pyannote[1169].end 6949.96596875
transcript.pyannote[1170].speaker SPEAKER_12
transcript.pyannote[1170].start 6950.25284375
transcript.pyannote[1170].end 6964.68096875
transcript.pyannote[1171].speaker SPEAKER_12
transcript.pyannote[1171].start 6964.79909375
transcript.pyannote[1171].end 6987.76596875
transcript.pyannote[1172].speaker SPEAKER_12
transcript.pyannote[1172].start 6988.17096875
transcript.pyannote[1172].end 6989.03159375
transcript.pyannote[1173].speaker SPEAKER_12
transcript.pyannote[1173].start 6989.48721875
transcript.pyannote[1173].end 6991.46159375
transcript.pyannote[1174].speaker SPEAKER_12
transcript.pyannote[1174].start 6991.69784375
transcript.pyannote[1174].end 7001.75534375
transcript.pyannote[1175].speaker SPEAKER_12
transcript.pyannote[1175].start 7002.24471875
transcript.pyannote[1175].end 7003.89846875
transcript.pyannote[1176].speaker SPEAKER_12
transcript.pyannote[1176].start 7004.32034375
transcript.pyannote[1176].end 7014.59721875
transcript.pyannote[1177].speaker SPEAKER_23
transcript.pyannote[1177].start 7015.18784375
transcript.pyannote[1177].end 7016.63909375
transcript.pyannote[1178].speaker SPEAKER_23
transcript.pyannote[1178].start 7017.53346875
transcript.pyannote[1178].end 7024.73909375
transcript.pyannote[1179].speaker SPEAKER_23
transcript.pyannote[1179].start 7025.02596875
transcript.pyannote[1179].end 7033.93596875
transcript.pyannote[1180].speaker SPEAKER_23
transcript.pyannote[1180].start 7034.69534375
transcript.pyannote[1180].end 7051.46909375
transcript.pyannote[1181].speaker SPEAKER_12
transcript.pyannote[1181].start 7051.46909375
transcript.pyannote[1181].end 7053.15659375
transcript.pyannote[1182].speaker SPEAKER_03
transcript.pyannote[1182].start 7056.75096875
transcript.pyannote[1182].end 7058.74221875
transcript.pyannote[1183].speaker SPEAKER_16
transcript.pyannote[1183].start 7069.17096875
transcript.pyannote[1183].end 7071.06096875
transcript.pyannote[1184].speaker SPEAKER_03
transcript.pyannote[1184].start 7071.44909375
transcript.pyannote[1184].end 7072.24221875
transcript.pyannote[1185].speaker SPEAKER_03
transcript.pyannote[1185].start 7076.59596875
transcript.pyannote[1185].end 7076.61284375
transcript.pyannote[1186].speaker SPEAKER_16
transcript.pyannote[1186].start 7076.61284375
transcript.pyannote[1186].end 7076.62971875
transcript.pyannote[1187].speaker SPEAKER_03
transcript.pyannote[1187].start 7076.62971875
transcript.pyannote[1187].end 7076.96721875
transcript.pyannote[1188].speaker SPEAKER_16
transcript.pyannote[1188].start 7076.96721875
transcript.pyannote[1188].end 7077.11909375
transcript.pyannote[1189].speaker SPEAKER_03
transcript.pyannote[1189].start 7077.11909375
transcript.pyannote[1189].end 7077.16971875
transcript.pyannote[1190].speaker SPEAKER_16
transcript.pyannote[1190].start 7077.16971875
transcript.pyannote[1190].end 7077.22034375
transcript.pyannote[1191].speaker SPEAKER_16
transcript.pyannote[1191].start 7077.57471875
transcript.pyannote[1191].end 7079.98784375
transcript.pyannote[1192].speaker SPEAKER_16
transcript.pyannote[1192].start 7081.94534375
transcript.pyannote[1192].end 7081.96221875
transcript.pyannote[1193].speaker SPEAKER_16
transcript.pyannote[1193].start 7086.21471875
transcript.pyannote[1193].end 7089.23534375
transcript.pyannote[1194].speaker SPEAKER_16
transcript.pyannote[1194].start 7089.53909375
transcript.pyannote[1194].end 7093.09971875
transcript.pyannote[1195].speaker SPEAKER_16
transcript.pyannote[1195].start 7093.84221875
transcript.pyannote[1195].end 7097.36909375
transcript.pyannote[1196].speaker SPEAKER_16
transcript.pyannote[1196].start 7098.56721875
transcript.pyannote[1196].end 7100.69346875
transcript.pyannote[1197].speaker SPEAKER_27
transcript.pyannote[1197].start 7100.69346875
transcript.pyannote[1197].end 7102.04346875
transcript.pyannote[1198].speaker SPEAKER_16
transcript.pyannote[1198].start 7105.04721875
transcript.pyannote[1198].end 7105.80659375
transcript.pyannote[1199].speaker SPEAKER_16
transcript.pyannote[1199].start 7106.24534375
transcript.pyannote[1199].end 7107.20721875
transcript.pyannote[1200].speaker SPEAKER_16
transcript.pyannote[1200].start 7107.84846875
transcript.pyannote[1200].end 7111.22346875
transcript.pyannote[1201].speaker SPEAKER_16
transcript.pyannote[1201].start 7112.01659375
transcript.pyannote[1201].end 7117.21409375
transcript.pyannote[1202].speaker SPEAKER_16
transcript.pyannote[1202].start 7117.82159375
transcript.pyannote[1202].end 7119.57659375
transcript.pyannote[1203].speaker SPEAKER_16
transcript.pyannote[1203].start 7120.21784375
transcript.pyannote[1203].end 7125.63471875
transcript.pyannote[1204].speaker SPEAKER_16
transcript.pyannote[1204].start 7126.59659375
transcript.pyannote[1204].end 7129.71846875
transcript.pyannote[1205].speaker SPEAKER_16
transcript.pyannote[1205].start 7130.22471875
transcript.pyannote[1205].end 7134.94971875
transcript.pyannote[1206].speaker SPEAKER_16
transcript.pyannote[1206].start 7135.72596875
transcript.pyannote[1206].end 7137.02534375
transcript.pyannote[1207].speaker SPEAKER_16
transcript.pyannote[1207].start 7137.29534375
transcript.pyannote[1207].end 7145.17596875
transcript.pyannote[1208].speaker SPEAKER_16
transcript.pyannote[1208].start 7146.52596875
transcript.pyannote[1208].end 7150.10346875
transcript.pyannote[1209].speaker SPEAKER_16
transcript.pyannote[1209].start 7150.77846875
transcript.pyannote[1209].end 7151.67284375
transcript.pyannote[1210].speaker SPEAKER_27
transcript.pyannote[1210].start 7152.39846875
transcript.pyannote[1210].end 7156.66784375
transcript.pyannote[1211].speaker SPEAKER_16
transcript.pyannote[1211].start 7156.66784375
transcript.pyannote[1211].end 7164.56534375
transcript.pyannote[1212].speaker SPEAKER_27
transcript.pyannote[1212].start 7158.99659375
transcript.pyannote[1212].end 7160.48159375
transcript.pyannote[1213].speaker SPEAKER_16
transcript.pyannote[1213].start 7164.95346875
transcript.pyannote[1213].end 7166.35409375
transcript.pyannote[1214].speaker SPEAKER_16
transcript.pyannote[1214].start 7167.11346875
transcript.pyannote[1214].end 7169.44221875
transcript.pyannote[1215].speaker SPEAKER_02
transcript.pyannote[1215].start 7169.44221875
transcript.pyannote[1215].end 7169.69534375
transcript.pyannote[1216].speaker SPEAKER_16
transcript.pyannote[1216].start 7169.96534375
transcript.pyannote[1216].end 7172.42909375
transcript.pyannote[1217].speaker SPEAKER_16
transcript.pyannote[1217].start 7172.91846875
transcript.pyannote[1217].end 7181.13659375
transcript.pyannote[1218].speaker SPEAKER_16
transcript.pyannote[1218].start 7181.27159375
transcript.pyannote[1218].end 7183.63409375
transcript.pyannote[1219].speaker SPEAKER_16
transcript.pyannote[1219].start 7184.00534375
transcript.pyannote[1219].end 7192.52721875
transcript.pyannote[1220].speaker SPEAKER_16
transcript.pyannote[1220].start 7192.66221875
transcript.pyannote[1220].end 7199.56409375
transcript.pyannote[1221].speaker SPEAKER_27
transcript.pyannote[1221].start 7199.64846875
transcript.pyannote[1221].end 7199.98596875
transcript.pyannote[1222].speaker SPEAKER_27
transcript.pyannote[1222].start 7200.55971875
transcript.pyannote[1222].end 7202.88846875
transcript.pyannote[1223].speaker SPEAKER_27
transcript.pyannote[1223].start 7203.27659375
transcript.pyannote[1223].end 7203.93471875
transcript.pyannote[1224].speaker SPEAKER_27
transcript.pyannote[1224].start 7204.35659375
transcript.pyannote[1224].end 7205.77409375
transcript.pyannote[1225].speaker SPEAKER_27
transcript.pyannote[1225].start 7205.92596875
transcript.pyannote[1225].end 7210.33034375
transcript.pyannote[1226].speaker SPEAKER_16
transcript.pyannote[1226].start 7205.99346875
transcript.pyannote[1226].end 7207.10721875
transcript.pyannote[1227].speaker SPEAKER_16
transcript.pyannote[1227].start 7209.80721875
transcript.pyannote[1227].end 7210.21221875
transcript.pyannote[1228].speaker SPEAKER_02
transcript.pyannote[1228].start 7210.21221875
transcript.pyannote[1228].end 7210.26284375
transcript.pyannote[1229].speaker SPEAKER_27
transcript.pyannote[1229].start 7210.75221875
transcript.pyannote[1229].end 7216.99596875
transcript.pyannote[1230].speaker SPEAKER_02
transcript.pyannote[1230].start 7216.52346875
transcript.pyannote[1230].end 7217.82284375
transcript.pyannote[1231].speaker SPEAKER_27
transcript.pyannote[1231].start 7217.40096875
transcript.pyannote[1231].end 7221.95721875
transcript.pyannote[1232].speaker SPEAKER_16
transcript.pyannote[1232].start 7217.82284375
transcript.pyannote[1232].end 7217.87346875
transcript.pyannote[1233].speaker SPEAKER_16
transcript.pyannote[1233].start 7221.55221875
transcript.pyannote[1233].end 7228.65659375
transcript.pyannote[1234].speaker SPEAKER_27
transcript.pyannote[1234].start 7223.27346875
transcript.pyannote[1234].end 7223.56034375
transcript.pyannote[1235].speaker SPEAKER_16
transcript.pyannote[1235].start 7229.53409375
transcript.pyannote[1235].end 7232.90909375
transcript.pyannote[1236].speaker SPEAKER_16
transcript.pyannote[1236].start 7233.01034375
transcript.pyannote[1236].end 7233.68534375
transcript.pyannote[1237].speaker SPEAKER_16
transcript.pyannote[1237].start 7235.45721875
transcript.pyannote[1237].end 7238.42721875
transcript.pyannote[1238].speaker SPEAKER_16
transcript.pyannote[1238].start 7238.79846875
transcript.pyannote[1238].end 7242.86534375
transcript.pyannote[1239].speaker SPEAKER_16
transcript.pyannote[1239].start 7243.69221875
transcript.pyannote[1239].end 7250.50971875
transcript.pyannote[1240].speaker SPEAKER_16
transcript.pyannote[1240].start 7251.55596875
transcript.pyannote[1240].end 7252.14659375
transcript.pyannote[1241].speaker SPEAKER_16
transcript.pyannote[1241].start 7253.58096875
transcript.pyannote[1241].end 7258.44096875
transcript.pyannote[1242].speaker SPEAKER_16
transcript.pyannote[1242].start 7259.16659375
transcript.pyannote[1242].end 7260.21284375
transcript.pyannote[1243].speaker SPEAKER_16
transcript.pyannote[1243].start 7261.00596875
transcript.pyannote[1243].end 7262.06909375
transcript.pyannote[1244].speaker SPEAKER_16
transcript.pyannote[1244].start 7263.53721875
transcript.pyannote[1244].end 7264.16159375
transcript.pyannote[1245].speaker SPEAKER_16
transcript.pyannote[1245].start 7265.22471875
transcript.pyannote[1245].end 7265.88284375
transcript.pyannote[1246].speaker SPEAKER_16
transcript.pyannote[1246].start 7266.23721875
transcript.pyannote[1246].end 7267.95846875
transcript.pyannote[1247].speaker SPEAKER_16
transcript.pyannote[1247].start 7268.27909375
transcript.pyannote[1247].end 7269.15659375
transcript.pyannote[1248].speaker SPEAKER_16
transcript.pyannote[1248].start 7269.69659375
transcript.pyannote[1248].end 7271.63721875
transcript.pyannote[1249].speaker SPEAKER_16
transcript.pyannote[1249].start 7272.29534375
transcript.pyannote[1249].end 7274.16846875
transcript.pyannote[1250].speaker SPEAKER_16
transcript.pyannote[1250].start 7274.64096875
transcript.pyannote[1250].end 7275.53534375
transcript.pyannote[1251].speaker SPEAKER_16
transcript.pyannote[1251].start 7276.71659375
transcript.pyannote[1251].end 7278.87659375
transcript.pyannote[1252].speaker SPEAKER_16
transcript.pyannote[1252].start 7279.63596875
transcript.pyannote[1252].end 7281.45846875
transcript.pyannote[1253].speaker SPEAKER_16
transcript.pyannote[1253].start 7282.06596875
transcript.pyannote[1253].end 7283.71971875
transcript.pyannote[1254].speaker SPEAKER_16
transcript.pyannote[1254].start 7285.30596875
transcript.pyannote[1254].end 7288.00596875
transcript.pyannote[1255].speaker SPEAKER_16
transcript.pyannote[1255].start 7289.44034375
transcript.pyannote[1255].end 7292.91659375
transcript.pyannote[1256].speaker SPEAKER_16
transcript.pyannote[1256].start 7293.47346875
transcript.pyannote[1256].end 7296.24096875
transcript.pyannote[1257].speaker SPEAKER_02
transcript.pyannote[1257].start 7296.25784375
transcript.pyannote[1257].end 7296.47721875
transcript.pyannote[1258].speaker SPEAKER_16
transcript.pyannote[1258].start 7297.13534375
transcript.pyannote[1258].end 7298.53596875
transcript.pyannote[1259].speaker SPEAKER_16
transcript.pyannote[1259].start 7298.97471875
transcript.pyannote[1259].end 7299.66659375
transcript.pyannote[1260].speaker SPEAKER_16
transcript.pyannote[1260].start 7299.93659375
transcript.pyannote[1260].end 7300.37534375
transcript.pyannote[1261].speaker SPEAKER_16
transcript.pyannote[1261].start 7301.38784375
transcript.pyannote[1261].end 7302.31596875
transcript.pyannote[1262].speaker SPEAKER_16
transcript.pyannote[1262].start 7302.92346875
transcript.pyannote[1262].end 7304.08784375
transcript.pyannote[1263].speaker SPEAKER_16
transcript.pyannote[1263].start 7305.04971875
transcript.pyannote[1263].end 7307.71596875
transcript.pyannote[1264].speaker SPEAKER_16
transcript.pyannote[1264].start 7308.45846875
transcript.pyannote[1264].end 7312.22159375
transcript.pyannote[1265].speaker SPEAKER_16
transcript.pyannote[1265].start 7312.60971875
transcript.pyannote[1265].end 7314.04409375
transcript.pyannote[1266].speaker SPEAKER_16
transcript.pyannote[1266].start 7314.38159375
transcript.pyannote[1266].end 7318.66784375
transcript.pyannote[1267].speaker SPEAKER_16
transcript.pyannote[1267].start 7319.35971875
transcript.pyannote[1267].end 7321.11471875
transcript.pyannote[1268].speaker SPEAKER_16
transcript.pyannote[1268].start 7321.40159375
transcript.pyannote[1268].end 7322.75159375
transcript.pyannote[1269].speaker SPEAKER_16
transcript.pyannote[1269].start 7323.54471875
transcript.pyannote[1269].end 7324.21971875
transcript.pyannote[1270].speaker SPEAKER_16
transcript.pyannote[1270].start 7324.87784375
transcript.pyannote[1270].end 7325.36721875
transcript.pyannote[1271].speaker SPEAKER_16
transcript.pyannote[1271].start 7326.16034375
transcript.pyannote[1271].end 7331.15534375
transcript.pyannote[1272].speaker SPEAKER_16
transcript.pyannote[1272].start 7331.79659375
transcript.pyannote[1272].end 7336.87596875
transcript.pyannote[1273].speaker SPEAKER_16
transcript.pyannote[1273].start 7337.56784375
transcript.pyannote[1273].end 7338.10784375
transcript.pyannote[1274].speaker SPEAKER_16
transcript.pyannote[1274].start 7338.25971875
transcript.pyannote[1274].end 7340.60534375
transcript.pyannote[1275].speaker SPEAKER_16
transcript.pyannote[1275].start 7340.72346875
transcript.pyannote[1275].end 7344.85784375
transcript.pyannote[1276].speaker SPEAKER_16
transcript.pyannote[1276].start 7344.97596875
transcript.pyannote[1276].end 7346.61284375
transcript.pyannote[1277].speaker SPEAKER_02
transcript.pyannote[1277].start 7346.61284375
transcript.pyannote[1277].end 7346.95034375
transcript.pyannote[1278].speaker SPEAKER_16
transcript.pyannote[1278].start 7346.96721875
transcript.pyannote[1278].end 7347.99659375
transcript.pyannote[1279].speaker SPEAKER_02
transcript.pyannote[1279].start 7347.99659375
transcript.pyannote[1279].end 7348.31721875
transcript.pyannote[1280].speaker SPEAKER_16
transcript.pyannote[1280].start 7348.51971875
transcript.pyannote[1280].end 7353.02534375
transcript.pyannote[1281].speaker SPEAKER_16
transcript.pyannote[1281].start 7353.09284375
transcript.pyannote[1281].end 7355.62409375
transcript.pyannote[1282].speaker SPEAKER_16
transcript.pyannote[1282].start 7356.43409375
transcript.pyannote[1282].end 7356.95721875
transcript.pyannote[1283].speaker SPEAKER_16
transcript.pyannote[1283].start 7357.80096875
transcript.pyannote[1283].end 7359.45471875
transcript.pyannote[1284].speaker SPEAKER_16
transcript.pyannote[1284].start 7360.51784375
transcript.pyannote[1284].end 7361.61471875
transcript.pyannote[1285].speaker SPEAKER_16
transcript.pyannote[1285].start 7362.22221875
transcript.pyannote[1285].end 7362.72846875
transcript.pyannote[1286].speaker SPEAKER_16
transcript.pyannote[1286].start 7364.48346875
transcript.pyannote[1286].end 7365.52971875
transcript.pyannote[1287].speaker SPEAKER_16
transcript.pyannote[1287].start 7366.12034375
transcript.pyannote[1287].end 7366.93034375
transcript.pyannote[1288].speaker SPEAKER_16
transcript.pyannote[1288].start 7367.28471875
transcript.pyannote[1288].end 7368.29721875
transcript.pyannote[1289].speaker SPEAKER_16
transcript.pyannote[1289].start 7368.66846875
transcript.pyannote[1289].end 7374.32159375
transcript.pyannote[1290].speaker SPEAKER_16
transcript.pyannote[1290].start 7375.55346875
transcript.pyannote[1290].end 7377.94971875
transcript.pyannote[1291].speaker SPEAKER_16
transcript.pyannote[1291].start 7378.11846875
transcript.pyannote[1291].end 7378.23659375
transcript.pyannote[1292].speaker SPEAKER_16
transcript.pyannote[1292].start 7378.28721875
transcript.pyannote[1292].end 7379.38409375
transcript.pyannote[1293].speaker SPEAKER_16
transcript.pyannote[1293].start 7379.97471875
transcript.pyannote[1293].end 7383.92346875
transcript.pyannote[1294].speaker SPEAKER_02
transcript.pyannote[1294].start 7383.85596875
transcript.pyannote[1294].end 7384.12596875
transcript.pyannote[1295].speaker SPEAKER_16
transcript.pyannote[1295].start 7384.10909375
transcript.pyannote[1295].end 7387.34909375
transcript.pyannote[1296].speaker SPEAKER_16
transcript.pyannote[1296].start 7387.61909375
transcript.pyannote[1296].end 7390.09971875
transcript.pyannote[1297].speaker SPEAKER_16
transcript.pyannote[1297].start 7390.50471875
transcript.pyannote[1297].end 7391.38221875
transcript.pyannote[1298].speaker SPEAKER_16
transcript.pyannote[1298].start 7392.29346875
transcript.pyannote[1298].end 7395.71909375
transcript.pyannote[1299].speaker SPEAKER_16
transcript.pyannote[1299].start 7395.98909375
transcript.pyannote[1299].end 7397.62596875
transcript.pyannote[1300].speaker SPEAKER_16
transcript.pyannote[1300].start 7398.04784375
transcript.pyannote[1300].end 7398.60471875
transcript.pyannote[1301].speaker SPEAKER_16
transcript.pyannote[1301].start 7399.87034375
transcript.pyannote[1301].end 7403.38034375
transcript.pyannote[1302].speaker SPEAKER_16
transcript.pyannote[1302].start 7403.80221875
transcript.pyannote[1302].end 7405.89471875
transcript.pyannote[1303].speaker SPEAKER_02
transcript.pyannote[1303].start 7405.99596875
transcript.pyannote[1303].end 7406.02971875
transcript.pyannote[1304].speaker SPEAKER_27
transcript.pyannote[1304].start 7406.02971875
transcript.pyannote[1304].end 7406.24909375
transcript.pyannote[1305].speaker SPEAKER_02
transcript.pyannote[1305].start 7406.24909375
transcript.pyannote[1305].end 7406.26596875
transcript.pyannote[1306].speaker SPEAKER_16
transcript.pyannote[1306].start 7407.29534375
transcript.pyannote[1306].end 7408.96596875
transcript.pyannote[1307].speaker SPEAKER_16
transcript.pyannote[1307].start 7409.64096875
transcript.pyannote[1307].end 7410.46784375
transcript.pyannote[1308].speaker SPEAKER_16
transcript.pyannote[1308].start 7411.19346875
transcript.pyannote[1308].end 7412.12159375
transcript.pyannote[1309].speaker SPEAKER_16
transcript.pyannote[1309].start 7413.30284375
transcript.pyannote[1309].end 7415.05784375
transcript.pyannote[1310].speaker SPEAKER_16
transcript.pyannote[1310].start 7415.91846875
transcript.pyannote[1310].end 7416.69471875
transcript.pyannote[1311].speaker SPEAKER_16
transcript.pyannote[1311].start 7417.33596875
transcript.pyannote[1311].end 7418.60159375
transcript.pyannote[1312].speaker SPEAKER_16
transcript.pyannote[1312].start 7418.98971875
transcript.pyannote[1312].end 7419.86721875
transcript.pyannote[1313].speaker SPEAKER_16
transcript.pyannote[1313].start 7420.77846875
transcript.pyannote[1313].end 7422.92159375
transcript.pyannote[1314].speaker SPEAKER_16
transcript.pyannote[1314].start 7423.36034375
transcript.pyannote[1314].end 7424.27159375
transcript.pyannote[1315].speaker SPEAKER_16
transcript.pyannote[1315].start 7425.65534375
transcript.pyannote[1315].end 7428.47346875
transcript.pyannote[1316].speaker SPEAKER_16
transcript.pyannote[1316].start 7429.38471875
transcript.pyannote[1316].end 7431.62909375
transcript.pyannote[1317].speaker SPEAKER_16
transcript.pyannote[1317].start 7432.54034375
transcript.pyannote[1317].end 7434.02534375
transcript.pyannote[1318].speaker SPEAKER_16
transcript.pyannote[1318].start 7434.56534375
transcript.pyannote[1318].end 7437.01221875
transcript.pyannote[1319].speaker SPEAKER_16
transcript.pyannote[1319].start 7437.19784375
transcript.pyannote[1319].end 7439.05409375
transcript.pyannote[1320].speaker SPEAKER_02
transcript.pyannote[1320].start 7439.15534375
transcript.pyannote[1320].end 7439.39159375
transcript.pyannote[1321].speaker SPEAKER_16
transcript.pyannote[1321].start 7439.71221875
transcript.pyannote[1321].end 7440.40409375
transcript.pyannote[1322].speaker SPEAKER_16
transcript.pyannote[1322].start 7441.38284375
transcript.pyannote[1322].end 7442.93534375
transcript.pyannote[1323].speaker SPEAKER_16
transcript.pyannote[1323].start 7443.47534375
transcript.pyannote[1323].end 7443.93096875
transcript.pyannote[1324].speaker SPEAKER_16
transcript.pyannote[1324].start 7444.65659375
transcript.pyannote[1324].end 7446.52971875
transcript.pyannote[1325].speaker SPEAKER_27
transcript.pyannote[1325].start 7447.37346875
transcript.pyannote[1325].end 7447.77846875
transcript.pyannote[1326].speaker SPEAKER_27
transcript.pyannote[1326].start 7448.13284375
transcript.pyannote[1326].end 7455.35534375
transcript.pyannote[1327].speaker SPEAKER_27
transcript.pyannote[1327].start 7455.87846875
transcript.pyannote[1327].end 7463.15159375
transcript.pyannote[1328].speaker SPEAKER_16
transcript.pyannote[1328].start 7456.51971875
transcript.pyannote[1328].end 7457.29596875
transcript.pyannote[1329].speaker SPEAKER_16
transcript.pyannote[1329].start 7460.72159375
transcript.pyannote[1329].end 7461.17721875
transcript.pyannote[1330].speaker SPEAKER_16
transcript.pyannote[1330].start 7463.05034375
transcript.pyannote[1330].end 7469.95221875
transcript.pyannote[1331].speaker SPEAKER_27
transcript.pyannote[1331].start 7463.84346875
transcript.pyannote[1331].end 7464.55221875
transcript.pyannote[1332].speaker SPEAKER_02
transcript.pyannote[1332].start 7464.55221875
transcript.pyannote[1332].end 7464.58596875
transcript.pyannote[1333].speaker SPEAKER_27
transcript.pyannote[1333].start 7465.71659375
transcript.pyannote[1333].end 7466.35784375
transcript.pyannote[1334].speaker SPEAKER_02
transcript.pyannote[1334].start 7466.35784375
transcript.pyannote[1334].end 7466.77971875
transcript.pyannote[1335].speaker SPEAKER_02
transcript.pyannote[1335].start 7469.85096875
transcript.pyannote[1335].end 7470.23909375
transcript.pyannote[1336].speaker SPEAKER_16
transcript.pyannote[1336].start 7469.98596875
transcript.pyannote[1336].end 7471.23471875
transcript.pyannote[1337].speaker SPEAKER_02
transcript.pyannote[1337].start 7471.38659375
transcript.pyannote[1337].end 7471.79159375
transcript.pyannote[1338].speaker SPEAKER_16
transcript.pyannote[1338].start 7471.87596875
transcript.pyannote[1338].end 7472.87159375
transcript.pyannote[1339].speaker SPEAKER_16
transcript.pyannote[1339].start 7473.12471875
transcript.pyannote[1339].end 7474.72784375
transcript.pyannote[1340].speaker SPEAKER_16
transcript.pyannote[1340].start 7475.25096875
transcript.pyannote[1340].end 7476.41534375
transcript.pyannote[1341].speaker SPEAKER_16
transcript.pyannote[1341].start 7477.12409375
transcript.pyannote[1341].end 7478.71034375
transcript.pyannote[1342].speaker SPEAKER_27
transcript.pyannote[1342].start 7478.71034375
transcript.pyannote[1342].end 7479.30096875
transcript.pyannote[1343].speaker SPEAKER_16
transcript.pyannote[1343].start 7479.21659375
transcript.pyannote[1343].end 7480.24596875
transcript.pyannote[1344].speaker SPEAKER_27
transcript.pyannote[1344].start 7479.72284375
transcript.pyannote[1344].end 7481.76471875
transcript.pyannote[1345].speaker SPEAKER_16
transcript.pyannote[1345].start 7480.95471875
transcript.pyannote[1345].end 7484.16096875
transcript.pyannote[1346].speaker SPEAKER_27
transcript.pyannote[1346].start 7482.03471875
transcript.pyannote[1346].end 7485.42659375
transcript.pyannote[1347].speaker SPEAKER_16
transcript.pyannote[1347].start 7485.42659375
transcript.pyannote[1347].end 7486.89471875
transcript.pyannote[1348].speaker SPEAKER_16
transcript.pyannote[1348].start 7486.96221875
transcript.pyannote[1348].end 7488.29534375
transcript.pyannote[1349].speaker SPEAKER_27
transcript.pyannote[1349].start 7488.14346875
transcript.pyannote[1349].end 7488.56534375
transcript.pyannote[1350].speaker SPEAKER_02
transcript.pyannote[1350].start 7488.56534375
transcript.pyannote[1350].end 7488.58221875
transcript.pyannote[1351].speaker SPEAKER_16
transcript.pyannote[1351].start 7488.76784375
transcript.pyannote[1351].end 7491.61971875
transcript.pyannote[1352].speaker SPEAKER_02
transcript.pyannote[1352].start 7491.67034375
transcript.pyannote[1352].end 7491.97409375
transcript.pyannote[1353].speaker SPEAKER_16
transcript.pyannote[1353].start 7491.97409375
transcript.pyannote[1353].end 7493.30721875
transcript.pyannote[1354].speaker SPEAKER_16
transcript.pyannote[1354].start 7493.39159375
transcript.pyannote[1354].end 7497.10409375
transcript.pyannote[1355].speaker SPEAKER_02
transcript.pyannote[1355].start 7494.75846875
transcript.pyannote[1355].end 7495.12971875
transcript.pyannote[1356].speaker SPEAKER_02
transcript.pyannote[1356].start 7496.91846875
transcript.pyannote[1356].end 7496.93534375
transcript.pyannote[1357].speaker SPEAKER_27
transcript.pyannote[1357].start 7496.93534375
transcript.pyannote[1357].end 7497.72846875
transcript.pyannote[1358].speaker SPEAKER_16
transcript.pyannote[1358].start 7497.17159375
transcript.pyannote[1358].end 7498.25159375
transcript.pyannote[1359].speaker SPEAKER_16
transcript.pyannote[1359].start 7498.65659375
transcript.pyannote[1359].end 7499.21346875
transcript.pyannote[1360].speaker SPEAKER_27
transcript.pyannote[1360].start 7500.10784375
transcript.pyannote[1360].end 7501.03596875
transcript.pyannote[1361].speaker SPEAKER_27
transcript.pyannote[1361].start 7501.66034375
transcript.pyannote[1361].end 7502.94284375
transcript.pyannote[1362].speaker SPEAKER_27
transcript.pyannote[1362].start 7502.97659375
transcript.pyannote[1362].end 7503.02721875
transcript.pyannote[1363].speaker SPEAKER_27
transcript.pyannote[1363].start 7504.78221875
transcript.pyannote[1363].end 7507.93784375
transcript.pyannote[1364].speaker SPEAKER_16
transcript.pyannote[1364].start 7506.33471875
transcript.pyannote[1364].end 7506.85784375
transcript.pyannote[1365].speaker SPEAKER_16
transcript.pyannote[1365].start 7507.49909375
transcript.pyannote[1365].end 7509.35534375
transcript.pyannote[1366].speaker SPEAKER_27
transcript.pyannote[1366].start 7508.34284375
transcript.pyannote[1366].end 7509.87846875
transcript.pyannote[1367].speaker SPEAKER_16
transcript.pyannote[1367].start 7509.87846875
transcript.pyannote[1367].end 7512.51096875
transcript.pyannote[1368].speaker SPEAKER_16
transcript.pyannote[1368].start 7512.94971875
transcript.pyannote[1368].end 7519.04159375
transcript.pyannote[1369].speaker SPEAKER_16
transcript.pyannote[1369].start 7519.98659375
transcript.pyannote[1369].end 7523.66534375
transcript.pyannote[1370].speaker SPEAKER_02
transcript.pyannote[1370].start 7523.42909375
transcript.pyannote[1370].end 7524.07034375
transcript.pyannote[1371].speaker SPEAKER_16
transcript.pyannote[1371].start 7524.07034375
transcript.pyannote[1371].end 7529.62221875
transcript.pyannote[1372].speaker SPEAKER_16
transcript.pyannote[1372].start 7530.34784375
transcript.pyannote[1372].end 7532.25471875
transcript.pyannote[1373].speaker SPEAKER_16
transcript.pyannote[1373].start 7533.11534375
transcript.pyannote[1373].end 7535.54534375
transcript.pyannote[1374].speaker SPEAKER_27
transcript.pyannote[1374].start 7536.33846875
transcript.pyannote[1374].end 7536.57471875
transcript.pyannote[1375].speaker SPEAKER_16
transcript.pyannote[1375].start 7537.04721875
transcript.pyannote[1375].end 7537.53659375
transcript.pyannote[1376].speaker SPEAKER_16
transcript.pyannote[1376].start 7538.14409375
transcript.pyannote[1376].end 7539.32534375
transcript.pyannote[1377].speaker SPEAKER_16
transcript.pyannote[1377].start 7539.78096875
transcript.pyannote[1377].end 7543.51034375
transcript.pyannote[1378].speaker SPEAKER_02
transcript.pyannote[1378].start 7543.74659375
transcript.pyannote[1378].end 7544.01659375
transcript.pyannote[1379].speaker SPEAKER_16
transcript.pyannote[1379].start 7544.18534375
transcript.pyannote[1379].end 7547.05409375
transcript.pyannote[1380].speaker SPEAKER_16
transcript.pyannote[1380].start 7547.30721875
transcript.pyannote[1380].end 7549.09596875
transcript.pyannote[1381].speaker SPEAKER_27
transcript.pyannote[1381].start 7549.73721875
transcript.pyannote[1381].end 7553.71971875
transcript.pyannote[1382].speaker SPEAKER_16
transcript.pyannote[1382].start 7553.71971875
transcript.pyannote[1382].end 7556.90909375
transcript.pyannote[1383].speaker SPEAKER_27
transcript.pyannote[1383].start 7554.34409375
transcript.pyannote[1383].end 7555.57596875
transcript.pyannote[1384].speaker SPEAKER_16
transcript.pyannote[1384].start 7561.58346875
transcript.pyannote[1384].end 7562.68034375
transcript.pyannote[1385].speaker SPEAKER_16
transcript.pyannote[1385].start 7562.78159375
transcript.pyannote[1385].end 7564.43534375
transcript.pyannote[1386].speaker SPEAKER_27
transcript.pyannote[1386].start 7564.43534375
transcript.pyannote[1386].end 7564.72221875
transcript.pyannote[1387].speaker SPEAKER_16
transcript.pyannote[1387].start 7564.65471875
transcript.pyannote[1387].end 7566.32534375
transcript.pyannote[1388].speaker SPEAKER_27
transcript.pyannote[1388].start 7566.25784375
transcript.pyannote[1388].end 7568.97471875
transcript.pyannote[1389].speaker SPEAKER_16
transcript.pyannote[1389].start 7566.42659375
transcript.pyannote[1389].end 7567.60784375
transcript.pyannote[1390].speaker SPEAKER_16
transcript.pyannote[1390].start 7568.04659375
transcript.pyannote[1390].end 7578.10409375
transcript.pyannote[1391].speaker SPEAKER_16
transcript.pyannote[1391].start 7578.96471875
transcript.pyannote[1391].end 7582.30596875
transcript.pyannote[1392].speaker SPEAKER_16
transcript.pyannote[1392].start 7582.64346875
transcript.pyannote[1392].end 7585.09034375
transcript.pyannote[1393].speaker SPEAKER_16
transcript.pyannote[1393].start 7585.56284375
transcript.pyannote[1393].end 7586.62596875
transcript.pyannote[1394].speaker SPEAKER_16
transcript.pyannote[1394].start 7587.04784375
transcript.pyannote[1394].end 7588.97159375
transcript.pyannote[1395].speaker SPEAKER_02
transcript.pyannote[1395].start 7589.25846875
transcript.pyannote[1395].end 7589.56221875
transcript.pyannote[1396].speaker SPEAKER_16
transcript.pyannote[1396].start 7589.98409375
transcript.pyannote[1396].end 7591.57034375
transcript.pyannote[1397].speaker SPEAKER_02
transcript.pyannote[1397].start 7590.86159375
transcript.pyannote[1397].end 7591.40159375
transcript.pyannote[1398].speaker SPEAKER_16
transcript.pyannote[1398].start 7591.97534375
transcript.pyannote[1398].end 7592.56596875
transcript.pyannote[1399].speaker SPEAKER_16
transcript.pyannote[1399].start 7592.97096875
transcript.pyannote[1399].end 7594.54034375
transcript.pyannote[1400].speaker SPEAKER_16
transcript.pyannote[1400].start 7595.13096875
transcript.pyannote[1400].end 7597.67909375
transcript.pyannote[1401].speaker SPEAKER_16
transcript.pyannote[1401].start 7597.71284375
transcript.pyannote[1401].end 7598.82659375
transcript.pyannote[1402].speaker SPEAKER_16
transcript.pyannote[1402].start 7599.36659375
transcript.pyannote[1402].end 7603.53471875
transcript.pyannote[1403].speaker SPEAKER_16
transcript.pyannote[1403].start 7604.07471875
transcript.pyannote[1403].end 7608.09096875
transcript.pyannote[1404].speaker SPEAKER_16
transcript.pyannote[1404].start 7610.50409375
transcript.pyannote[1404].end 7612.12409375
transcript.pyannote[1405].speaker SPEAKER_27
transcript.pyannote[1405].start 7611.38159375
transcript.pyannote[1405].end 7612.44471875
transcript.pyannote[1406].speaker SPEAKER_27
transcript.pyannote[1406].start 7612.78221875
transcript.pyannote[1406].end 7615.95471875
transcript.pyannote[1407].speaker SPEAKER_27
transcript.pyannote[1407].start 7616.22471875
transcript.pyannote[1407].end 7616.24159375
transcript.pyannote[1408].speaker SPEAKER_16
transcript.pyannote[1408].start 7616.24159375
transcript.pyannote[1408].end 7620.20721875
transcript.pyannote[1409].speaker SPEAKER_27
transcript.pyannote[1409].start 7616.27534375
transcript.pyannote[1409].end 7616.73096875
transcript.pyannote[1410].speaker SPEAKER_27
transcript.pyannote[1410].start 7619.32971875
transcript.pyannote[1410].end 7624.39221875
transcript.pyannote[1411].speaker SPEAKER_16
transcript.pyannote[1411].start 7624.51034375
transcript.pyannote[1411].end 7624.56096875
transcript.pyannote[1412].speaker SPEAKER_28
transcript.pyannote[1412].start 7624.56096875
transcript.pyannote[1412].end 7624.99971875
transcript.pyannote[1413].speaker SPEAKER_27
transcript.pyannote[1413].start 7624.99971875
transcript.pyannote[1413].end 7632.59346875
transcript.pyannote[1414].speaker SPEAKER_27
transcript.pyannote[1414].start 7633.40346875
transcript.pyannote[1414].end 7637.52096875
transcript.pyannote[1415].speaker SPEAKER_27
transcript.pyannote[1415].start 7638.09471875
transcript.pyannote[1415].end 7642.65096875
transcript.pyannote[1416].speaker SPEAKER_27
transcript.pyannote[1416].start 7643.14034375
transcript.pyannote[1416].end 7648.01721875
transcript.pyannote[1417].speaker SPEAKER_27
transcript.pyannote[1417].start 7648.67534375
transcript.pyannote[1417].end 7658.10846875
transcript.pyannote[1418].speaker SPEAKER_16
transcript.pyannote[1418].start 7658.10846875
transcript.pyannote[1418].end 7666.51221875
transcript.pyannote[1419].speaker SPEAKER_27
transcript.pyannote[1419].start 7658.56409375
transcript.pyannote[1419].end 7659.23909375
transcript.pyannote[1420].speaker SPEAKER_27
transcript.pyannote[1420].start 7660.60596875
transcript.pyannote[1420].end 7662.47909375
transcript.pyannote[1421].speaker SPEAKER_16
transcript.pyannote[1421].start 7666.88346875
transcript.pyannote[1421].end 7674.37596875
transcript.pyannote[1422].speaker SPEAKER_00
transcript.pyannote[1422].start 7671.37221875
transcript.pyannote[1422].end 7671.74346875
transcript.pyannote[1423].speaker SPEAKER_00
transcript.pyannote[1423].start 7672.72221875
transcript.pyannote[1423].end 7673.11034375
transcript.pyannote[1424].speaker SPEAKER_16
transcript.pyannote[1424].start 7674.86534375
transcript.pyannote[1424].end 7696.48221875
transcript.pyannote[1425].speaker SPEAKER_27
transcript.pyannote[1425].start 7696.36409375
transcript.pyannote[1425].end 7700.46471875
transcript.pyannote[1426].speaker SPEAKER_16
transcript.pyannote[1426].start 7697.19096875
transcript.pyannote[1426].end 7697.74784375
transcript.pyannote[1427].speaker SPEAKER_16
transcript.pyannote[1427].start 7698.18659375
transcript.pyannote[1427].end 7700.58284375
transcript.pyannote[1428].speaker SPEAKER_27
transcript.pyannote[1428].start 7700.76846875
transcript.pyannote[1428].end 7702.38846875
transcript.pyannote[1429].speaker SPEAKER_16
transcript.pyannote[1429].start 7700.90346875
transcript.pyannote[1429].end 7708.53096875
transcript.pyannote[1430].speaker SPEAKER_27
transcript.pyannote[1430].start 7703.06346875
transcript.pyannote[1430].end 7703.40096875
transcript.pyannote[1431].speaker SPEAKER_16
transcript.pyannote[1431].start 7709.05409375
transcript.pyannote[1431].end 7709.61096875
transcript.pyannote[1432].speaker SPEAKER_16
transcript.pyannote[1432].start 7709.88096875
transcript.pyannote[1432].end 7713.69471875
transcript.pyannote[1433].speaker SPEAKER_16
transcript.pyannote[1433].start 7713.99846875
transcript.pyannote[1433].end 7714.55534375
transcript.pyannote[1434].speaker SPEAKER_16
transcript.pyannote[1434].start 7715.85471875
transcript.pyannote[1434].end 7717.96409375
transcript.pyannote[1435].speaker SPEAKER_16
transcript.pyannote[1435].start 7718.58846875
transcript.pyannote[1435].end 7719.28034375
transcript.pyannote[1436].speaker SPEAKER_16
transcript.pyannote[1436].start 7720.00596875
transcript.pyannote[1436].end 7730.94096875
transcript.pyannote[1437].speaker SPEAKER_00
transcript.pyannote[1437].start 7721.60909375
transcript.pyannote[1437].end 7721.69346875
transcript.pyannote[1438].speaker SPEAKER_27
transcript.pyannote[1438].start 7721.69346875
transcript.pyannote[1438].end 7721.71034375
transcript.pyannote[1439].speaker SPEAKER_28
transcript.pyannote[1439].start 7721.71034375
transcript.pyannote[1439].end 7722.09846875
transcript.pyannote[1440].speaker SPEAKER_03
transcript.pyannote[1440].start 7728.22409375
transcript.pyannote[1440].end 7728.52784375
transcript.pyannote[1441].speaker SPEAKER_03
transcript.pyannote[1441].start 7729.37159375
transcript.pyannote[1441].end 7729.65846875
transcript.pyannote[1442].speaker SPEAKER_03
transcript.pyannote[1442].start 7730.60346875
transcript.pyannote[1442].end 7730.78909375
transcript.pyannote[1443].speaker SPEAKER_03
transcript.pyannote[1443].start 7732.12221875
transcript.pyannote[1443].end 7734.72096875
transcript.pyannote[1444].speaker SPEAKER_03
transcript.pyannote[1444].start 8405.31659375
transcript.pyannote[1444].end 8407.74659375
transcript.pyannote[1445].speaker SPEAKER_03
transcript.pyannote[1445].start 8408.47221875
transcript.pyannote[1445].end 8411.47596875
transcript.pyannote[1446].speaker SPEAKER_03
transcript.pyannote[1446].start 8412.01596875
transcript.pyannote[1446].end 8412.80909375
transcript.pyannote[1447].speaker SPEAKER_05
transcript.pyannote[1447].start 8416.65659375
transcript.pyannote[1447].end 8417.23034375
transcript.pyannote[1448].speaker SPEAKER_05
transcript.pyannote[1448].start 8417.75346875
transcript.pyannote[1448].end 8419.22159375
transcript.pyannote[1449].speaker SPEAKER_05
transcript.pyannote[1449].start 8419.42409375
transcript.pyannote[1449].end 8424.90846875
transcript.pyannote[1450].speaker SPEAKER_05
transcript.pyannote[1450].start 8425.21221875
transcript.pyannote[1450].end 8427.28784375
transcript.pyannote[1451].speaker SPEAKER_05
transcript.pyannote[1451].start 8427.82784375
transcript.pyannote[1451].end 8428.97534375
transcript.pyannote[1452].speaker SPEAKER_27
transcript.pyannote[1452].start 8428.97534375
transcript.pyannote[1452].end 8433.02534375
transcript.pyannote[1453].speaker SPEAKER_27
transcript.pyannote[1453].start 8433.37971875
transcript.pyannote[1453].end 8434.08846875
transcript.pyannote[1454].speaker SPEAKER_27
transcript.pyannote[1454].start 8434.88159375
transcript.pyannote[1454].end 8442.23909375
transcript.pyannote[1455].speaker SPEAKER_05
transcript.pyannote[1455].start 8437.76721875
transcript.pyannote[1455].end 8438.23971875
transcript.pyannote[1456].speaker SPEAKER_00
transcript.pyannote[1456].start 8438.23971875
transcript.pyannote[1456].end 8438.25659375
transcript.pyannote[1457].speaker SPEAKER_05
transcript.pyannote[1457].start 8442.40784375
transcript.pyannote[1457].end 8448.76971875
transcript.pyannote[1458].speaker SPEAKER_05
transcript.pyannote[1458].start 8449.19159375
transcript.pyannote[1458].end 8467.29846875
transcript.pyannote[1459].speaker SPEAKER_05
transcript.pyannote[1459].start 8467.58534375
transcript.pyannote[1459].end 8475.31409375
transcript.pyannote[1460].speaker SPEAKER_05
transcript.pyannote[1460].start 8475.43221875
transcript.pyannote[1460].end 8476.96784375
transcript.pyannote[1461].speaker SPEAKER_05
transcript.pyannote[1461].start 8477.30534375
transcript.pyannote[1461].end 8492.25659375
transcript.pyannote[1462].speaker SPEAKER_05
transcript.pyannote[1462].start 8492.74596875
transcript.pyannote[1462].end 8512.03409375
transcript.pyannote[1463].speaker SPEAKER_05
transcript.pyannote[1463].start 8512.05096875
transcript.pyannote[1463].end 8514.21096875
transcript.pyannote[1464].speaker SPEAKER_05
transcript.pyannote[1464].start 8514.58221875
transcript.pyannote[1464].end 8520.72471875
transcript.pyannote[1465].speaker SPEAKER_05
transcript.pyannote[1465].start 8521.46721875
transcript.pyannote[1465].end 8523.03659375
transcript.pyannote[1466].speaker SPEAKER_05
transcript.pyannote[1466].start 8523.40784375
transcript.pyannote[1466].end 8529.61784375
transcript.pyannote[1467].speaker SPEAKER_27
transcript.pyannote[1467].start 8529.61784375
transcript.pyannote[1467].end 8529.70221875
transcript.pyannote[1468].speaker SPEAKER_05
transcript.pyannote[1468].start 8529.70221875
transcript.pyannote[1468].end 8529.80346875
transcript.pyannote[1469].speaker SPEAKER_27
transcript.pyannote[1469].start 8529.80346875
transcript.pyannote[1469].end 8532.73971875
transcript.pyannote[1470].speaker SPEAKER_27
transcript.pyannote[1470].start 8532.84096875
transcript.pyannote[1470].end 8571.14721875
transcript.pyannote[1471].speaker SPEAKER_05
transcript.pyannote[1471].start 8536.24971875
transcript.pyannote[1471].end 8536.62096875
transcript.pyannote[1472].speaker SPEAKER_05
transcript.pyannote[1472].start 8570.72534375
transcript.pyannote[1472].end 8575.29846875
transcript.pyannote[1473].speaker SPEAKER_27
transcript.pyannote[1473].start 8573.40846875
transcript.pyannote[1473].end 8575.26471875
transcript.pyannote[1474].speaker SPEAKER_27
transcript.pyannote[1474].start 8575.29846875
transcript.pyannote[1474].end 8575.31534375
transcript.pyannote[1475].speaker SPEAKER_05
transcript.pyannote[1475].start 8575.31534375
transcript.pyannote[1475].end 8575.53471875
transcript.pyannote[1476].speaker SPEAKER_27
transcript.pyannote[1476].start 8575.53471875
transcript.pyannote[1476].end 8575.70346875
transcript.pyannote[1477].speaker SPEAKER_05
transcript.pyannote[1477].start 8575.70346875
transcript.pyannote[1477].end 8576.34471875
transcript.pyannote[1478].speaker SPEAKER_27
transcript.pyannote[1478].start 8575.72034375
transcript.pyannote[1478].end 8578.94346875
transcript.pyannote[1479].speaker SPEAKER_05
transcript.pyannote[1479].start 8577.99846875
transcript.pyannote[1479].end 8579.34846875
transcript.pyannote[1480].speaker SPEAKER_27
transcript.pyannote[1480].start 8579.34846875
transcript.pyannote[1480].end 8579.43284375
transcript.pyannote[1481].speaker SPEAKER_05
transcript.pyannote[1481].start 8579.43284375
transcript.pyannote[1481].end 8579.63534375
transcript.pyannote[1482].speaker SPEAKER_27
transcript.pyannote[1482].start 8579.63534375
transcript.pyannote[1482].end 8579.68596875
transcript.pyannote[1483].speaker SPEAKER_05
transcript.pyannote[1483].start 8579.68596875
transcript.pyannote[1483].end 8580.79971875
transcript.pyannote[1484].speaker SPEAKER_27
transcript.pyannote[1484].start 8580.79971875
transcript.pyannote[1484].end 8588.30909375
transcript.pyannote[1485].speaker SPEAKER_27
transcript.pyannote[1485].start 8588.64659375
transcript.pyannote[1485].end 8597.16846875
transcript.pyannote[1486].speaker SPEAKER_05
transcript.pyannote[1486].start 8595.93659375
transcript.pyannote[1486].end 8609.70659375
transcript.pyannote[1487].speaker SPEAKER_27
transcript.pyannote[1487].start 8597.43846875
transcript.pyannote[1487].end 8598.02909375
transcript.pyannote[1488].speaker SPEAKER_02
transcript.pyannote[1488].start 8607.12471875
transcript.pyannote[1488].end 8608.03596875
transcript.pyannote[1489].speaker SPEAKER_28
transcript.pyannote[1489].start 8608.03596875
transcript.pyannote[1489].end 8608.50846875
transcript.pyannote[1490].speaker SPEAKER_02
transcript.pyannote[1490].start 8608.50846875
transcript.pyannote[1490].end 8608.54221875
transcript.pyannote[1491].speaker SPEAKER_05
transcript.pyannote[1491].start 8609.80784375
transcript.pyannote[1491].end 8614.24596875
transcript.pyannote[1492].speaker SPEAKER_05
transcript.pyannote[1492].start 8614.53284375
transcript.pyannote[1492].end 8620.05096875
transcript.pyannote[1493].speaker SPEAKER_05
transcript.pyannote[1493].start 8620.38846875
transcript.pyannote[1493].end 8624.30346875
transcript.pyannote[1494].speaker SPEAKER_27
transcript.pyannote[1494].start 8624.50596875
transcript.pyannote[1494].end 8629.92284375
transcript.pyannote[1495].speaker SPEAKER_05
transcript.pyannote[1495].start 8629.18034375
transcript.pyannote[1495].end 8632.97721875
transcript.pyannote[1496].speaker SPEAKER_27
transcript.pyannote[1496].start 8631.37409375
transcript.pyannote[1496].end 8632.85909375
transcript.pyannote[1497].speaker SPEAKER_05
transcript.pyannote[1497].start 8633.06159375
transcript.pyannote[1497].end 8637.11159375
transcript.pyannote[1498].speaker SPEAKER_27
transcript.pyannote[1498].start 8633.31471875
transcript.pyannote[1498].end 8633.63534375
transcript.pyannote[1499].speaker SPEAKER_05
transcript.pyannote[1499].start 8637.51659375
transcript.pyannote[1499].end 8643.79409375
transcript.pyannote[1500].speaker SPEAKER_27
transcript.pyannote[1500].start 8642.39346875
transcript.pyannote[1500].end 8656.12971875
transcript.pyannote[1501].speaker SPEAKER_27
transcript.pyannote[1501].start 8656.88909375
transcript.pyannote[1501].end 8664.22971875
transcript.pyannote[1502].speaker SPEAKER_27
transcript.pyannote[1502].start 8664.90471875
transcript.pyannote[1502].end 8688.10784375
transcript.pyannote[1503].speaker SPEAKER_05
transcript.pyannote[1503].start 8668.16159375
transcript.pyannote[1503].end 8672.54909375
transcript.pyannote[1504].speaker SPEAKER_05
transcript.pyannote[1504].start 8684.24346875
transcript.pyannote[1504].end 8690.14971875
transcript.pyannote[1505].speaker SPEAKER_27
transcript.pyannote[1505].start 8689.18784375
transcript.pyannote[1505].end 8702.77221875
transcript.pyannote[1506].speaker SPEAKER_05
transcript.pyannote[1506].start 8697.16971875
transcript.pyannote[1506].end 8699.63346875
transcript.pyannote[1507].speaker SPEAKER_05
transcript.pyannote[1507].start 8701.65846875
transcript.pyannote[1507].end 8702.99159375
transcript.pyannote[1508].speaker SPEAKER_27
transcript.pyannote[1508].start 8703.26159375
transcript.pyannote[1508].end 8706.21471875
transcript.pyannote[1509].speaker SPEAKER_05
transcript.pyannote[1509].start 8704.96596875
transcript.pyannote[1509].end 8708.72909375
transcript.pyannote[1510].speaker SPEAKER_27
transcript.pyannote[1510].start 8709.25221875
transcript.pyannote[1510].end 8709.37034375
transcript.pyannote[1511].speaker SPEAKER_05
transcript.pyannote[1511].start 8709.37034375
transcript.pyannote[1511].end 8713.99409375
transcript.pyannote[1512].speaker SPEAKER_27
transcript.pyannote[1512].start 8710.21409375
transcript.pyannote[1512].end 8712.34034375
transcript.pyannote[1513].speaker SPEAKER_27
transcript.pyannote[1513].start 8712.47534375
transcript.pyannote[1513].end 8724.18659375
transcript.pyannote[1514].speaker SPEAKER_27
transcript.pyannote[1514].start 8724.97971875
transcript.pyannote[1514].end 8734.37909375
transcript.pyannote[1515].speaker SPEAKER_05
transcript.pyannote[1515].start 8733.02909375
transcript.pyannote[1515].end 8753.21159375
transcript.pyannote[1516].speaker SPEAKER_00
transcript.pyannote[1516].start 8740.69034375
transcript.pyannote[1516].end 8742.49596875
transcript.pyannote[1517].speaker SPEAKER_00
transcript.pyannote[1517].start 8744.63909375
transcript.pyannote[1517].end 8745.02721875
transcript.pyannote[1518].speaker SPEAKER_27
transcript.pyannote[1518].start 8745.02721875
transcript.pyannote[1518].end 8748.97596875
transcript.pyannote[1519].speaker SPEAKER_27
transcript.pyannote[1519].start 8749.95471875
transcript.pyannote[1519].end 8757.48096875
transcript.pyannote[1520].speaker SPEAKER_05
transcript.pyannote[1520].start 8757.48096875
transcript.pyannote[1520].end 8759.65784375
transcript.pyannote[1521].speaker SPEAKER_27
transcript.pyannote[1521].start 8759.18534375
transcript.pyannote[1521].end 8759.30346875
transcript.pyannote[1522].speaker SPEAKER_27
transcript.pyannote[1522].start 8759.65784375
transcript.pyannote[1522].end 8759.97846875
transcript.pyannote[1523].speaker SPEAKER_05
transcript.pyannote[1523].start 8759.97846875
transcript.pyannote[1523].end 8760.02909375
transcript.pyannote[1524].speaker SPEAKER_27
transcript.pyannote[1524].start 8760.02909375
transcript.pyannote[1524].end 8760.04596875
transcript.pyannote[1525].speaker SPEAKER_05
transcript.pyannote[1525].start 8760.04596875
transcript.pyannote[1525].end 8760.06284375
transcript.pyannote[1526].speaker SPEAKER_27
transcript.pyannote[1526].start 8760.06284375
transcript.pyannote[1526].end 8761.53096875
transcript.pyannote[1527].speaker SPEAKER_05
transcript.pyannote[1527].start 8760.11346875
transcript.pyannote[1527].end 8761.56471875
transcript.pyannote[1528].speaker SPEAKER_27
transcript.pyannote[1528].start 8761.56471875
transcript.pyannote[1528].end 8762.32409375
transcript.pyannote[1529].speaker SPEAKER_05
transcript.pyannote[1529].start 8762.32409375
transcript.pyannote[1529].end 8767.45409375
transcript.pyannote[1530].speaker SPEAKER_27
transcript.pyannote[1530].start 8762.44221875
transcript.pyannote[1530].end 8767.26846875
transcript.pyannote[1531].speaker SPEAKER_27
transcript.pyannote[1531].start 8767.79159375
transcript.pyannote[1531].end 8780.41409375
transcript.pyannote[1532].speaker SPEAKER_05
transcript.pyannote[1532].start 8771.65596875
transcript.pyannote[1532].end 8773.03971875
transcript.pyannote[1533].speaker SPEAKER_05
transcript.pyannote[1533].start 8773.09034375
transcript.pyannote[1533].end 8774.84534375
transcript.pyannote[1534].speaker SPEAKER_05
transcript.pyannote[1534].start 8780.73471875
transcript.pyannote[1534].end 8785.74659375
transcript.pyannote[1535].speaker SPEAKER_27
transcript.pyannote[1535].start 8780.76846875
transcript.pyannote[1535].end 8781.24096875
transcript.pyannote[1536].speaker SPEAKER_27
transcript.pyannote[1536].start 8784.48096875
transcript.pyannote[1536].end 8790.45471875
transcript.pyannote[1537].speaker SPEAKER_05
transcript.pyannote[1537].start 8786.82659375
transcript.pyannote[1537].end 8787.23159375
transcript.pyannote[1538].speaker SPEAKER_05
transcript.pyannote[1538].start 8789.83034375
transcript.pyannote[1538].end 8790.47159375
transcript.pyannote[1539].speaker SPEAKER_27
transcript.pyannote[1539].start 8790.47159375
transcript.pyannote[1539].end 8791.61909375
transcript.pyannote[1540].speaker SPEAKER_05
transcript.pyannote[1540].start 8791.61909375
transcript.pyannote[1540].end 8801.49096875
transcript.pyannote[1541].speaker SPEAKER_27
transcript.pyannote[1541].start 8791.68659375
transcript.pyannote[1541].end 8792.69909375
transcript.pyannote[1542].speaker SPEAKER_27
transcript.pyannote[1542].start 8793.30659375
transcript.pyannote[1542].end 8795.58471875
transcript.pyannote[1543].speaker SPEAKER_05
transcript.pyannote[1543].start 8801.72721875
transcript.pyannote[1543].end 8822.97284375
transcript.pyannote[1544].speaker SPEAKER_09
transcript.pyannote[1544].start 8805.91221875
transcript.pyannote[1544].end 8806.19909375
transcript.pyannote[1545].speaker SPEAKER_27
transcript.pyannote[1545].start 8821.23471875
transcript.pyannote[1545].end 8821.57221875
transcript.pyannote[1546].speaker SPEAKER_27
transcript.pyannote[1546].start 8822.97284375
transcript.pyannote[1546].end 8838.51471875
transcript.pyannote[1547].speaker SPEAKER_05
transcript.pyannote[1547].start 8836.13534375
transcript.pyannote[1547].end 8840.74221875
transcript.pyannote[1548].speaker SPEAKER_27
transcript.pyannote[1548].start 8840.10096875
transcript.pyannote[1548].end 8841.31596875
transcript.pyannote[1549].speaker SPEAKER_27
transcript.pyannote[1549].start 8841.73784375
transcript.pyannote[1549].end 8847.18846875
transcript.pyannote[1550].speaker SPEAKER_27
transcript.pyannote[1550].start 8847.34034375
transcript.pyannote[1550].end 8848.25159375
transcript.pyannote[1551].speaker SPEAKER_27
transcript.pyannote[1551].start 8848.77471875
transcript.pyannote[1551].end 8849.26409375
transcript.pyannote[1552].speaker SPEAKER_05
transcript.pyannote[1552].start 8849.26409375
transcript.pyannote[1552].end 8849.29784375
transcript.pyannote[1553].speaker SPEAKER_27
transcript.pyannote[1553].start 8849.29784375
transcript.pyannote[1553].end 8849.36534375
transcript.pyannote[1554].speaker SPEAKER_05
transcript.pyannote[1554].start 8849.36534375
transcript.pyannote[1554].end 8849.39909375
transcript.pyannote[1555].speaker SPEAKER_27
transcript.pyannote[1555].start 8849.39909375
transcript.pyannote[1555].end 8849.92221875
transcript.pyannote[1556].speaker SPEAKER_05
transcript.pyannote[1556].start 8849.92221875
transcript.pyannote[1556].end 8852.03159375
transcript.pyannote[1557].speaker SPEAKER_27
transcript.pyannote[1557].start 8852.03159375
transcript.pyannote[1557].end 8852.06534375
transcript.pyannote[1558].speaker SPEAKER_05
transcript.pyannote[1558].start 8852.06534375
transcript.pyannote[1558].end 8852.13284375
transcript.pyannote[1559].speaker SPEAKER_27
transcript.pyannote[1559].start 8852.13284375
transcript.pyannote[1559].end 8852.82471875
transcript.pyannote[1560].speaker SPEAKER_05
transcript.pyannote[1560].start 8852.82471875
transcript.pyannote[1560].end 8852.95971875
transcript.pyannote[1561].speaker SPEAKER_05
transcript.pyannote[1561].start 8853.31409375
transcript.pyannote[1561].end 8853.34784375
transcript.pyannote[1562].speaker SPEAKER_27
transcript.pyannote[1562].start 8853.34784375
transcript.pyannote[1562].end 8853.87096875
transcript.pyannote[1563].speaker SPEAKER_27
transcript.pyannote[1563].start 8854.76534375
transcript.pyannote[1563].end 8854.81596875
transcript.pyannote[1564].speaker SPEAKER_05
transcript.pyannote[1564].start 8854.81596875
transcript.pyannote[1564].end 8855.74409375
transcript.pyannote[1565].speaker SPEAKER_27
transcript.pyannote[1565].start 8854.84971875
transcript.pyannote[1565].end 8855.82846875
transcript.pyannote[1566].speaker SPEAKER_05
transcript.pyannote[1566].start 8855.82846875
transcript.pyannote[1566].end 8855.84534375
transcript.pyannote[1567].speaker SPEAKER_27
transcript.pyannote[1567].start 8855.84534375
transcript.pyannote[1567].end 8864.97471875
transcript.pyannote[1568].speaker SPEAKER_05
transcript.pyannote[1568].start 8858.47784375
transcript.pyannote[1568].end 8858.93346875
transcript.pyannote[1569].speaker SPEAKER_05
transcript.pyannote[1569].start 8864.97471875
transcript.pyannote[1569].end 8896.83471875
transcript.pyannote[1570].speaker SPEAKER_27
transcript.pyannote[1570].start 8865.46409375
transcript.pyannote[1570].end 8866.17284375
transcript.pyannote[1571].speaker SPEAKER_03
transcript.pyannote[1571].start 8866.17284375
transcript.pyannote[1571].end 8866.25721875
transcript.pyannote[1572].speaker SPEAKER_05
transcript.pyannote[1572].start 8897.07096875
transcript.pyannote[1572].end 8908.29284375
transcript.pyannote[1573].speaker SPEAKER_05
transcript.pyannote[1573].start 8908.51221875
transcript.pyannote[1573].end 8908.66409375
transcript.pyannote[1574].speaker SPEAKER_05
transcript.pyannote[1574].start 8908.91721875
transcript.pyannote[1574].end 8916.52784375
transcript.pyannote[1575].speaker SPEAKER_05
transcript.pyannote[1575].start 8917.03409375
transcript.pyannote[1575].end 8919.09284375
transcript.pyannote[1576].speaker SPEAKER_05
transcript.pyannote[1576].start 8920.62846875
transcript.pyannote[1576].end 8921.60721875
transcript.pyannote[1577].speaker SPEAKER_27
transcript.pyannote[1577].start 8921.60721875
transcript.pyannote[1577].end 8921.82659375
transcript.pyannote[1578].speaker SPEAKER_05
transcript.pyannote[1578].start 8921.82659375
transcript.pyannote[1578].end 8931.90096875
transcript.pyannote[1579].speaker SPEAKER_27
transcript.pyannote[1579].start 8922.48471875
transcript.pyannote[1579].end 8923.02471875
transcript.pyannote[1580].speaker SPEAKER_27
transcript.pyannote[1580].start 8923.51409375
transcript.pyannote[1580].end 8923.88534375
transcript.pyannote[1581].speaker SPEAKER_27
transcript.pyannote[1581].start 8924.64471875
transcript.pyannote[1581].end 8925.53909375
transcript.pyannote[1582].speaker SPEAKER_05
transcript.pyannote[1582].start 8932.28909375
transcript.pyannote[1582].end 8967.15284375
transcript.pyannote[1583].speaker SPEAKER_27
transcript.pyannote[1583].start 8967.57471875
transcript.pyannote[1583].end 8977.24409375
transcript.pyannote[1584].speaker SPEAKER_05
transcript.pyannote[1584].start 8976.82221875
transcript.pyannote[1584].end 8978.54346875
transcript.pyannote[1585].speaker SPEAKER_27
transcript.pyannote[1585].start 8977.64909375
transcript.pyannote[1585].end 8978.91471875
transcript.pyannote[1586].speaker SPEAKER_05
transcript.pyannote[1586].start 8979.04971875
transcript.pyannote[1586].end 9023.56596875
transcript.pyannote[1587].speaker SPEAKER_27
transcript.pyannote[1587].start 8981.19284375
transcript.pyannote[1587].end 8982.28971875
transcript.pyannote[1588].speaker SPEAKER_27
transcript.pyannote[1588].start 8983.48784375
transcript.pyannote[1588].end 8985.05721875
transcript.pyannote[1589].speaker SPEAKER_00
transcript.pyannote[1589].start 8985.05721875
transcript.pyannote[1589].end 8985.09096875
transcript.pyannote[1590].speaker SPEAKER_27
transcript.pyannote[1590].start 8985.09096875
transcript.pyannote[1590].end 8985.54659375
transcript.pyannote[1591].speaker SPEAKER_00
transcript.pyannote[1591].start 8985.54659375
transcript.pyannote[1591].end 8985.66471875
transcript.pyannote[1592].speaker SPEAKER_00
transcript.pyannote[1592].start 8990.76096875
transcript.pyannote[1592].end 8991.84096875
transcript.pyannote[1593].speaker SPEAKER_10
transcript.pyannote[1593].start 9002.77596875
transcript.pyannote[1593].end 9002.86034375
transcript.pyannote[1594].speaker SPEAKER_10
transcript.pyannote[1594].start 9002.97846875
transcript.pyannote[1594].end 9003.02909375
transcript.pyannote[1595].speaker SPEAKER_28
transcript.pyannote[1595].start 9003.02909375
transcript.pyannote[1595].end 9003.04596875
transcript.pyannote[1596].speaker SPEAKER_27
transcript.pyannote[1596].start 9023.92034375
transcript.pyannote[1596].end 9025.20284375
transcript.pyannote[1597].speaker SPEAKER_05
transcript.pyannote[1597].start 9025.20284375
transcript.pyannote[1597].end 9025.21971875
transcript.pyannote[1598].speaker SPEAKER_27
transcript.pyannote[1598].start 9025.21971875
transcript.pyannote[1598].end 9025.30409375
transcript.pyannote[1599].speaker SPEAKER_05
transcript.pyannote[1599].start 9025.30409375
transcript.pyannote[1599].end 9025.38846875
transcript.pyannote[1600].speaker SPEAKER_27
transcript.pyannote[1600].start 9025.38846875
transcript.pyannote[1600].end 9025.87784375
transcript.pyannote[1601].speaker SPEAKER_05
transcript.pyannote[1601].start 9025.87784375
transcript.pyannote[1601].end 9049.46909375
transcript.pyannote[1602].speaker SPEAKER_03
transcript.pyannote[1602].start 9046.09409375
transcript.pyannote[1602].end 9046.29659375
transcript.pyannote[1603].speaker SPEAKER_03
transcript.pyannote[1603].start 9048.99659375
transcript.pyannote[1603].end 9049.41846875
transcript.pyannote[1604].speaker SPEAKER_03
transcript.pyannote[1604].start 9049.46909375
transcript.pyannote[1604].end 9049.53659375
transcript.pyannote[1605].speaker SPEAKER_05
transcript.pyannote[1605].start 9049.53659375
transcript.pyannote[1605].end 9049.55346875
transcript.pyannote[1606].speaker SPEAKER_03
transcript.pyannote[1606].start 9049.55346875
transcript.pyannote[1606].end 9049.57034375
transcript.pyannote[1607].speaker SPEAKER_03
transcript.pyannote[1607].start 9050.65034375
transcript.pyannote[1607].end 9052.28721875
transcript.pyannote[1608].speaker SPEAKER_03
transcript.pyannote[1608].start 9052.72596875
transcript.pyannote[1608].end 9055.03784375
transcript.pyannote[1609].speaker SPEAKER_22
transcript.pyannote[1609].start 9064.04909375
transcript.pyannote[1609].end 9066.91784375
transcript.pyannote[1610].speaker SPEAKER_03
transcript.pyannote[1610].start 9067.17096875
transcript.pyannote[1610].end 9068.01471875
transcript.pyannote[1611].speaker SPEAKER_22
transcript.pyannote[1611].start 9071.92971875
transcript.pyannote[1611].end 9073.02659375
transcript.pyannote[1612].speaker SPEAKER_22
transcript.pyannote[1612].start 9073.51596875
transcript.pyannote[1612].end 9074.15721875
transcript.pyannote[1613].speaker SPEAKER_22
transcript.pyannote[1613].start 9074.61284375
transcript.pyannote[1613].end 9111.02909375
transcript.pyannote[1614].speaker SPEAKER_22
transcript.pyannote[1614].start 9111.29909375
transcript.pyannote[1614].end 9152.47409375
transcript.pyannote[1615].speaker SPEAKER_22
transcript.pyannote[1615].start 9152.89596875
transcript.pyannote[1615].end 9159.62909375
transcript.pyannote[1616].speaker SPEAKER_22
transcript.pyannote[1616].start 9160.00034375
transcript.pyannote[1616].end 9161.19846875
transcript.pyannote[1617].speaker SPEAKER_27
transcript.pyannote[1617].start 9162.97034375
transcript.pyannote[1617].end 9163.32471875
transcript.pyannote[1618].speaker SPEAKER_27
transcript.pyannote[1618].start 9163.51034375
transcript.pyannote[1618].end 9166.80096875
transcript.pyannote[1619].speaker SPEAKER_02
transcript.pyannote[1619].start 9166.80096875
transcript.pyannote[1619].end 9166.85159375
transcript.pyannote[1620].speaker SPEAKER_22
transcript.pyannote[1620].start 9166.85159375
transcript.pyannote[1620].end 9166.96971875
transcript.pyannote[1621].speaker SPEAKER_02
transcript.pyannote[1621].start 9166.96971875
transcript.pyannote[1621].end 9167.12159375
transcript.pyannote[1622].speaker SPEAKER_27
transcript.pyannote[1622].start 9167.30721875
transcript.pyannote[1622].end 9167.86409375
transcript.pyannote[1623].speaker SPEAKER_27
transcript.pyannote[1623].start 9168.11721875
transcript.pyannote[1623].end 9174.41159375
transcript.pyannote[1624].speaker SPEAKER_02
transcript.pyannote[1624].start 9173.16284375
transcript.pyannote[1624].end 9173.71971875
transcript.pyannote[1625].speaker SPEAKER_27
transcript.pyannote[1625].start 9174.49596875
transcript.pyannote[1625].end 9175.33971875
transcript.pyannote[1626].speaker SPEAKER_27
transcript.pyannote[1626].start 9175.67721875
transcript.pyannote[1626].end 9182.59596875
transcript.pyannote[1627].speaker SPEAKER_22
transcript.pyannote[1627].start 9182.57909375
transcript.pyannote[1627].end 9187.96221875
transcript.pyannote[1628].speaker SPEAKER_27
transcript.pyannote[1628].start 9182.76471875
transcript.pyannote[1628].end 9183.62534375
transcript.pyannote[1629].speaker SPEAKER_27
transcript.pyannote[1629].start 9187.70909375
transcript.pyannote[1629].end 9188.46846875
transcript.pyannote[1630].speaker SPEAKER_22
transcript.pyannote[1630].start 9188.29971875
transcript.pyannote[1630].end 9188.95784375
transcript.pyannote[1631].speaker SPEAKER_27
transcript.pyannote[1631].start 9188.85659375
transcript.pyannote[1631].end 9189.19409375
transcript.pyannote[1632].speaker SPEAKER_27
transcript.pyannote[1632].start 9189.97034375
transcript.pyannote[1632].end 9191.60721875
transcript.pyannote[1633].speaker SPEAKER_27
transcript.pyannote[1633].start 9192.18096875
transcript.pyannote[1633].end 9199.62284375
transcript.pyannote[1634].speaker SPEAKER_22
transcript.pyannote[1634].start 9198.00284375
transcript.pyannote[1634].end 9198.54284375
transcript.pyannote[1635].speaker SPEAKER_22
transcript.pyannote[1635].start 9199.62284375
transcript.pyannote[1635].end 9220.46346875
transcript.pyannote[1636].speaker SPEAKER_22
transcript.pyannote[1636].start 9220.90221875
transcript.pyannote[1636].end 9226.31909375
transcript.pyannote[1637].speaker SPEAKER_27
transcript.pyannote[1637].start 9226.35284375
transcript.pyannote[1637].end 9226.82534375
transcript.pyannote[1638].speaker SPEAKER_27
transcript.pyannote[1638].start 9227.34846875
transcript.pyannote[1638].end 9230.01471875
transcript.pyannote[1639].speaker SPEAKER_27
transcript.pyannote[1639].start 9230.13284375
transcript.pyannote[1639].end 9230.72346875
transcript.pyannote[1640].speaker SPEAKER_27
transcript.pyannote[1640].start 9231.58409375
transcript.pyannote[1640].end 9234.84096875
transcript.pyannote[1641].speaker SPEAKER_22
transcript.pyannote[1641].start 9233.81159375
transcript.pyannote[1641].end 9260.82846875
transcript.pyannote[1642].speaker SPEAKER_27
transcript.pyannote[1642].start 9260.45721875
transcript.pyannote[1642].end 9260.62596875
transcript.pyannote[1643].speaker SPEAKER_27
transcript.pyannote[1643].start 9260.82846875
transcript.pyannote[1643].end 9260.94659375
transcript.pyannote[1644].speaker SPEAKER_22
transcript.pyannote[1644].start 9260.94659375
transcript.pyannote[1644].end 9260.96346875
transcript.pyannote[1645].speaker SPEAKER_27
transcript.pyannote[1645].start 9260.96346875
transcript.pyannote[1645].end 9262.90409375
transcript.pyannote[1646].speaker SPEAKER_22
transcript.pyannote[1646].start 9262.90409375
transcript.pyannote[1646].end 9262.97159375
transcript.pyannote[1647].speaker SPEAKER_27
transcript.pyannote[1647].start 9262.97159375
transcript.pyannote[1647].end 9264.28784375
transcript.pyannote[1648].speaker SPEAKER_22
transcript.pyannote[1648].start 9262.98846875
transcript.pyannote[1648].end 9267.66284375
transcript.pyannote[1649].speaker SPEAKER_27
transcript.pyannote[1649].start 9266.27909375
transcript.pyannote[1649].end 9272.74221875
transcript.pyannote[1650].speaker SPEAKER_22
transcript.pyannote[1650].start 9270.85221875
transcript.pyannote[1650].end 9271.17284375
transcript.pyannote[1651].speaker SPEAKER_22
transcript.pyannote[1651].start 9272.65784375
transcript.pyannote[1651].end 9273.06284375
transcript.pyannote[1652].speaker SPEAKER_27
transcript.pyannote[1652].start 9273.07971875
transcript.pyannote[1652].end 9276.15096875
transcript.pyannote[1653].speaker SPEAKER_27
transcript.pyannote[1653].start 9276.57284375
transcript.pyannote[1653].end 9285.73596875
transcript.pyannote[1654].speaker SPEAKER_22
transcript.pyannote[1654].start 9278.20971875
transcript.pyannote[1654].end 9278.74971875
transcript.pyannote[1655].speaker SPEAKER_22
transcript.pyannote[1655].start 9282.19221875
transcript.pyannote[1655].end 9306.82971875
transcript.pyannote[1656].speaker SPEAKER_27
transcript.pyannote[1656].start 9288.80721875
transcript.pyannote[1656].end 9289.75221875
transcript.pyannote[1657].speaker SPEAKER_00
transcript.pyannote[1657].start 9289.75221875
transcript.pyannote[1657].end 9289.90409375
transcript.pyannote[1658].speaker SPEAKER_00
transcript.pyannote[1658].start 9291.91221875
transcript.pyannote[1658].end 9292.23284375
transcript.pyannote[1659].speaker SPEAKER_22
transcript.pyannote[1659].start 9307.38659375
transcript.pyannote[1659].end 9329.91471875
transcript.pyannote[1660].speaker SPEAKER_22
transcript.pyannote[1660].start 9330.06659375
transcript.pyannote[1660].end 9336.31034375
transcript.pyannote[1661].speaker SPEAKER_22
transcript.pyannote[1661].start 9336.47909375
transcript.pyannote[1661].end 9347.19471875
transcript.pyannote[1662].speaker SPEAKER_27
transcript.pyannote[1662].start 9348.29159375
transcript.pyannote[1662].end 9348.56159375
transcript.pyannote[1663].speaker SPEAKER_27
transcript.pyannote[1663].start 9348.73034375
transcript.pyannote[1663].end 9349.94534375
transcript.pyannote[1664].speaker SPEAKER_22
transcript.pyannote[1664].start 9349.84409375
transcript.pyannote[1664].end 9443.98971875
transcript.pyannote[1665].speaker SPEAKER_22
transcript.pyannote[1665].start 9444.69846875
transcript.pyannote[1665].end 9445.01909375
transcript.pyannote[1666].speaker SPEAKER_27
transcript.pyannote[1666].start 9445.96409375
transcript.pyannote[1666].end 9449.25471875
transcript.pyannote[1667].speaker SPEAKER_27
transcript.pyannote[1667].start 9449.47409375
transcript.pyannote[1667].end 9452.74784375
transcript.pyannote[1668].speaker SPEAKER_22
transcript.pyannote[1668].start 9451.38096875
transcript.pyannote[1668].end 9453.16971875
transcript.pyannote[1669].speaker SPEAKER_27
transcript.pyannote[1669].start 9453.08534375
transcript.pyannote[1669].end 9456.69659375
transcript.pyannote[1670].speaker SPEAKER_22
transcript.pyannote[1670].start 9456.19034375
transcript.pyannote[1670].end 9482.11034375
transcript.pyannote[1671].speaker SPEAKER_28
transcript.pyannote[1671].start 9479.14034375
transcript.pyannote[1671].end 9479.17409375
transcript.pyannote[1672].speaker SPEAKER_03
transcript.pyannote[1672].start 9479.17409375
transcript.pyannote[1672].end 9479.46096875
transcript.pyannote[1673].speaker SPEAKER_03
transcript.pyannote[1673].start 9480.79409375
transcript.pyannote[1673].end 9480.94596875
transcript.pyannote[1674].speaker SPEAKER_02
transcript.pyannote[1674].start 9481.95846875
transcript.pyannote[1674].end 9482.04284375
transcript.pyannote[1675].speaker SPEAKER_03
transcript.pyannote[1675].start 9482.04284375
transcript.pyannote[1675].end 9482.07659375
transcript.pyannote[1676].speaker SPEAKER_27
transcript.pyannote[1676].start 9482.11034375
transcript.pyannote[1676].end 9482.16096875
transcript.pyannote[1677].speaker SPEAKER_22
transcript.pyannote[1677].start 9482.16096875
transcript.pyannote[1677].end 9483.62909375
transcript.pyannote[1678].speaker SPEAKER_27
transcript.pyannote[1678].start 9482.98784375
transcript.pyannote[1678].end 9483.07221875
transcript.pyannote[1679].speaker SPEAKER_03
transcript.pyannote[1679].start 9483.07221875
transcript.pyannote[1679].end 9483.08909375
transcript.pyannote[1680].speaker SPEAKER_27
transcript.pyannote[1680].start 9483.08909375
transcript.pyannote[1680].end 9483.10596875
transcript.pyannote[1681].speaker SPEAKER_03
transcript.pyannote[1681].start 9483.10596875
transcript.pyannote[1681].end 9483.13971875
transcript.pyannote[1682].speaker SPEAKER_03
transcript.pyannote[1682].start 9483.62909375
transcript.pyannote[1682].end 9483.64596875
transcript.pyannote[1683].speaker SPEAKER_27
transcript.pyannote[1683].start 9483.64596875
transcript.pyannote[1683].end 9484.13534375
transcript.pyannote[1684].speaker SPEAKER_03
transcript.pyannote[1684].start 9484.13534375
transcript.pyannote[1684].end 9484.25346875
transcript.pyannote[1685].speaker SPEAKER_03
transcript.pyannote[1685].start 9484.79346875
transcript.pyannote[1685].end 9486.54846875
transcript.pyannote[1686].speaker SPEAKER_03
transcript.pyannote[1686].start 9486.83534375
transcript.pyannote[1686].end 9489.06284375
transcript.pyannote[1687].speaker SPEAKER_06
transcript.pyannote[1687].start 9502.57971875
transcript.pyannote[1687].end 9507.01784375
transcript.pyannote[1688].speaker SPEAKER_06
transcript.pyannote[1688].start 9511.00034375
transcript.pyannote[1688].end 9511.82721875
transcript.pyannote[1689].speaker SPEAKER_06
transcript.pyannote[1689].start 9511.96221875
transcript.pyannote[1689].end 9538.40534375
transcript.pyannote[1690].speaker SPEAKER_27
transcript.pyannote[1690].start 9540.64971875
transcript.pyannote[1690].end 9542.30346875
transcript.pyannote[1691].speaker SPEAKER_06
transcript.pyannote[1691].start 9541.96596875
transcript.pyannote[1691].end 9544.36221875
transcript.pyannote[1692].speaker SPEAKER_06
transcript.pyannote[1692].start 9544.91909375
transcript.pyannote[1692].end 9550.03221875
transcript.pyannote[1693].speaker SPEAKER_06
transcript.pyannote[1693].start 9551.02784375
transcript.pyannote[1693].end 9551.60159375
transcript.pyannote[1694].speaker SPEAKER_27
transcript.pyannote[1694].start 9551.83784375
transcript.pyannote[1694].end 9555.70221875
transcript.pyannote[1695].speaker SPEAKER_06
transcript.pyannote[1695].start 9556.73159375
transcript.pyannote[1695].end 9574.18034375
transcript.pyannote[1696].speaker SPEAKER_06
transcript.pyannote[1696].start 9574.41659375
transcript.pyannote[1696].end 9639.58784375
transcript.pyannote[1697].speaker SPEAKER_06
transcript.pyannote[1697].start 9641.19096875
transcript.pyannote[1697].end 9642.65909375
transcript.pyannote[1698].speaker SPEAKER_06
transcript.pyannote[1698].start 9643.89096875
transcript.pyannote[1698].end 9644.54909375
transcript.pyannote[1699].speaker SPEAKER_06
transcript.pyannote[1699].start 9645.73034375
transcript.pyannote[1699].end 9649.07159375
transcript.pyannote[1700].speaker SPEAKER_27
transcript.pyannote[1700].start 9650.03346875
transcript.pyannote[1700].end 9660.02346875
transcript.pyannote[1701].speaker SPEAKER_06
transcript.pyannote[1701].start 9660.02346875
transcript.pyannote[1701].end 9660.76596875
transcript.pyannote[1702].speaker SPEAKER_27
transcript.pyannote[1702].start 9660.76596875
transcript.pyannote[1702].end 9661.03596875
transcript.pyannote[1703].speaker SPEAKER_06
transcript.pyannote[1703].start 9661.03596875
transcript.pyannote[1703].end 9661.98096875
transcript.pyannote[1704].speaker SPEAKER_21
transcript.pyannote[1704].start 9663.70221875
transcript.pyannote[1704].end 9669.96284375
transcript.pyannote[1705].speaker SPEAKER_28
transcript.pyannote[1705].start 9666.03096875
transcript.pyannote[1705].end 9666.04784375
transcript.pyannote[1706].speaker SPEAKER_06
transcript.pyannote[1706].start 9668.39346875
transcript.pyannote[1706].end 9685.35284375
transcript.pyannote[1707].speaker SPEAKER_06
transcript.pyannote[1707].start 9687.54659375
transcript.pyannote[1707].end 9693.65534375
transcript.pyannote[1708].speaker SPEAKER_06
transcript.pyannote[1708].start 9694.24596875
transcript.pyannote[1708].end 9726.74721875
transcript.pyannote[1709].speaker SPEAKER_06
transcript.pyannote[1709].start 9726.96659375
transcript.pyannote[1709].end 9740.51721875
transcript.pyannote[1710].speaker SPEAKER_06
transcript.pyannote[1710].start 9741.56346875
transcript.pyannote[1710].end 9748.98846875
transcript.pyannote[1711].speaker SPEAKER_06
transcript.pyannote[1711].start 9749.39346875
transcript.pyannote[1711].end 9769.66034375
transcript.pyannote[1712].speaker SPEAKER_06
transcript.pyannote[1712].start 9770.11596875
transcript.pyannote[1712].end 9773.40659375
transcript.pyannote[1713].speaker SPEAKER_06
transcript.pyannote[1713].start 9774.08159375
transcript.pyannote[1713].end 9775.44846875
transcript.pyannote[1714].speaker SPEAKER_06
transcript.pyannote[1714].start 9776.57909375
transcript.pyannote[1714].end 9777.74346875
transcript.pyannote[1715].speaker SPEAKER_27
transcript.pyannote[1715].start 9779.43096875
transcript.pyannote[1715].end 9786.14721875
transcript.pyannote[1716].speaker SPEAKER_27
transcript.pyannote[1716].start 9786.38346875
transcript.pyannote[1716].end 9792.88034375
transcript.pyannote[1717].speaker SPEAKER_06
transcript.pyannote[1717].start 9792.88034375
transcript.pyannote[1717].end 9821.31471875
transcript.pyannote[1718].speaker SPEAKER_27
transcript.pyannote[1718].start 9795.47909375
transcript.pyannote[1718].end 9795.86721875
transcript.pyannote[1719].speaker SPEAKER_06
transcript.pyannote[1719].start 9822.73221875
transcript.pyannote[1719].end 9838.03784375
transcript.pyannote[1720].speaker SPEAKER_06
transcript.pyannote[1720].start 9838.29096875
transcript.pyannote[1720].end 9839.03346875
transcript.pyannote[1721].speaker SPEAKER_06
transcript.pyannote[1721].start 9839.52284375
transcript.pyannote[1721].end 9848.34846875
transcript.pyannote[1722].speaker SPEAKER_06
transcript.pyannote[1722].start 9849.05721875
transcript.pyannote[1722].end 9854.77784375
transcript.pyannote[1723].speaker SPEAKER_06
transcript.pyannote[1723].start 9855.26721875
transcript.pyannote[1723].end 9861.64596875
transcript.pyannote[1724].speaker SPEAKER_06
transcript.pyannote[1724].start 9862.35471875
transcript.pyannote[1724].end 9864.34596875
transcript.pyannote[1725].speaker SPEAKER_06
transcript.pyannote[1725].start 9864.63284375
transcript.pyannote[1725].end 9865.59471875
transcript.pyannote[1726].speaker SPEAKER_06
transcript.pyannote[1726].start 9866.65784375
transcript.pyannote[1726].end 9915.42659375
transcript.pyannote[1727].speaker SPEAKER_06
transcript.pyannote[1727].start 9915.98346875
transcript.pyannote[1727].end 9916.16909375
transcript.pyannote[1728].speaker SPEAKER_06
transcript.pyannote[1728].start 9916.30409375
transcript.pyannote[1728].end 9921.92346875
transcript.pyannote[1729].speaker SPEAKER_06
transcript.pyannote[1729].start 9922.26096875
transcript.pyannote[1729].end 9942.93284375
transcript.pyannote[1730].speaker SPEAKER_06
transcript.pyannote[1730].start 9943.37159375
transcript.pyannote[1730].end 9952.02846875
transcript.pyannote[1731].speaker SPEAKER_06
transcript.pyannote[1731].start 9952.85534375
transcript.pyannote[1731].end 9963.35159375
transcript.pyannote[1732].speaker SPEAKER_06
transcript.pyannote[1732].start 9963.95909375
transcript.pyannote[1732].end 9969.42659375
transcript.pyannote[1733].speaker SPEAKER_06
transcript.pyannote[1733].start 9969.84846875
transcript.pyannote[1733].end 9975.16409375
transcript.pyannote[1734].speaker SPEAKER_06
transcript.pyannote[1734].start 9975.45096875
transcript.pyannote[1734].end 9981.55971875
transcript.pyannote[1735].speaker SPEAKER_06
transcript.pyannote[1735].start 9982.11659375
transcript.pyannote[1735].end 10000.32471875
transcript.pyannote[1736].speaker SPEAKER_06
transcript.pyannote[1736].start 10000.66221875
transcript.pyannote[1736].end 10007.71596875
transcript.pyannote[1737].speaker SPEAKER_06
transcript.pyannote[1737].start 10008.96471875
transcript.pyannote[1737].end 10009.01534375
transcript.pyannote[1738].speaker SPEAKER_06
transcript.pyannote[1738].start 10009.33596875
transcript.pyannote[1738].end 10018.36409375
transcript.pyannote[1739].speaker SPEAKER_06
transcript.pyannote[1739].start 10018.61721875
transcript.pyannote[1739].end 10022.16096875
transcript.pyannote[1740].speaker SPEAKER_06
transcript.pyannote[1740].start 10022.68409375
transcript.pyannote[1740].end 10027.00409375
transcript.pyannote[1741].speaker SPEAKER_06
transcript.pyannote[1741].start 10027.40909375
transcript.pyannote[1741].end 10041.92159375
transcript.pyannote[1742].speaker SPEAKER_06
transcript.pyannote[1742].start 10042.98471875
transcript.pyannote[1742].end 10048.45221875
transcript.pyannote[1743].speaker SPEAKER_06
transcript.pyannote[1743].start 10049.36346875
transcript.pyannote[1743].end 10054.07159375
transcript.pyannote[1744].speaker SPEAKER_06
transcript.pyannote[1744].start 10054.13909375
transcript.pyannote[1744].end 10057.12596875
transcript.pyannote[1745].speaker SPEAKER_00
transcript.pyannote[1745].start 10056.26534375
transcript.pyannote[1745].end 10057.02471875
transcript.pyannote[1746].speaker SPEAKER_06
transcript.pyannote[1746].start 10057.39596875
transcript.pyannote[1746].end 10060.23096875
transcript.pyannote[1747].speaker SPEAKER_06
transcript.pyannote[1747].start 10060.73721875
transcript.pyannote[1747].end 10074.92909375
transcript.pyannote[1748].speaker SPEAKER_06
transcript.pyannote[1748].start 10075.40159375
transcript.pyannote[1748].end 10085.59409375
transcript.pyannote[1749].speaker SPEAKER_06
transcript.pyannote[1749].start 10085.99909375
transcript.pyannote[1749].end 10091.17971875
transcript.pyannote[1750].speaker SPEAKER_06
transcript.pyannote[1750].start 10092.47909375
transcript.pyannote[1750].end 10105.15221875
transcript.pyannote[1751].speaker SPEAKER_06
transcript.pyannote[1751].start 10105.65846875
transcript.pyannote[1751].end 10107.04221875
transcript.pyannote[1752].speaker SPEAKER_06
transcript.pyannote[1752].start 10107.56534375
transcript.pyannote[1752].end 10108.89846875
transcript.pyannote[1753].speaker SPEAKER_06
transcript.pyannote[1753].start 10109.26971875
transcript.pyannote[1753].end 10115.64846875
transcript.pyannote[1754].speaker SPEAKER_06
transcript.pyannote[1754].start 10116.01971875
transcript.pyannote[1754].end 10123.98471875
transcript.pyannote[1755].speaker SPEAKER_06
transcript.pyannote[1755].start 10124.45721875
transcript.pyannote[1755].end 10130.66721875
transcript.pyannote[1756].speaker SPEAKER_06
transcript.pyannote[1756].start 10131.34221875
transcript.pyannote[1756].end 10133.35034375
transcript.pyannote[1757].speaker SPEAKER_06
transcript.pyannote[1757].start 10133.94096875
transcript.pyannote[1757].end 10147.35659375
transcript.pyannote[1758].speaker SPEAKER_06
transcript.pyannote[1758].start 10147.96409375
transcript.pyannote[1758].end 10167.77534375
transcript.pyannote[1759].speaker SPEAKER_06
transcript.pyannote[1759].start 10167.96096875
transcript.pyannote[1759].end 10169.04096875
transcript.pyannote[1760].speaker SPEAKER_06
transcript.pyannote[1760].start 10169.56409375
transcript.pyannote[1760].end 10170.94784375
transcript.pyannote[1761].speaker SPEAKER_06
transcript.pyannote[1761].start 10172.41596875
transcript.pyannote[1761].end 10189.93221875
transcript.pyannote[1762].speaker SPEAKER_06
transcript.pyannote[1762].start 10190.70846875
transcript.pyannote[1762].end 10192.32846875
transcript.pyannote[1763].speaker SPEAKER_06
transcript.pyannote[1763].start 10192.90221875
transcript.pyannote[1763].end 10197.18846875
transcript.pyannote[1764].speaker SPEAKER_06
transcript.pyannote[1764].start 10197.52596875
transcript.pyannote[1764].end 10199.39909375
transcript.pyannote[1765].speaker SPEAKER_06
transcript.pyannote[1765].start 10200.31034375
transcript.pyannote[1765].end 10203.44909375
transcript.pyannote[1766].speaker SPEAKER_06
transcript.pyannote[1766].start 10203.97221875
transcript.pyannote[1766].end 10207.44846875
transcript.pyannote[1767].speaker SPEAKER_06
transcript.pyannote[1767].start 10208.71409375
transcript.pyannote[1767].end 10221.57284375
transcript.pyannote[1768].speaker SPEAKER_06
transcript.pyannote[1768].start 10221.91034375
transcript.pyannote[1768].end 10226.34846875
transcript.pyannote[1769].speaker SPEAKER_06
transcript.pyannote[1769].start 10227.04034375
transcript.pyannote[1769].end 10233.14909375
transcript.pyannote[1770].speaker SPEAKER_06
transcript.pyannote[1770].start 10234.06034375
transcript.pyannote[1770].end 10235.66346875
transcript.pyannote[1771].speaker SPEAKER_06
transcript.pyannote[1771].start 10236.70971875
transcript.pyannote[1771].end 10244.42159375
transcript.pyannote[1772].speaker SPEAKER_06
transcript.pyannote[1772].start 10245.04596875
transcript.pyannote[1772].end 10248.45471875
transcript.pyannote[1773].speaker SPEAKER_06
transcript.pyannote[1773].start 10248.82596875
transcript.pyannote[1773].end 10258.42784375
transcript.pyannote[1774].speaker SPEAKER_06
transcript.pyannote[1774].start 10258.61346875
transcript.pyannote[1774].end 10259.37284375
transcript.pyannote[1775].speaker SPEAKER_06
transcript.pyannote[1775].start 10260.80721875
transcript.pyannote[1775].end 10279.08284375
transcript.pyannote[1776].speaker SPEAKER_06
transcript.pyannote[1776].start 10279.65659375
transcript.pyannote[1776].end 10291.84034375
transcript.pyannote[1777].speaker SPEAKER_06
transcript.pyannote[1777].start 10292.19471875
transcript.pyannote[1777].end 10293.61221875
transcript.pyannote[1778].speaker SPEAKER_06
transcript.pyannote[1778].start 10293.73034375
transcript.pyannote[1778].end 10299.53534375
transcript.pyannote[1779].speaker SPEAKER_06
transcript.pyannote[1779].start 10299.94034375
transcript.pyannote[1779].end 10322.87346875
transcript.pyannote[1780].speaker SPEAKER_06
transcript.pyannote[1780].start 10323.61596875
transcript.pyannote[1780].end 10334.83784375
transcript.pyannote[1781].speaker SPEAKER_06
transcript.pyannote[1781].start 10335.22596875
transcript.pyannote[1781].end 10357.26471875
transcript.pyannote[1782].speaker SPEAKER_06
transcript.pyannote[1782].start 10358.78346875
transcript.pyannote[1782].end 10364.20034375
transcript.pyannote[1783].speaker SPEAKER_27
transcript.pyannote[1783].start 10364.65596875
transcript.pyannote[1783].end 10365.21284375
transcript.pyannote[1784].speaker SPEAKER_27
transcript.pyannote[1784].start 10365.56721875
transcript.pyannote[1784].end 10377.02534375
transcript.pyannote[1785].speaker SPEAKER_06
transcript.pyannote[1785].start 10377.02534375
transcript.pyannote[1785].end 10381.90221875
transcript.pyannote[1786].speaker SPEAKER_27
transcript.pyannote[1786].start 10378.71284375
transcript.pyannote[1786].end 10379.25284375
transcript.pyannote[1787].speaker SPEAKER_27
transcript.pyannote[1787].start 10381.61534375
transcript.pyannote[1787].end 10382.32409375
transcript.pyannote[1788].speaker SPEAKER_06
transcript.pyannote[1788].start 10382.32409375
transcript.pyannote[1788].end 10384.31534375
transcript.pyannote[1789].speaker SPEAKER_27
transcript.pyannote[1789].start 10384.31534375
transcript.pyannote[1789].end 10384.50096875
transcript.pyannote[1790].speaker SPEAKER_06
transcript.pyannote[1790].start 10384.50096875
transcript.pyannote[1790].end 10384.97346875
transcript.pyannote[1791].speaker SPEAKER_27
transcript.pyannote[1791].start 10384.97346875
transcript.pyannote[1791].end 10399.97534375
transcript.pyannote[1792].speaker SPEAKER_06
transcript.pyannote[1792].start 10397.88284375
transcript.pyannote[1792].end 10449.53721875
transcript.pyannote[1793].speaker SPEAKER_03
transcript.pyannote[1793].start 10449.80721875
transcript.pyannote[1793].end 10456.03409375
transcript.pyannote[1794].speaker SPEAKER_06
transcript.pyannote[1794].start 10451.27534375
transcript.pyannote[1794].end 10451.66346875
transcript.pyannote[1795].speaker SPEAKER_06
transcript.pyannote[1795].start 10454.81909375
transcript.pyannote[1795].end 10458.00846875
transcript.pyannote[1796].speaker SPEAKER_06
transcript.pyannote[1796].start 10459.45971875
transcript.pyannote[1796].end 10466.96909375
transcript.pyannote[1797].speaker SPEAKER_27
transcript.pyannote[1797].start 10466.96909375
transcript.pyannote[1797].end 10473.16221875
transcript.pyannote[1798].speaker SPEAKER_28
transcript.pyannote[1798].start 10472.25096875
transcript.pyannote[1798].end 10472.80784375
transcript.pyannote[1799].speaker SPEAKER_06
transcript.pyannote[1799].start 10472.80784375
transcript.pyannote[1799].end 10473.09471875
transcript.pyannote[1800].speaker SPEAKER_06
transcript.pyannote[1800].start 10473.16221875
transcript.pyannote[1800].end 10473.19596875
transcript.pyannote[1801].speaker SPEAKER_27
transcript.pyannote[1801].start 10473.19596875
transcript.pyannote[1801].end 10474.02284375
transcript.pyannote[1802].speaker SPEAKER_06
transcript.pyannote[1802].start 10474.02284375
transcript.pyannote[1802].end 10481.31284375
transcript.pyannote[1803].speaker SPEAKER_27
transcript.pyannote[1803].start 10477.34721875
transcript.pyannote[1803].end 10477.97159375
transcript.pyannote[1804].speaker SPEAKER_05
transcript.pyannote[1804].start 10477.97159375
transcript.pyannote[1804].end 10478.41034375
transcript.pyannote[1805].speaker SPEAKER_27
transcript.pyannote[1805].start 10478.41034375
transcript.pyannote[1805].end 10478.96721875
transcript.pyannote[1806].speaker SPEAKER_05
transcript.pyannote[1806].start 10478.96721875
transcript.pyannote[1806].end 10479.18659375
transcript.pyannote[1807].speaker SPEAKER_03
transcript.pyannote[1807].start 10481.88659375
transcript.pyannote[1807].end 10485.17721875
transcript.pyannote[1808].speaker SPEAKER_03
transcript.pyannote[1808].start 10486.27409375
transcript.pyannote[1808].end 10488.77159375
transcript.pyannote[1809].speaker SPEAKER_06
transcript.pyannote[1809].start 10486.99971875
transcript.pyannote[1809].end 10488.28221875
transcript.pyannote[1810].speaker SPEAKER_06
transcript.pyannote[1810].start 10488.61971875
transcript.pyannote[1810].end 10499.72346875
transcript.pyannote[1811].speaker SPEAKER_06
transcript.pyannote[1811].start 10499.99346875
transcript.pyannote[1811].end 10518.50534375
transcript.pyannote[1812].speaker SPEAKER_27
transcript.pyannote[1812].start 10509.30846875
transcript.pyannote[1812].end 10509.57846875
transcript.pyannote[1813].speaker SPEAKER_00
transcript.pyannote[1813].start 10509.57846875
transcript.pyannote[1813].end 10509.96659375
transcript.pyannote[1814].speaker SPEAKER_27
transcript.pyannote[1814].start 10509.96659375
transcript.pyannote[1814].end 10510.11846875
transcript.pyannote[1815].speaker SPEAKER_27
transcript.pyannote[1815].start 10518.01596875
transcript.pyannote[1815].end 10534.97534375
transcript.pyannote[1816].speaker SPEAKER_06
transcript.pyannote[1816].start 10534.97534375
transcript.pyannote[1816].end 10539.37971875
transcript.pyannote[1817].speaker SPEAKER_27
transcript.pyannote[1817].start 10535.07659375
transcript.pyannote[1817].end 10537.62471875
transcript.pyannote[1818].speaker SPEAKER_06
transcript.pyannote[1818].start 10539.80159375
transcript.pyannote[1818].end 10540.44284375
transcript.pyannote[1819].speaker SPEAKER_06
transcript.pyannote[1819].start 10540.84784375
transcript.pyannote[1819].end 10541.05034375
transcript.pyannote[1820].speaker SPEAKER_03
transcript.pyannote[1820].start 10541.30346875
transcript.pyannote[1820].end 10544.13846875
transcript.pyannote[1821].speaker SPEAKER_06
transcript.pyannote[1821].start 10543.31159375
transcript.pyannote[1821].end 10565.85659375
transcript.pyannote[1822].speaker SPEAKER_03
transcript.pyannote[1822].start 10565.85659375
transcript.pyannote[1822].end 10566.17721875
transcript.pyannote[1823].speaker SPEAKER_06
transcript.pyannote[1823].start 10566.17721875
transcript.pyannote[1823].end 10566.71721875
transcript.pyannote[1824].speaker SPEAKER_03
transcript.pyannote[1824].start 10566.22784375
transcript.pyannote[1824].end 10569.95721875
transcript.pyannote[1825].speaker SPEAKER_03
transcript.pyannote[1825].start 10569.97409375
transcript.pyannote[1825].end 10570.02471875
transcript.pyannote[1826].speaker SPEAKER_03
transcript.pyannote[1826].start 10570.51409375
transcript.pyannote[1826].end 10570.59846875
transcript.pyannote[1827].speaker SPEAKER_03
transcript.pyannote[1827].start 10570.90221875
transcript.pyannote[1827].end 10579.45784375
transcript.pyannote[1828].speaker SPEAKER_26
transcript.pyannote[1828].start 10588.57034375
transcript.pyannote[1828].end 10590.81471875
transcript.pyannote[1829].speaker SPEAKER_26
transcript.pyannote[1829].start 10599.82596875
transcript.pyannote[1829].end 10602.10409375
transcript.pyannote[1830].speaker SPEAKER_26
transcript.pyannote[1830].start 10602.39096875
transcript.pyannote[1830].end 10606.98096875
transcript.pyannote[1831].speaker SPEAKER_26
transcript.pyannote[1831].start 10607.41971875
transcript.pyannote[1831].end 10615.08096875
transcript.pyannote[1832].speaker SPEAKER_26
transcript.pyannote[1832].start 10615.70534375
transcript.pyannote[1832].end 10620.24471875
transcript.pyannote[1833].speaker SPEAKER_26
transcript.pyannote[1833].start 10621.00409375
transcript.pyannote[1833].end 10624.59846875
transcript.pyannote[1834].speaker SPEAKER_26
transcript.pyannote[1834].start 10624.80096875
transcript.pyannote[1834].end 10628.51346875
transcript.pyannote[1835].speaker SPEAKER_26
transcript.pyannote[1835].start 10629.13784375
transcript.pyannote[1835].end 10632.59721875
transcript.pyannote[1836].speaker SPEAKER_26
transcript.pyannote[1836].start 10633.15409375
transcript.pyannote[1836].end 10634.47034375
transcript.pyannote[1837].speaker SPEAKER_26
transcript.pyannote[1837].start 10634.84159375
transcript.pyannote[1837].end 10637.20409375
transcript.pyannote[1838].speaker SPEAKER_26
transcript.pyannote[1838].start 10637.72721875
transcript.pyannote[1838].end 10640.08971875
transcript.pyannote[1839].speaker SPEAKER_26
transcript.pyannote[1839].start 10640.10659375
transcript.pyannote[1839].end 10642.62096875
transcript.pyannote[1840].speaker SPEAKER_28
transcript.pyannote[1840].start 10642.50284375
transcript.pyannote[1840].end 10642.51971875
transcript.pyannote[1841].speaker SPEAKER_28
transcript.pyannote[1841].start 10642.53659375
transcript.pyannote[1841].end 10642.87409375
transcript.pyannote[1842].speaker SPEAKER_26
transcript.pyannote[1842].start 10642.77284375
transcript.pyannote[1842].end 10657.06596875
transcript.pyannote[1843].speaker SPEAKER_26
transcript.pyannote[1843].start 10657.40346875
transcript.pyannote[1843].end 10665.28409375
transcript.pyannote[1844].speaker SPEAKER_26
transcript.pyannote[1844].start 10665.70596875
transcript.pyannote[1844].end 10684.89284375
transcript.pyannote[1845].speaker SPEAKER_26
transcript.pyannote[1845].start 10685.44971875
transcript.pyannote[1845].end 10687.64346875
transcript.pyannote[1846].speaker SPEAKER_26
transcript.pyannote[1846].start 10688.26784375
transcript.pyannote[1846].end 10689.43221875
transcript.pyannote[1847].speaker SPEAKER_26
transcript.pyannote[1847].start 10689.97221875
transcript.pyannote[1847].end 10690.61346875
transcript.pyannote[1848].speaker SPEAKER_27
transcript.pyannote[1848].start 10691.44034375
transcript.pyannote[1848].end 10698.40971875
transcript.pyannote[1849].speaker SPEAKER_26
transcript.pyannote[1849].start 10697.11034375
transcript.pyannote[1849].end 10698.29159375
transcript.pyannote[1850].speaker SPEAKER_26
transcript.pyannote[1850].start 10698.40971875
transcript.pyannote[1850].end 10699.64159375
transcript.pyannote[1851].speaker SPEAKER_26
transcript.pyannote[1851].start 10700.36721875
transcript.pyannote[1851].end 10704.24846875
transcript.pyannote[1852].speaker SPEAKER_26
transcript.pyannote[1852].start 10704.95721875
transcript.pyannote[1852].end 10706.23971875
transcript.pyannote[1853].speaker SPEAKER_26
transcript.pyannote[1853].start 10706.61096875
transcript.pyannote[1853].end 10706.67846875
transcript.pyannote[1854].speaker SPEAKER_28
transcript.pyannote[1854].start 10706.67846875
transcript.pyannote[1854].end 10709.74971875
transcript.pyannote[1855].speaker SPEAKER_26
transcript.pyannote[1855].start 10706.74596875
transcript.pyannote[1855].end 10732.58159375
transcript.pyannote[1856].speaker SPEAKER_00
transcript.pyannote[1856].start 10716.22971875
transcript.pyannote[1856].end 10716.24659375
transcript.pyannote[1857].speaker SPEAKER_00
transcript.pyannote[1857].start 10727.06346875
transcript.pyannote[1857].end 10727.58659375
transcript.pyannote[1858].speaker SPEAKER_00
transcript.pyannote[1858].start 10729.57784375
transcript.pyannote[1858].end 10729.79721875
transcript.pyannote[1859].speaker SPEAKER_26
transcript.pyannote[1859].start 10733.39159375
transcript.pyannote[1859].end 10740.71534375
transcript.pyannote[1860].speaker SPEAKER_26
transcript.pyannote[1860].start 10741.87971875
transcript.pyannote[1860].end 10750.85721875
transcript.pyannote[1861].speaker SPEAKER_26
transcript.pyannote[1861].start 10751.19471875
transcript.pyannote[1861].end 10753.03409375
transcript.pyannote[1862].speaker SPEAKER_26
transcript.pyannote[1862].start 10753.48971875
transcript.pyannote[1862].end 10755.43034375
transcript.pyannote[1863].speaker SPEAKER_26
transcript.pyannote[1863].start 10755.58221875
transcript.pyannote[1863].end 10771.71471875
transcript.pyannote[1864].speaker SPEAKER_27
transcript.pyannote[1864].start 10771.71471875
transcript.pyannote[1864].end 10777.30034375
transcript.pyannote[1865].speaker SPEAKER_27
transcript.pyannote[1865].start 10777.80659375
transcript.pyannote[1865].end 10781.95784375
transcript.pyannote[1866].speaker SPEAKER_27
transcript.pyannote[1866].start 10782.46409375
transcript.pyannote[1866].end 10782.86909375
transcript.pyannote[1867].speaker SPEAKER_27
transcript.pyannote[1867].start 10783.18971875
transcript.pyannote[1867].end 10784.55659375
transcript.pyannote[1868].speaker SPEAKER_27
transcript.pyannote[1868].start 10785.01221875
transcript.pyannote[1868].end 10789.82159375
transcript.pyannote[1869].speaker SPEAKER_27
transcript.pyannote[1869].start 10790.09159375
transcript.pyannote[1869].end 10794.86721875
transcript.pyannote[1870].speaker SPEAKER_27
transcript.pyannote[1870].start 10795.10346875
transcript.pyannote[1870].end 10796.23409375
transcript.pyannote[1871].speaker SPEAKER_27
transcript.pyannote[1871].start 10796.87534375
transcript.pyannote[1871].end 10798.57971875
transcript.pyannote[1872].speaker SPEAKER_27
transcript.pyannote[1872].start 10798.78221875
transcript.pyannote[1872].end 10804.48596875
transcript.pyannote[1873].speaker SPEAKER_27
transcript.pyannote[1873].start 10804.51971875
transcript.pyannote[1873].end 10809.02534375
transcript.pyannote[1874].speaker SPEAKER_26
transcript.pyannote[1874].start 10809.02534375
transcript.pyannote[1874].end 10816.58534375
transcript.pyannote[1875].speaker SPEAKER_27
transcript.pyannote[1875].start 10809.24471875
transcript.pyannote[1875].end 10811.99534375
transcript.pyannote[1876].speaker SPEAKER_26
transcript.pyannote[1876].start 10816.85534375
transcript.pyannote[1876].end 10816.99034375
transcript.pyannote[1877].speaker SPEAKER_26
transcript.pyannote[1877].start 10817.29409375
transcript.pyannote[1877].end 10821.27659375
transcript.pyannote[1878].speaker SPEAKER_27
transcript.pyannote[1878].start 10817.46284375
transcript.pyannote[1878].end 10817.76659375
transcript.pyannote[1879].speaker SPEAKER_28
transcript.pyannote[1879].start 10817.76659375
transcript.pyannote[1879].end 10817.81721875
transcript.pyannote[1880].speaker SPEAKER_27
transcript.pyannote[1880].start 10817.81721875
transcript.pyannote[1880].end 10817.93534375
transcript.pyannote[1881].speaker SPEAKER_26
transcript.pyannote[1881].start 10821.71534375
transcript.pyannote[1881].end 10831.35096875
transcript.pyannote[1882].speaker SPEAKER_27
transcript.pyannote[1882].start 10827.36846875
transcript.pyannote[1882].end 10841.47596875
transcript.pyannote[1883].speaker SPEAKER_26
transcript.pyannote[1883].start 10831.68846875
transcript.pyannote[1883].end 10832.00909375
transcript.pyannote[1884].speaker SPEAKER_26
transcript.pyannote[1884].start 10839.53534375
transcript.pyannote[1884].end 10854.35159375
transcript.pyannote[1885].speaker SPEAKER_27
transcript.pyannote[1885].start 10842.62346875
transcript.pyannote[1885].end 10843.43346875
transcript.pyannote[1886].speaker SPEAKER_27
transcript.pyannote[1886].start 10844.93534375
transcript.pyannote[1886].end 10848.74909375
transcript.pyannote[1887].speaker SPEAKER_03
transcript.pyannote[1887].start 10848.74909375
transcript.pyannote[1887].end 10848.81659375
transcript.pyannote[1888].speaker SPEAKER_28
transcript.pyannote[1888].start 10848.81659375
transcript.pyannote[1888].end 10848.83346875
transcript.pyannote[1889].speaker SPEAKER_27
transcript.pyannote[1889].start 10849.91346875
transcript.pyannote[1889].end 10853.03534375
transcript.pyannote[1890].speaker SPEAKER_27
transcript.pyannote[1890].start 10853.05221875
transcript.pyannote[1890].end 10866.61971875
transcript.pyannote[1891].speaker SPEAKER_26
transcript.pyannote[1891].start 10859.61659375
transcript.pyannote[1891].end 10860.40971875
transcript.pyannote[1892].speaker SPEAKER_26
transcript.pyannote[1892].start 10860.78096875
transcript.pyannote[1892].end 10861.96221875
transcript.pyannote[1893].speaker SPEAKER_26
transcript.pyannote[1893].start 10862.02971875
transcript.pyannote[1893].end 10862.06346875
transcript.pyannote[1894].speaker SPEAKER_26
transcript.pyannote[1894].start 10862.13096875
transcript.pyannote[1894].end 10863.85221875
transcript.pyannote[1895].speaker SPEAKER_26
transcript.pyannote[1895].start 10863.98721875
transcript.pyannote[1895].end 10865.60721875
transcript.pyannote[1896].speaker SPEAKER_26
transcript.pyannote[1896].start 10865.97846875
transcript.pyannote[1896].end 10866.02909375
transcript.pyannote[1897].speaker SPEAKER_27
transcript.pyannote[1897].start 10866.75471875
transcript.pyannote[1897].end 10869.87659375
transcript.pyannote[1898].speaker SPEAKER_26
transcript.pyannote[1898].start 10867.02471875
transcript.pyannote[1898].end 10869.84284375
transcript.pyannote[1899].speaker SPEAKER_27
transcript.pyannote[1899].start 10870.24784375
transcript.pyannote[1899].end 10870.39971875
transcript.pyannote[1900].speaker SPEAKER_26
transcript.pyannote[1900].start 10870.39971875
transcript.pyannote[1900].end 10870.41659375
transcript.pyannote[1901].speaker SPEAKER_26
transcript.pyannote[1901].start 10870.73721875
transcript.pyannote[1901].end 10873.70721875
transcript.pyannote[1902].speaker SPEAKER_27
transcript.pyannote[1902].start 10871.85096875
transcript.pyannote[1902].end 10873.35284375
transcript.pyannote[1903].speaker SPEAKER_27
transcript.pyannote[1903].start 10874.17971875
transcript.pyannote[1903].end 10874.19659375
transcript.pyannote[1904].speaker SPEAKER_26
transcript.pyannote[1904].start 10874.19659375
transcript.pyannote[1904].end 10876.37346875
transcript.pyannote[1905].speaker SPEAKER_26
transcript.pyannote[1905].start 10876.69409375
transcript.pyannote[1905].end 10911.54096875
transcript.pyannote[1906].speaker SPEAKER_26
transcript.pyannote[1906].start 10912.24971875
transcript.pyannote[1906].end 10912.97534375
transcript.pyannote[1907].speaker SPEAKER_27
transcript.pyannote[1907].start 10912.45221875
transcript.pyannote[1907].end 10913.17784375
transcript.pyannote[1908].speaker SPEAKER_26
transcript.pyannote[1908].start 10913.17784375
transcript.pyannote[1908].end 10913.19471875
transcript.pyannote[1909].speaker SPEAKER_27
transcript.pyannote[1909].start 10913.19471875
transcript.pyannote[1909].end 10913.22846875
transcript.pyannote[1910].speaker SPEAKER_26
transcript.pyannote[1910].start 10913.22846875
transcript.pyannote[1910].end 10913.97096875
transcript.pyannote[1911].speaker SPEAKER_27
transcript.pyannote[1911].start 10913.97096875
transcript.pyannote[1911].end 10915.96221875
transcript.pyannote[1912].speaker SPEAKER_26
transcript.pyannote[1912].start 10915.96221875
transcript.pyannote[1912].end 10916.97471875
transcript.pyannote[1913].speaker SPEAKER_27
transcript.pyannote[1913].start 10916.97471875
transcript.pyannote[1913].end 10917.02534375
transcript.pyannote[1914].speaker SPEAKER_26
transcript.pyannote[1914].start 10917.02534375
transcript.pyannote[1914].end 10929.39471875
transcript.pyannote[1915].speaker SPEAKER_27
transcript.pyannote[1915].start 10917.56534375
transcript.pyannote[1915].end 10918.20659375
transcript.pyannote[1916].speaker SPEAKER_27
transcript.pyannote[1916].start 10920.06284375
transcript.pyannote[1916].end 10922.02034375
transcript.pyannote[1917].speaker SPEAKER_27
transcript.pyannote[1917].start 10922.13846875
transcript.pyannote[1917].end 10922.15534375
transcript.pyannote[1918].speaker SPEAKER_27
transcript.pyannote[1918].start 10922.29034375
transcript.pyannote[1918].end 10923.84284375
transcript.pyannote[1919].speaker SPEAKER_27
transcript.pyannote[1919].start 10925.31096875
transcript.pyannote[1919].end 10927.42034375
transcript.pyannote[1920].speaker SPEAKER_27
transcript.pyannote[1920].start 10928.61846875
transcript.pyannote[1920].end 10929.37784375
transcript.pyannote[1921].speaker SPEAKER_27
transcript.pyannote[1921].start 10929.39471875
transcript.pyannote[1921].end 10929.85034375
transcript.pyannote[1922].speaker SPEAKER_26
transcript.pyannote[1922].start 10929.85034375
transcript.pyannote[1922].end 10930.93034375
transcript.pyannote[1923].speaker SPEAKER_27
transcript.pyannote[1923].start 10929.86721875
transcript.pyannote[1923].end 10931.35221875
transcript.pyannote[1924].speaker SPEAKER_27
transcript.pyannote[1924].start 10931.63909375
transcript.pyannote[1924].end 10936.54971875
transcript.pyannote[1925].speaker SPEAKER_26
transcript.pyannote[1925].start 10931.74034375
transcript.pyannote[1925].end 10933.63034375
transcript.pyannote[1926].speaker SPEAKER_26
transcript.pyannote[1926].start 10935.68909375
transcript.pyannote[1926].end 10936.36409375
transcript.pyannote[1927].speaker SPEAKER_26
transcript.pyannote[1927].start 10936.54971875
transcript.pyannote[1927].end 10942.96221875
transcript.pyannote[1928].speaker SPEAKER_27
transcript.pyannote[1928].start 10939.08096875
transcript.pyannote[1928].end 10939.65471875
transcript.pyannote[1929].speaker SPEAKER_27
transcript.pyannote[1929].start 10940.65034375
transcript.pyannote[1929].end 10941.32534375
transcript.pyannote[1930].speaker SPEAKER_27
transcript.pyannote[1930].start 10942.96221875
transcript.pyannote[1930].end 10950.03284375
transcript.pyannote[1931].speaker SPEAKER_26
transcript.pyannote[1931].start 10943.82284375
transcript.pyannote[1931].end 10944.19409375
transcript.pyannote[1932].speaker SPEAKER_26
transcript.pyannote[1932].start 10947.45096875
transcript.pyannote[1932].end 10957.17096875
transcript.pyannote[1933].speaker SPEAKER_27
transcript.pyannote[1933].start 10951.48409375
transcript.pyannote[1933].end 10954.48784375
transcript.pyannote[1934].speaker SPEAKER_27
transcript.pyannote[1934].start 10955.17971875
transcript.pyannote[1934].end 10966.09784375
transcript.pyannote[1935].speaker SPEAKER_26
transcript.pyannote[1935].start 10960.47846875
transcript.pyannote[1935].end 10961.59221875
transcript.pyannote[1936].speaker SPEAKER_26
transcript.pyannote[1936].start 10966.09784375
transcript.pyannote[1936].end 10969.45596875
transcript.pyannote[1937].speaker SPEAKER_27
transcript.pyannote[1937].start 10966.16534375
transcript.pyannote[1937].end 10966.51971875
transcript.pyannote[1938].speaker SPEAKER_27
transcript.pyannote[1938].start 10966.85721875
transcript.pyannote[1938].end 10968.83159375
transcript.pyannote[1939].speaker SPEAKER_26
transcript.pyannote[1939].start 10969.84409375
transcript.pyannote[1939].end 10976.12159375
transcript.pyannote[1940].speaker SPEAKER_26
transcript.pyannote[1940].start 10976.49284375
transcript.pyannote[1940].end 10986.02721875
transcript.pyannote[1941].speaker SPEAKER_27
transcript.pyannote[1941].start 10983.88409375
transcript.pyannote[1941].end 10995.71346875
transcript.pyannote[1942].speaker SPEAKER_26
transcript.pyannote[1942].start 10989.84096875
transcript.pyannote[1942].end 10990.54971875
transcript.pyannote[1943].speaker SPEAKER_26
transcript.pyannote[1943].start 10991.41034375
transcript.pyannote[1943].end 10992.67596875
transcript.pyannote[1944].speaker SPEAKER_26
transcript.pyannote[1944].start 10994.31284375
transcript.pyannote[1944].end 11002.68284375
transcript.pyannote[1945].speaker SPEAKER_27
transcript.pyannote[1945].start 10995.94971875
transcript.pyannote[1945].end 10996.38846875
transcript.pyannote[1946].speaker SPEAKER_27
transcript.pyannote[1946].start 11000.96159375
transcript.pyannote[1946].end 11007.37409375
transcript.pyannote[1947].speaker SPEAKER_26
transcript.pyannote[1947].start 11003.35784375
transcript.pyannote[1947].end 11003.71221875
transcript.pyannote[1948].speaker SPEAKER_26
transcript.pyannote[1948].start 11005.63596875
transcript.pyannote[1948].end 11005.93971875
transcript.pyannote[1949].speaker SPEAKER_26
transcript.pyannote[1949].start 11006.69909375
transcript.pyannote[1949].end 11009.63534375
transcript.pyannote[1950].speaker SPEAKER_26
transcript.pyannote[1950].start 11009.78721875
transcript.pyannote[1950].end 11012.33534375
transcript.pyannote[1951].speaker SPEAKER_26
transcript.pyannote[1951].start 11012.87534375
transcript.pyannote[1951].end 11018.41034375
transcript.pyannote[1952].speaker SPEAKER_27
transcript.pyannote[1952].start 11015.54159375
transcript.pyannote[1952].end 11015.64284375
transcript.pyannote[1953].speaker SPEAKER_26
transcript.pyannote[1953].start 11018.79846875
transcript.pyannote[1953].end 11088.10409375
transcript.pyannote[1954].speaker SPEAKER_03
transcript.pyannote[1954].start 11081.32034375
transcript.pyannote[1954].end 11081.80971875
transcript.pyannote[1955].speaker SPEAKER_03
transcript.pyannote[1955].start 11082.51846875
transcript.pyannote[1955].end 11094.34784375
transcript.pyannote[1956].speaker SPEAKER_02
transcript.pyannote[1956].start 11088.10409375
transcript.pyannote[1956].end 11088.42471875
transcript.pyannote[1957].speaker SPEAKER_03
transcript.pyannote[1957].start 11094.93846875
transcript.pyannote[1957].end 11102.61659375
transcript.pyannote[1958].speaker SPEAKER_04
transcript.pyannote[1958].start 11113.16346875
transcript.pyannote[1958].end 11115.23909375
transcript.pyannote[1959].speaker SPEAKER_03
transcript.pyannote[1959].start 11115.34034375
transcript.pyannote[1959].end 11116.13346875
transcript.pyannote[1960].speaker SPEAKER_04
transcript.pyannote[1960].start 11119.69409375
transcript.pyannote[1960].end 11131.65846875
transcript.pyannote[1961].speaker SPEAKER_03
transcript.pyannote[1961].start 11119.72784375
transcript.pyannote[1961].end 11119.87971875
transcript.pyannote[1962].speaker SPEAKER_28
transcript.pyannote[1962].start 11119.87971875
transcript.pyannote[1962].end 11120.21721875
transcript.pyannote[1963].speaker SPEAKER_04
transcript.pyannote[1963].start 11131.91159375
transcript.pyannote[1963].end 11132.46846875
transcript.pyannote[1964].speaker SPEAKER_04
transcript.pyannote[1964].start 11132.70471875
transcript.pyannote[1964].end 11133.05909375
transcript.pyannote[1965].speaker SPEAKER_04
transcript.pyannote[1965].start 11134.18971875
transcript.pyannote[1965].end 11135.10096875
transcript.pyannote[1966].speaker SPEAKER_04
transcript.pyannote[1966].start 11135.43846875
transcript.pyannote[1966].end 11139.28596875
transcript.pyannote[1967].speaker SPEAKER_04
transcript.pyannote[1967].start 11139.85971875
transcript.pyannote[1967].end 11161.22346875
transcript.pyannote[1968].speaker SPEAKER_04
transcript.pyannote[1968].start 11161.66221875
transcript.pyannote[1968].end 11163.26534375
transcript.pyannote[1969].speaker SPEAKER_04
transcript.pyannote[1969].start 11163.83909375
transcript.pyannote[1969].end 11181.49034375
transcript.pyannote[1970].speaker SPEAKER_04
transcript.pyannote[1970].start 11182.24971875
transcript.pyannote[1970].end 11189.45534375
transcript.pyannote[1971].speaker SPEAKER_04
transcript.pyannote[1971].start 11189.96159375
transcript.pyannote[1971].end 11202.85409375
transcript.pyannote[1972].speaker SPEAKER_04
transcript.pyannote[1972].start 11203.15784375
transcript.pyannote[1972].end 11204.35596875
transcript.pyannote[1973].speaker SPEAKER_04
transcript.pyannote[1973].start 11204.74409375
transcript.pyannote[1973].end 11208.03471875
transcript.pyannote[1974].speaker SPEAKER_04
transcript.pyannote[1974].start 11208.32159375
transcript.pyannote[1974].end 11208.74346875
transcript.pyannote[1975].speaker SPEAKER_04
transcript.pyannote[1975].start 11209.67159375
transcript.pyannote[1975].end 11228.06534375
transcript.pyannote[1976].speaker SPEAKER_04
transcript.pyannote[1976].start 11228.09909375
transcript.pyannote[1976].end 11228.68971875
transcript.pyannote[1977].speaker SPEAKER_04
transcript.pyannote[1977].start 11229.26346875
transcript.pyannote[1977].end 11250.89721875
transcript.pyannote[1978].speaker SPEAKER_04
transcript.pyannote[1978].start 11251.18409375
transcript.pyannote[1978].end 11257.22534375
transcript.pyannote[1979].speaker SPEAKER_04
transcript.pyannote[1979].start 11257.51221875
transcript.pyannote[1979].end 11264.27909375
transcript.pyannote[1980].speaker SPEAKER_00
transcript.pyannote[1980].start 11259.97596875
transcript.pyannote[1980].end 11260.06034375
transcript.pyannote[1981].speaker SPEAKER_28
transcript.pyannote[1981].start 11260.06034375
transcript.pyannote[1981].end 11260.07721875
transcript.pyannote[1982].speaker SPEAKER_00
transcript.pyannote[1982].start 11260.07721875
transcript.pyannote[1982].end 11260.46534375
transcript.pyannote[1983].speaker SPEAKER_00
transcript.pyannote[1983].start 11261.34284375
transcript.pyannote[1983].end 11261.35971875
transcript.pyannote[1984].speaker SPEAKER_28
transcript.pyannote[1984].start 11261.35971875
transcript.pyannote[1984].end 11261.37659375
transcript.pyannote[1985].speaker SPEAKER_00
transcript.pyannote[1985].start 11261.37659375
transcript.pyannote[1985].end 11261.47784375
transcript.pyannote[1986].speaker SPEAKER_28
transcript.pyannote[1986].start 11261.47784375
transcript.pyannote[1986].end 11261.49471875
transcript.pyannote[1987].speaker SPEAKER_00
transcript.pyannote[1987].start 11261.49471875
transcript.pyannote[1987].end 11261.56221875
transcript.pyannote[1988].speaker SPEAKER_04
transcript.pyannote[1988].start 11264.39721875
transcript.pyannote[1988].end 11268.80159375
transcript.pyannote[1989].speaker SPEAKER_04
transcript.pyannote[1989].start 11269.17284375
transcript.pyannote[1989].end 11274.70784375
transcript.pyannote[1990].speaker SPEAKER_28
transcript.pyannote[1990].start 11273.91471875
transcript.pyannote[1990].end 11274.01596875
transcript.pyannote[1991].speaker SPEAKER_04
transcript.pyannote[1991].start 11275.09596875
transcript.pyannote[1991].end 11288.47784375
transcript.pyannote[1992].speaker SPEAKER_04
transcript.pyannote[1992].start 11288.79846875
transcript.pyannote[1992].end 11289.62534375
transcript.pyannote[1993].speaker SPEAKER_04
transcript.pyannote[1993].start 11289.97971875
transcript.pyannote[1993].end 11293.64159375
transcript.pyannote[1994].speaker SPEAKER_27
transcript.pyannote[1994].start 11293.15221875
transcript.pyannote[1994].end 11293.18596875
transcript.pyannote[1995].speaker SPEAKER_27
transcript.pyannote[1995].start 11293.75971875
transcript.pyannote[1995].end 11304.88034375
transcript.pyannote[1996].speaker SPEAKER_27
transcript.pyannote[1996].start 11305.09971875
transcript.pyannote[1996].end 11305.50471875
transcript.pyannote[1997].speaker SPEAKER_27
transcript.pyannote[1997].start 11305.94346875
transcript.pyannote[1997].end 11312.03534375
transcript.pyannote[1998].speaker SPEAKER_04
transcript.pyannote[1998].start 11312.03534375
transcript.pyannote[1998].end 11324.97846875
transcript.pyannote[1999].speaker SPEAKER_27
transcript.pyannote[1999].start 11322.04221875
transcript.pyannote[1999].end 11322.17721875
transcript.pyannote[2000].speaker SPEAKER_27
transcript.pyannote[2000].start 11324.23596875
transcript.pyannote[2000].end 11324.53971875
transcript.pyannote[2001].speaker SPEAKER_27
transcript.pyannote[2001].start 11324.97846875
transcript.pyannote[2001].end 11331.05346875
transcript.pyannote[2002].speaker SPEAKER_27
transcript.pyannote[2002].start 11331.37409375
transcript.pyannote[2002].end 11334.56346875
transcript.pyannote[2003].speaker SPEAKER_27
transcript.pyannote[2003].start 11335.00221875
transcript.pyannote[2003].end 11339.17034375
transcript.pyannote[2004].speaker SPEAKER_27
transcript.pyannote[2004].start 11339.35596875
transcript.pyannote[2004].end 11341.27971875
transcript.pyannote[2005].speaker SPEAKER_27
transcript.pyannote[2005].start 11341.78596875
transcript.pyannote[2005].end 11343.91221875
transcript.pyannote[2006].speaker SPEAKER_27
transcript.pyannote[2006].start 11344.46909375
transcript.pyannote[2006].end 11359.85909375
transcript.pyannote[2007].speaker SPEAKER_27
transcript.pyannote[2007].start 11360.36534375
transcript.pyannote[2007].end 11362.59284375
transcript.pyannote[2008].speaker SPEAKER_27
transcript.pyannote[2008].start 11363.23409375
transcript.pyannote[2008].end 11374.30409375
transcript.pyannote[2009].speaker SPEAKER_04
transcript.pyannote[2009].start 11374.30409375
transcript.pyannote[2009].end 11387.19659375
transcript.pyannote[2010].speaker SPEAKER_27
transcript.pyannote[2010].start 11376.81846875
transcript.pyannote[2010].end 11377.83096875
transcript.pyannote[2011].speaker SPEAKER_27
transcript.pyannote[2011].start 11384.61471875
transcript.pyannote[2011].end 11385.00284375
transcript.pyannote[2012].speaker SPEAKER_27
transcript.pyannote[2012].start 11386.48784375
transcript.pyannote[2012].end 11389.35659375
transcript.pyannote[2013].speaker SPEAKER_27
transcript.pyannote[2013].start 11389.72784375
transcript.pyannote[2013].end 11392.73159375
transcript.pyannote[2014].speaker SPEAKER_04
transcript.pyannote[2014].start 11390.62221875
transcript.pyannote[2014].end 11401.20284375
transcript.pyannote[2015].speaker SPEAKER_11
transcript.pyannote[2015].start 11401.20284375
transcript.pyannote[2015].end 11401.47284375
transcript.pyannote[2016].speaker SPEAKER_04
transcript.pyannote[2016].start 11401.38846875
transcript.pyannote[2016].end 11414.51721875
transcript.pyannote[2017].speaker SPEAKER_27
transcript.pyannote[2017].start 11413.67346875
transcript.pyannote[2017].end 11416.99784375
transcript.pyannote[2018].speaker SPEAKER_04
transcript.pyannote[2018].start 11414.66909375
transcript.pyannote[2018].end 11422.68471875
transcript.pyannote[2019].speaker SPEAKER_04
transcript.pyannote[2019].start 11423.17409375
transcript.pyannote[2019].end 11455.94534375
transcript.pyannote[2020].speaker SPEAKER_04
transcript.pyannote[2020].start 11456.36721875
transcript.pyannote[2020].end 11461.05846875
transcript.pyannote[2021].speaker SPEAKER_04
transcript.pyannote[2021].start 11461.48034375
transcript.pyannote[2021].end 11468.24721875
transcript.pyannote[2022].speaker SPEAKER_04
transcript.pyannote[2022].start 11468.98971875
transcript.pyannote[2022].end 11470.13721875
transcript.pyannote[2023].speaker SPEAKER_04
transcript.pyannote[2023].start 11470.20471875
transcript.pyannote[2023].end 11480.75159375
transcript.pyannote[2024].speaker SPEAKER_04
transcript.pyannote[2024].start 11480.95409375
transcript.pyannote[2024].end 11481.66284375
transcript.pyannote[2025].speaker SPEAKER_04
transcript.pyannote[2025].start 11482.27034375
transcript.pyannote[2025].end 11498.62221875
transcript.pyannote[2026].speaker SPEAKER_00
transcript.pyannote[2026].start 11493.69471875
transcript.pyannote[2026].end 11493.74534375
transcript.pyannote[2027].speaker SPEAKER_28
transcript.pyannote[2027].start 11493.74534375
transcript.pyannote[2027].end 11493.76221875
transcript.pyannote[2028].speaker SPEAKER_00
transcript.pyannote[2028].start 11493.76221875
transcript.pyannote[2028].end 11494.15034375
transcript.pyannote[2029].speaker SPEAKER_00
transcript.pyannote[2029].start 11495.14596875
transcript.pyannote[2029].end 11496.09096875
transcript.pyannote[2030].speaker SPEAKER_04
transcript.pyannote[2030].start 11499.01034375
transcript.pyannote[2030].end 11500.52909375
transcript.pyannote[2031].speaker SPEAKER_04
transcript.pyannote[2031].start 11501.28846875
transcript.pyannote[2031].end 11532.28784375
transcript.pyannote[2032].speaker SPEAKER_04
transcript.pyannote[2032].start 11532.35534375
transcript.pyannote[2032].end 11555.81159375
transcript.pyannote[2033].speaker SPEAKER_00
transcript.pyannote[2033].start 11539.39221875
transcript.pyannote[2033].end 11539.47659375
transcript.pyannote[2034].speaker SPEAKER_03
transcript.pyannote[2034].start 11539.47659375
transcript.pyannote[2034].end 11539.83096875
transcript.pyannote[2035].speaker SPEAKER_00
transcript.pyannote[2035].start 11539.83096875
transcript.pyannote[2035].end 11539.96596875
transcript.pyannote[2036].speaker SPEAKER_28
transcript.pyannote[2036].start 11555.77784375
transcript.pyannote[2036].end 11556.13221875
transcript.pyannote[2037].speaker SPEAKER_04
transcript.pyannote[2037].start 11556.01409375
transcript.pyannote[2037].end 11566.78034375
transcript.pyannote[2038].speaker SPEAKER_04
transcript.pyannote[2038].start 11567.01659375
transcript.pyannote[2038].end 11575.47096875
transcript.pyannote[2039].speaker SPEAKER_00
transcript.pyannote[2039].start 11572.48409375
transcript.pyannote[2039].end 11573.07471875
transcript.pyannote[2040].speaker SPEAKER_00
transcript.pyannote[2040].start 11573.12534375
transcript.pyannote[2040].end 11573.19284375
transcript.pyannote[2041].speaker SPEAKER_04
transcript.pyannote[2041].start 11576.11221875
transcript.pyannote[2041].end 11584.58346875
transcript.pyannote[2042].speaker SPEAKER_04
transcript.pyannote[2042].start 11585.22471875
transcript.pyannote[2042].end 11588.09346875
transcript.pyannote[2043].speaker SPEAKER_04
transcript.pyannote[2043].start 11588.11034375
transcript.pyannote[2043].end 11592.04221875
transcript.pyannote[2044].speaker SPEAKER_04
transcript.pyannote[2044].start 11592.27846875
transcript.pyannote[2044].end 11597.74596875
transcript.pyannote[2045].speaker SPEAKER_04
transcript.pyannote[2045].start 11598.79221875
transcript.pyannote[2045].end 11613.89534375
transcript.pyannote[2046].speaker SPEAKER_27
transcript.pyannote[2046].start 11612.39346875
transcript.pyannote[2046].end 11613.27096875
transcript.pyannote[2047].speaker SPEAKER_27
transcript.pyannote[2047].start 11613.40596875
transcript.pyannote[2047].end 11613.94596875
transcript.pyannote[2048].speaker SPEAKER_04
transcript.pyannote[2048].start 11613.94596875
transcript.pyannote[2048].end 11613.96284375
transcript.pyannote[2049].speaker SPEAKER_27
transcript.pyannote[2049].start 11613.96284375
transcript.pyannote[2049].end 11614.23284375
transcript.pyannote[2050].speaker SPEAKER_04
transcript.pyannote[2050].start 11614.23284375
transcript.pyannote[2050].end 11614.26659375
transcript.pyannote[2051].speaker SPEAKER_04
transcript.pyannote[2051].start 11617.37159375
transcript.pyannote[2051].end 11617.38846875
transcript.pyannote[2052].speaker SPEAKER_03
transcript.pyannote[2052].start 11617.38846875
transcript.pyannote[2052].end 11621.72534375
transcript.pyannote[2053].speaker SPEAKER_03
transcript.pyannote[2053].start 11630.78721875
transcript.pyannote[2053].end 11633.63909375
transcript.pyannote[2054].speaker SPEAKER_09
transcript.pyannote[2054].start 11637.48659375
transcript.pyannote[2054].end 11643.34221875
transcript.pyannote[2055].speaker SPEAKER_09
transcript.pyannote[2055].start 11644.43909375
transcript.pyannote[2055].end 11650.59846875
transcript.pyannote[2056].speaker SPEAKER_09
transcript.pyannote[2056].start 11650.98659375
transcript.pyannote[2056].end 11704.46346875
transcript.pyannote[2057].speaker SPEAKER_09
transcript.pyannote[2057].start 11704.83471875
transcript.pyannote[2057].end 11755.94909375
transcript.pyannote[2058].speaker SPEAKER_09
transcript.pyannote[2058].start 11756.45534375
transcript.pyannote[2058].end 11806.32096875
transcript.pyannote[2059].speaker SPEAKER_09
transcript.pyannote[2059].start 11808.93659375
transcript.pyannote[2059].end 11810.59034375
transcript.pyannote[2060].speaker SPEAKER_09
transcript.pyannote[2060].start 11810.65784375
transcript.pyannote[2060].end 11811.72096875
transcript.pyannote[2061].speaker SPEAKER_09
transcript.pyannote[2061].start 11812.05846875
transcript.pyannote[2061].end 11812.86846875
transcript.pyannote[2062].speaker SPEAKER_27
transcript.pyannote[2062].start 11813.13846875
transcript.pyannote[2062].end 11815.18034375
transcript.pyannote[2063].speaker SPEAKER_09
transcript.pyannote[2063].start 11814.60659375
transcript.pyannote[2063].end 11815.85534375
transcript.pyannote[2064].speaker SPEAKER_27
transcript.pyannote[2064].start 11815.39971875
transcript.pyannote[2064].end 11815.46721875
transcript.pyannote[2065].speaker SPEAKER_27
transcript.pyannote[2065].start 11815.85534375
transcript.pyannote[2065].end 11816.05784375
transcript.pyannote[2066].speaker SPEAKER_09
transcript.pyannote[2066].start 11815.99034375
transcript.pyannote[2066].end 11816.02409375
transcript.pyannote[2067].speaker SPEAKER_09
transcript.pyannote[2067].start 11816.05784375
transcript.pyannote[2067].end 11817.91409375
transcript.pyannote[2068].speaker SPEAKER_27
transcript.pyannote[2068].start 11816.22659375
transcript.pyannote[2068].end 11816.24346875
transcript.pyannote[2069].speaker SPEAKER_27
transcript.pyannote[2069].start 11817.91409375
transcript.pyannote[2069].end 11817.93096875
transcript.pyannote[2070].speaker SPEAKER_27
transcript.pyannote[2070].start 11818.82534375
transcript.pyannote[2070].end 11820.42846875
transcript.pyannote[2071].speaker SPEAKER_09
transcript.pyannote[2071].start 11821.18784375
transcript.pyannote[2071].end 11823.51659375
transcript.pyannote[2072].speaker SPEAKER_27
transcript.pyannote[2072].start 11824.15784375
transcript.pyannote[2072].end 11825.71034375
transcript.pyannote[2073].speaker SPEAKER_09
transcript.pyannote[2073].start 11824.32659375
transcript.pyannote[2073].end 11825.10284375
transcript.pyannote[2074].speaker SPEAKER_09
transcript.pyannote[2074].start 11825.38971875
transcript.pyannote[2074].end 11826.63846875
transcript.pyannote[2075].speaker SPEAKER_27
transcript.pyannote[2075].start 11826.31784375
transcript.pyannote[2075].end 11827.75221875
transcript.pyannote[2076].speaker SPEAKER_27
transcript.pyannote[2076].start 11827.90409375
transcript.pyannote[2076].end 11831.78534375
transcript.pyannote[2077].speaker SPEAKER_27
transcript.pyannote[2077].start 11832.13971875
transcript.pyannote[2077].end 11837.13471875
transcript.pyannote[2078].speaker SPEAKER_09
transcript.pyannote[2078].start 11835.66659375
transcript.pyannote[2078].end 11841.96096875
transcript.pyannote[2079].speaker SPEAKER_09
transcript.pyannote[2079].start 11842.06221875
transcript.pyannote[2079].end 11842.56846875
transcript.pyannote[2080].speaker SPEAKER_09
transcript.pyannote[2080].start 11842.88909375
transcript.pyannote[2080].end 11850.12846875
transcript.pyannote[2081].speaker SPEAKER_27
transcript.pyannote[2081].start 11850.12846875
transcript.pyannote[2081].end 11852.49096875
transcript.pyannote[2082].speaker SPEAKER_09
transcript.pyannote[2082].start 11852.49096875
transcript.pyannote[2082].end 11852.54159375
transcript.pyannote[2083].speaker SPEAKER_27
transcript.pyannote[2083].start 11852.54159375
transcript.pyannote[2083].end 11853.60471875
transcript.pyannote[2084].speaker SPEAKER_09
transcript.pyannote[2084].start 11852.57534375
transcript.pyannote[2084].end 11933.87909375
transcript.pyannote[2085].speaker SPEAKER_27
transcript.pyannote[2085].start 11855.08971875
transcript.pyannote[2085].end 11855.71409375
transcript.pyannote[2086].speaker SPEAKER_27
transcript.pyannote[2086].start 11855.95034375
transcript.pyannote[2086].end 11856.28784375
transcript.pyannote[2087].speaker SPEAKER_09
transcript.pyannote[2087].start 11933.94659375
transcript.pyannote[2087].end 11989.97159375
transcript.pyannote[2088].speaker SPEAKER_27
transcript.pyannote[2088].start 11989.97159375
transcript.pyannote[2088].end 11990.73096875
transcript.pyannote[2089].speaker SPEAKER_27
transcript.pyannote[2089].start 11990.78159375
transcript.pyannote[2089].end 12004.39971875
transcript.pyannote[2090].speaker SPEAKER_27
transcript.pyannote[2090].start 12004.92284375
transcript.pyannote[2090].end 12006.82971875
transcript.pyannote[2091].speaker SPEAKER_27
transcript.pyannote[2091].start 12006.86346875
transcript.pyannote[2091].end 12009.78284375
transcript.pyannote[2092].speaker SPEAKER_26
transcript.pyannote[2092].start 12007.03221875
transcript.pyannote[2092].end 12008.06159375
transcript.pyannote[2093].speaker SPEAKER_27
transcript.pyannote[2093].start 12010.05284375
transcript.pyannote[2093].end 12015.43596875
transcript.pyannote[2094].speaker SPEAKER_27
transcript.pyannote[2094].start 12015.68909375
transcript.pyannote[2094].end 12016.27971875
transcript.pyannote[2095].speaker SPEAKER_09
transcript.pyannote[2095].start 12016.27971875
transcript.pyannote[2095].end 12016.33034375
transcript.pyannote[2096].speaker SPEAKER_27
transcript.pyannote[2096].start 12016.97159375
transcript.pyannote[2096].end 12016.98846875
transcript.pyannote[2097].speaker SPEAKER_09
transcript.pyannote[2097].start 12016.98846875
transcript.pyannote[2097].end 12017.62971875
transcript.pyannote[2098].speaker SPEAKER_27
transcript.pyannote[2098].start 12017.62971875
transcript.pyannote[2098].end 12017.76471875
transcript.pyannote[2099].speaker SPEAKER_09
transcript.pyannote[2099].start 12017.76471875
transcript.pyannote[2099].end 12020.93721875
transcript.pyannote[2100].speaker SPEAKER_09
transcript.pyannote[2100].start 12021.86534375
transcript.pyannote[2100].end 12026.60721875
transcript.pyannote[2101].speaker SPEAKER_09
transcript.pyannote[2101].start 12027.06284375
transcript.pyannote[2101].end 12030.35346875
transcript.pyannote[2102].speaker SPEAKER_09
transcript.pyannote[2102].start 12030.80909375
transcript.pyannote[2102].end 12032.96909375
transcript.pyannote[2103].speaker SPEAKER_02
transcript.pyannote[2103].start 12032.81721875
transcript.pyannote[2103].end 12033.00284375
transcript.pyannote[2104].speaker SPEAKER_09
transcript.pyannote[2104].start 12033.00284375
transcript.pyannote[2104].end 12042.33471875
transcript.pyannote[2105].speaker SPEAKER_09
transcript.pyannote[2105].start 12043.56659375
transcript.pyannote[2105].end 12071.71409375
transcript.pyannote[2106].speaker SPEAKER_09
transcript.pyannote[2106].start 12072.16971875
transcript.pyannote[2106].end 12072.96284375
transcript.pyannote[2107].speaker SPEAKER_27
transcript.pyannote[2107].start 12072.96284375
transcript.pyannote[2107].end 12072.99659375
transcript.pyannote[2108].speaker SPEAKER_09
transcript.pyannote[2108].start 12073.41846875
transcript.pyannote[2108].end 12073.43534375
transcript.pyannote[2109].speaker SPEAKER_27
transcript.pyannote[2109].start 12073.43534375
transcript.pyannote[2109].end 12081.97409375
transcript.pyannote[2110].speaker SPEAKER_27
transcript.pyannote[2110].start 12083.77971875
transcript.pyannote[2110].end 12091.59284375
transcript.pyannote[2111].speaker SPEAKER_09
transcript.pyannote[2111].start 12089.78721875
transcript.pyannote[2111].end 12093.58409375
transcript.pyannote[2112].speaker SPEAKER_09
transcript.pyannote[2112].start 12093.76971875
transcript.pyannote[2112].end 12114.13784375
transcript.pyannote[2113].speaker SPEAKER_09
transcript.pyannote[2113].start 12114.89721875
transcript.pyannote[2113].end 12135.53534375
transcript.pyannote[2114].speaker SPEAKER_09
transcript.pyannote[2114].start 12136.07534375
transcript.pyannote[2114].end 12136.09221875
transcript.pyannote[2115].speaker SPEAKER_27
transcript.pyannote[2115].start 12136.09221875
transcript.pyannote[2115].end 12136.32846875
transcript.pyannote[2116].speaker SPEAKER_27
transcript.pyannote[2116].start 12137.32409375
transcript.pyannote[2116].end 12137.67846875
transcript.pyannote[2117].speaker SPEAKER_27
transcript.pyannote[2117].start 12138.23534375
transcript.pyannote[2117].end 12138.55596875
transcript.pyannote[2118].speaker SPEAKER_27
transcript.pyannote[2118].start 12139.06221875
transcript.pyannote[2118].end 12144.04034375
transcript.pyannote[2119].speaker SPEAKER_09
transcript.pyannote[2119].start 12143.02784375
transcript.pyannote[2119].end 12157.00034375
transcript.pyannote[2120].speaker SPEAKER_27
transcript.pyannote[2120].start 12146.50409375
transcript.pyannote[2120].end 12147.71909375
transcript.pyannote[2121].speaker SPEAKER_02
transcript.pyannote[2121].start 12151.02659375
transcript.pyannote[2121].end 12151.53284375
transcript.pyannote[2122].speaker SPEAKER_03
transcript.pyannote[2122].start 12158.53596875
transcript.pyannote[2122].end 12162.77159375
transcript.pyannote[2123].speaker SPEAKER_09
transcript.pyannote[2123].start 12158.67096875
transcript.pyannote[2123].end 12158.68784375
transcript.pyannote[2124].speaker SPEAKER_27
transcript.pyannote[2124].start 12159.63284375
transcript.pyannote[2124].end 12159.76784375
transcript.pyannote[2125].speaker SPEAKER_09
transcript.pyannote[2125].start 12159.76784375
transcript.pyannote[2125].end 12159.95346875
transcript.pyannote[2126].speaker SPEAKER_09
transcript.pyannote[2126].start 12160.35846875
transcript.pyannote[2126].end 12162.16409375
transcript.pyannote[2127].speaker SPEAKER_27
transcript.pyannote[2127].start 12162.16409375
transcript.pyannote[2127].end 12162.18096875
transcript.pyannote[2128].speaker SPEAKER_27
transcript.pyannote[2128].start 12162.77159375
transcript.pyannote[2128].end 12162.95721875
transcript.pyannote[2129].speaker SPEAKER_03
transcript.pyannote[2129].start 12162.95721875
transcript.pyannote[2129].end 12162.97409375
transcript.pyannote[2130].speaker SPEAKER_27
transcript.pyannote[2130].start 12162.97409375
transcript.pyannote[2130].end 12163.83471875
transcript.pyannote[2131].speaker SPEAKER_03
transcript.pyannote[2131].start 12163.61534375
transcript.pyannote[2131].end 12166.43346875
transcript.pyannote[2132].speaker SPEAKER_09
transcript.pyannote[2132].start 12163.83471875
transcript.pyannote[2132].end 12163.86846875
transcript.pyannote[2133].speaker SPEAKER_03
transcript.pyannote[2133].start 12167.10846875
transcript.pyannote[2133].end 12170.82096875
transcript.pyannote[2134].speaker SPEAKER_09
transcript.pyannote[2134].start 12177.33471875
transcript.pyannote[2134].end 12179.35971875
transcript.pyannote[2135].speaker SPEAKER_03
transcript.pyannote[2135].start 12180.11909375
transcript.pyannote[2135].end 12181.06409375
transcript.pyannote[2136].speaker SPEAKER_09
transcript.pyannote[2136].start 12183.22409375
transcript.pyannote[2136].end 12230.27159375
transcript.pyannote[2137].speaker SPEAKER_03
transcript.pyannote[2137].start 12184.38846875
transcript.pyannote[2137].end 12185.24909375
transcript.pyannote[2138].speaker SPEAKER_03
transcript.pyannote[2138].start 12185.62034375
transcript.pyannote[2138].end 12185.95784375
transcript.pyannote[2139].speaker SPEAKER_09
transcript.pyannote[2139].start 12230.69346875
transcript.pyannote[2139].end 12230.71034375
transcript.pyannote[2140].speaker SPEAKER_27
transcript.pyannote[2140].start 12230.71034375
transcript.pyannote[2140].end 12230.91284375
transcript.pyannote[2141].speaker SPEAKER_09
transcript.pyannote[2141].start 12230.91284375
transcript.pyannote[2141].end 12231.28409375
transcript.pyannote[2142].speaker SPEAKER_27
transcript.pyannote[2142].start 12231.28409375
transcript.pyannote[2142].end 12231.36846875
transcript.pyannote[2143].speaker SPEAKER_09
transcript.pyannote[2143].start 12231.36846875
transcript.pyannote[2143].end 12232.16159375
transcript.pyannote[2144].speaker SPEAKER_27
transcript.pyannote[2144].start 12232.16159375
transcript.pyannote[2144].end 12232.19534375
transcript.pyannote[2145].speaker SPEAKER_09
transcript.pyannote[2145].start 12232.19534375
transcript.pyannote[2145].end 12232.27971875
transcript.pyannote[2146].speaker SPEAKER_27
transcript.pyannote[2146].start 12232.27971875
transcript.pyannote[2146].end 12239.08034375
transcript.pyannote[2147].speaker SPEAKER_27
transcript.pyannote[2147].start 12239.45159375
transcript.pyannote[2147].end 12247.88909375
transcript.pyannote[2148].speaker SPEAKER_09
transcript.pyannote[2148].start 12247.77096875
transcript.pyannote[2148].end 12300.84284375
transcript.pyannote[2149].speaker SPEAKER_11
transcript.pyannote[2149].start 12262.67159375
transcript.pyannote[2149].end 12262.78971875
transcript.pyannote[2150].speaker SPEAKER_09
transcript.pyannote[2150].start 12301.06221875
transcript.pyannote[2150].end 12312.55409375
transcript.pyannote[2151].speaker SPEAKER_09
transcript.pyannote[2151].start 12312.95909375
transcript.pyannote[2151].end 12319.67534375
transcript.pyannote[2152].speaker SPEAKER_02
transcript.pyannote[2152].start 12318.40971875
transcript.pyannote[2152].end 12318.42659375
transcript.pyannote[2153].speaker SPEAKER_02
transcript.pyannote[2153].start 12319.67534375
transcript.pyannote[2153].end 12320.02971875
transcript.pyannote[2154].speaker SPEAKER_09
transcript.pyannote[2154].start 12320.24909375
transcript.pyannote[2154].end 12323.97846875
transcript.pyannote[2155].speaker SPEAKER_27
transcript.pyannote[2155].start 12323.97846875
transcript.pyannote[2155].end 12330.30659375
transcript.pyannote[2156].speaker SPEAKER_27
transcript.pyannote[2156].start 12330.77909375
transcript.pyannote[2156].end 12342.10221875
transcript.pyannote[2157].speaker SPEAKER_09
transcript.pyannote[2157].start 12340.78596875
transcript.pyannote[2157].end 12341.25846875
transcript.pyannote[2158].speaker SPEAKER_09
transcript.pyannote[2158].start 12341.74784375
transcript.pyannote[2158].end 12342.13596875
transcript.pyannote[2159].speaker SPEAKER_27
transcript.pyannote[2159].start 12342.13596875
transcript.pyannote[2159].end 12342.16971875
transcript.pyannote[2160].speaker SPEAKER_02
transcript.pyannote[2160].start 12342.16971875
transcript.pyannote[2160].end 12342.28784375
transcript.pyannote[2161].speaker SPEAKER_09
transcript.pyannote[2161].start 12342.28784375
transcript.pyannote[2161].end 12350.52284375
transcript.pyannote[2162].speaker SPEAKER_09
transcript.pyannote[2162].start 12351.06284375
transcript.pyannote[2162].end 12353.34096875
transcript.pyannote[2163].speaker SPEAKER_09
transcript.pyannote[2163].start 12353.98221875
transcript.pyannote[2163].end 12355.61909375
transcript.pyannote[2164].speaker SPEAKER_02
transcript.pyannote[2164].start 12355.75409375
transcript.pyannote[2164].end 12356.04096875
transcript.pyannote[2165].speaker SPEAKER_09
transcript.pyannote[2165].start 12356.10846875
transcript.pyannote[2165].end 12357.98159375
transcript.pyannote[2166].speaker SPEAKER_09
transcript.pyannote[2166].start 12358.40346875
transcript.pyannote[2166].end 12362.35221875
transcript.pyannote[2167].speaker SPEAKER_27
transcript.pyannote[2167].start 12362.43659375
transcript.pyannote[2167].end 12362.53784375
transcript.pyannote[2168].speaker SPEAKER_27
transcript.pyannote[2168].start 12363.06096875
transcript.pyannote[2168].end 12364.93409375
transcript.pyannote[2169].speaker SPEAKER_27
transcript.pyannote[2169].start 12365.32221875
transcript.pyannote[2169].end 12369.47346875
transcript.pyannote[2170].speaker SPEAKER_27
transcript.pyannote[2170].start 12369.60846875
transcript.pyannote[2170].end 12376.96596875
transcript.pyannote[2171].speaker SPEAKER_09
transcript.pyannote[2171].start 12373.96221875
transcript.pyannote[2171].end 12374.02971875
transcript.pyannote[2172].speaker SPEAKER_09
transcript.pyannote[2172].start 12376.96596875
transcript.pyannote[2172].end 12377.10096875
transcript.pyannote[2173].speaker SPEAKER_27
transcript.pyannote[2173].start 12377.10096875
transcript.pyannote[2173].end 12382.16346875
transcript.pyannote[2174].speaker SPEAKER_09
transcript.pyannote[2174].start 12377.15159375
transcript.pyannote[2174].end 12378.38346875
transcript.pyannote[2175].speaker SPEAKER_09
transcript.pyannote[2175].start 12378.83909375
transcript.pyannote[2175].end 12380.02034375
transcript.pyannote[2176].speaker SPEAKER_27
transcript.pyannote[2176].start 12382.31534375
transcript.pyannote[2176].end 12384.47534375
transcript.pyannote[2177].speaker SPEAKER_27
transcript.pyannote[2177].start 12384.91409375
transcript.pyannote[2177].end 12394.04346875
transcript.pyannote[2178].speaker SPEAKER_09
transcript.pyannote[2178].start 12393.67221875
transcript.pyannote[2178].end 12393.99284375
transcript.pyannote[2179].speaker SPEAKER_09
transcript.pyannote[2179].start 12394.04346875
transcript.pyannote[2179].end 12394.27971875
transcript.pyannote[2180].speaker SPEAKER_27
transcript.pyannote[2180].start 12394.27971875
transcript.pyannote[2180].end 12395.73096875
transcript.pyannote[2181].speaker SPEAKER_09
transcript.pyannote[2181].start 12395.73096875
transcript.pyannote[2181].end 12409.39971875
transcript.pyannote[2182].speaker SPEAKER_27
transcript.pyannote[2182].start 12398.32971875
transcript.pyannote[2182].end 12398.38034375
transcript.pyannote[2183].speaker SPEAKER_06
transcript.pyannote[2183].start 12398.38034375
transcript.pyannote[2183].end 12400.08471875
transcript.pyannote[2184].speaker SPEAKER_00
transcript.pyannote[2184].start 12402.75096875
transcript.pyannote[2184].end 12403.20659375
transcript.pyannote[2185].speaker SPEAKER_28
transcript.pyannote[2185].start 12403.20659375
transcript.pyannote[2185].end 12403.27409375
transcript.pyannote[2186].speaker SPEAKER_27
transcript.pyannote[2186].start 12403.27409375
transcript.pyannote[2186].end 12403.64534375
transcript.pyannote[2187].speaker SPEAKER_00
transcript.pyannote[2187].start 12403.64534375
transcript.pyannote[2187].end 12403.74659375
transcript.pyannote[2188].speaker SPEAKER_00
transcript.pyannote[2188].start 12404.35409375
transcript.pyannote[2188].end 12404.69159375
transcript.pyannote[2189].speaker SPEAKER_27
transcript.pyannote[2189].start 12409.39971875
transcript.pyannote[2189].end 12409.56846875
transcript.pyannote[2190].speaker SPEAKER_09
transcript.pyannote[2190].start 12409.56846875
transcript.pyannote[2190].end 12409.58534375
transcript.pyannote[2191].speaker SPEAKER_27
transcript.pyannote[2191].start 12409.58534375
transcript.pyannote[2191].end 12419.27159375
transcript.pyannote[2192].speaker SPEAKER_27
transcript.pyannote[2192].start 12419.59221875
transcript.pyannote[2192].end 12422.17409375
transcript.pyannote[2193].speaker SPEAKER_27
transcript.pyannote[2193].start 12422.39346875
transcript.pyannote[2193].end 12428.28284375
transcript.pyannote[2194].speaker SPEAKER_27
transcript.pyannote[2194].start 12428.67096875
transcript.pyannote[2194].end 12428.97471875
transcript.pyannote[2195].speaker SPEAKER_09
transcript.pyannote[2195].start 12428.97471875
transcript.pyannote[2195].end 12437.27721875
transcript.pyannote[2196].speaker SPEAKER_09
transcript.pyannote[2196].start 12437.68221875
transcript.pyannote[2196].end 12438.35721875
transcript.pyannote[2197].speaker SPEAKER_09
transcript.pyannote[2197].start 12438.57659375
transcript.pyannote[2197].end 12441.69846875
transcript.pyannote[2198].speaker SPEAKER_09
transcript.pyannote[2198].start 12441.81659375
transcript.pyannote[2198].end 12441.83346875
transcript.pyannote[2199].speaker SPEAKER_09
transcript.pyannote[2199].start 12441.93471875
transcript.pyannote[2199].end 12441.95159375
transcript.pyannote[2200].speaker SPEAKER_09
transcript.pyannote[2200].start 12441.96846875
transcript.pyannote[2200].end 12451.75596875
transcript.pyannote[2201].speaker SPEAKER_09
transcript.pyannote[2201].start 12452.16096875
transcript.pyannote[2201].end 12462.06659375
transcript.pyannote[2202].speaker SPEAKER_05
transcript.pyannote[2202].start 12460.93596875
transcript.pyannote[2202].end 12460.95284375
transcript.pyannote[2203].speaker SPEAKER_27
transcript.pyannote[2203].start 12460.95284375
transcript.pyannote[2203].end 12464.95221875
transcript.pyannote[2204].speaker SPEAKER_09
transcript.pyannote[2204].start 12463.18034375
transcript.pyannote[2204].end 12475.12784375
transcript.pyannote[2205].speaker SPEAKER_27
transcript.pyannote[2205].start 12468.68159375
transcript.pyannote[2205].end 12468.79971875
transcript.pyannote[2206].speaker SPEAKER_27
transcript.pyannote[2206].start 12473.74409375
transcript.pyannote[2206].end 12474.25034375
transcript.pyannote[2207].speaker SPEAKER_27
transcript.pyannote[2207].start 12474.52034375
transcript.pyannote[2207].end 12485.87721875
transcript.pyannote[2208].speaker SPEAKER_27
transcript.pyannote[2208].start 12486.34971875
transcript.pyannote[2208].end 12492.96471875
transcript.pyannote[2209].speaker SPEAKER_09
transcript.pyannote[2209].start 12492.96471875
transcript.pyannote[2209].end 12515.08784375
transcript.pyannote[2210].speaker SPEAKER_04
transcript.pyannote[2210].start 12497.20034375
transcript.pyannote[2210].end 12497.48721875
transcript.pyannote[2211].speaker SPEAKER_09
transcript.pyannote[2211].start 12515.76284375
transcript.pyannote[2211].end 12524.72346875
transcript.pyannote[2212].speaker SPEAKER_09
transcript.pyannote[2212].start 12525.21284375
transcript.pyannote[2212].end 12530.35971875
transcript.pyannote[2213].speaker SPEAKER_27
transcript.pyannote[2213].start 12528.09846875
transcript.pyannote[2213].end 12528.13221875
transcript.pyannote[2214].speaker SPEAKER_27
transcript.pyannote[2214].start 12530.74784375
transcript.pyannote[2214].end 12533.17784375
transcript.pyannote[2215].speaker SPEAKER_09
transcript.pyannote[2215].start 12533.17784375
transcript.pyannote[2215].end 12553.71471875
transcript.pyannote[2216].speaker SPEAKER_27
transcript.pyannote[2216].start 12553.98471875
transcript.pyannote[2216].end 12554.28846875
transcript.pyannote[2217].speaker SPEAKER_09
transcript.pyannote[2217].start 12554.44034375
transcript.pyannote[2217].end 12557.73096875
transcript.pyannote[2218].speaker SPEAKER_03
transcript.pyannote[2218].start 12561.08909375
transcript.pyannote[2218].end 12567.95721875
transcript.pyannote[2219].speaker SPEAKER_07
transcript.pyannote[2219].start 12568.36221875
transcript.pyannote[2219].end 12616.40534375
transcript.pyannote[2220].speaker SPEAKER_07
transcript.pyannote[2220].start 12616.54034375
transcript.pyannote[2220].end 12643.42221875
transcript.pyannote[2221].speaker SPEAKER_07
transcript.pyannote[2221].start 12643.74284375
transcript.pyannote[2221].end 12644.56971875
transcript.pyannote[2222].speaker SPEAKER_07
transcript.pyannote[2222].start 12645.32909375
transcript.pyannote[2222].end 12692.81534375
transcript.pyannote[2223].speaker SPEAKER_03
transcript.pyannote[2223].start 12695.02596875
transcript.pyannote[2223].end 12698.67096875
transcript.pyannote[2224].speaker SPEAKER_17
transcript.pyannote[2224].start 12698.67096875
transcript.pyannote[2224].end 12699.75096875
transcript.pyannote[2225].speaker SPEAKER_03
transcript.pyannote[2225].start 12699.90284375
transcript.pyannote[2225].end 12700.62846875
transcript.pyannote[2226].speaker SPEAKER_03
transcript.pyannote[2226].start 12700.86471875
transcript.pyannote[2226].end 12702.45096875
transcript.pyannote[2227].speaker SPEAKER_03
transcript.pyannote[2227].start 12702.63659375
transcript.pyannote[2227].end 12705.28596875
transcript.pyannote[2228].speaker SPEAKER_03
transcript.pyannote[2228].start 12707.00721875
transcript.pyannote[2228].end 12709.96034375
transcript.pyannote[2229].speaker SPEAKER_17
transcript.pyannote[2229].start 12709.90971875
transcript.pyannote[2229].end 12732.82596875
transcript.pyannote[2230].speaker SPEAKER_17
transcript.pyannote[2230].start 12732.85971875
transcript.pyannote[2230].end 12734.59784375
transcript.pyannote[2231].speaker SPEAKER_03
transcript.pyannote[2231].start 12735.27284375
transcript.pyannote[2231].end 12737.97284375
transcript.pyannote[2232].speaker SPEAKER_03
transcript.pyannote[2232].start 12739.18784375
transcript.pyannote[2232].end 12739.49159375
transcript.pyannote[2233].speaker SPEAKER_03
transcript.pyannote[2233].start 12740.08221875
transcript.pyannote[2233].end 12740.53784375
transcript.pyannote[2234].speaker SPEAKER_03
transcript.pyannote[2234].start 12740.67284375
transcript.pyannote[2234].end 12741.24659375
transcript.pyannote[2235].speaker SPEAKER_03
transcript.pyannote[2235].start 12741.56721875
transcript.pyannote[2235].end 12743.47409375
transcript.pyannote[2236].speaker SPEAKER_03
transcript.pyannote[2236].start 12744.16596875
transcript.pyannote[2236].end 12746.39346875
transcript.pyannote[2237].speaker SPEAKER_23
transcript.pyannote[2237].start 12748.35096875
transcript.pyannote[2237].end 12756.97409375
transcript.pyannote[2238].speaker SPEAKER_02
transcript.pyannote[2238].start 12754.79721875
transcript.pyannote[2238].end 12754.84784375
transcript.pyannote[2239].speaker SPEAKER_03
transcript.pyannote[2239].start 12754.84784375
transcript.pyannote[2239].end 12755.03346875
transcript.pyannote[2240].speaker SPEAKER_02
transcript.pyannote[2240].start 12755.03346875
transcript.pyannote[2240].end 12755.11784375
transcript.pyannote[2241].speaker SPEAKER_02
transcript.pyannote[2241].start 12756.97409375
transcript.pyannote[2241].end 12757.09221875
transcript.pyannote[2242].speaker SPEAKER_23
transcript.pyannote[2242].start 12757.09221875
transcript.pyannote[2242].end 12757.34534375
transcript.pyannote[2243].speaker SPEAKER_02
transcript.pyannote[2243].start 12757.34534375
transcript.pyannote[2243].end 12757.53096875
transcript.pyannote[2244].speaker SPEAKER_23
transcript.pyannote[2244].start 12757.53096875
transcript.pyannote[2244].end 12758.45909375
transcript.pyannote[2245].speaker SPEAKER_02
transcript.pyannote[2245].start 12758.45909375
transcript.pyannote[2245].end 12759.84284375
transcript.pyannote[2246].speaker SPEAKER_03
transcript.pyannote[2246].start 12760.07909375
transcript.pyannote[2246].end 12765.58034375
transcript.pyannote[2247].speaker SPEAKER_02
transcript.pyannote[2247].start 12765.96846875
transcript.pyannote[2247].end 12766.18784375
transcript.pyannote[2248].speaker SPEAKER_02
transcript.pyannote[2248].start 12767.47034375
transcript.pyannote[2248].end 12768.02721875
transcript.pyannote[2249].speaker SPEAKER_02
transcript.pyannote[2249].start 12768.44909375
transcript.pyannote[2249].end 12769.05659375
transcript.pyannote[2250].speaker SPEAKER_03
transcript.pyannote[2250].start 12769.05659375
transcript.pyannote[2250].end 12769.90034375
transcript.pyannote[2251].speaker SPEAKER_02
transcript.pyannote[2251].start 12769.09034375
transcript.pyannote[2251].end 12769.61346875
transcript.pyannote[2252].speaker SPEAKER_03
transcript.pyannote[2252].start 12773.61284375
transcript.pyannote[2252].end 12785.40846875
transcript.pyannote[2253].speaker SPEAKER_00
transcript.pyannote[2253].start 12782.23596875
transcript.pyannote[2253].end 12782.25284375
transcript.pyannote[2254].speaker SPEAKER_28
transcript.pyannote[2254].start 12782.25284375
transcript.pyannote[2254].end 12782.28659375
transcript.pyannote[2255].speaker SPEAKER_00
transcript.pyannote[2255].start 12782.28659375
transcript.pyannote[2255].end 12782.38784375
transcript.pyannote[2256].speaker SPEAKER_03
transcript.pyannote[2256].start 12786.35346875
transcript.pyannote[2256].end 12790.69034375
transcript.pyannote[2257].speaker SPEAKER_17
transcript.pyannote[2257].start 12791.31471875
transcript.pyannote[2257].end 12850.29284375
transcript.pyannote[2258].speaker SPEAKER_03
transcript.pyannote[2258].start 12851.00159375
transcript.pyannote[2258].end 12851.28846875
transcript.pyannote[2259].speaker SPEAKER_03
transcript.pyannote[2259].start 12851.96346875
transcript.pyannote[2259].end 12854.88284375
transcript.pyannote[2260].speaker SPEAKER_01
transcript.pyannote[2260].start 12858.57846875
transcript.pyannote[2260].end 12859.97909375
transcript.pyannote[2261].speaker SPEAKER_01
transcript.pyannote[2261].start 12860.85659375
transcript.pyannote[2261].end 12862.29096875
transcript.pyannote[2262].speaker SPEAKER_01
transcript.pyannote[2262].start 12862.79721875
transcript.pyannote[2262].end 12864.46784375
transcript.pyannote[2263].speaker SPEAKER_01
transcript.pyannote[2263].start 12865.21034375
transcript.pyannote[2263].end 12867.64034375
transcript.pyannote[2264].speaker SPEAKER_01
transcript.pyannote[2264].start 12868.45034375
transcript.pyannote[2264].end 12874.37346875
transcript.pyannote[2265].speaker SPEAKER_01
transcript.pyannote[2265].start 12874.69409375
transcript.pyannote[2265].end 12878.64284375
transcript.pyannote[2266].speaker SPEAKER_01
transcript.pyannote[2266].start 12879.11534375
transcript.pyannote[2266].end 12882.52409375
transcript.pyannote[2267].speaker SPEAKER_01
transcript.pyannote[2267].start 12883.41846875
transcript.pyannote[2267].end 12886.43909375
transcript.pyannote[2268].speaker SPEAKER_01
transcript.pyannote[2268].start 12886.86096875
transcript.pyannote[2268].end 12889.24034375
transcript.pyannote[2269].speaker SPEAKER_01
transcript.pyannote[2269].start 12890.03346875
transcript.pyannote[2269].end 12895.85534375
transcript.pyannote[2270].speaker SPEAKER_01
transcript.pyannote[2270].start 12896.14221875
transcript.pyannote[2270].end 12899.38221875
transcript.pyannote[2271].speaker SPEAKER_03
transcript.pyannote[2271].start 12901.13721875
transcript.pyannote[2271].end 12906.26721875
transcript.pyannote[2272].speaker SPEAKER_06
transcript.pyannote[2272].start 12913.08471875
transcript.pyannote[2272].end 12940.99596875
transcript.pyannote[2273].speaker SPEAKER_06
transcript.pyannote[2273].start 12941.41784375
transcript.pyannote[2273].end 13004.49659375
transcript.pyannote[2274].speaker SPEAKER_06
transcript.pyannote[2274].start 13004.85096875
transcript.pyannote[2274].end 13025.11784375
transcript.pyannote[2275].speaker SPEAKER_06
transcript.pyannote[2275].start 13025.38784375
transcript.pyannote[2275].end 13119.38159375
transcript.pyannote[2276].speaker SPEAKER_06
transcript.pyannote[2276].start 13119.93846875
transcript.pyannote[2276].end 13145.13284375
transcript.pyannote[2277].speaker SPEAKER_06
transcript.pyannote[2277].start 13145.47034375
transcript.pyannote[2277].end 13149.58784375
transcript.pyannote[2278].speaker SPEAKER_06
transcript.pyannote[2278].start 13150.04346875
transcript.pyannote[2278].end 13163.42534375
transcript.pyannote[2279].speaker SPEAKER_06
transcript.pyannote[2279].start 13163.71221875
transcript.pyannote[2279].end 13182.61221875
transcript.pyannote[2280].speaker SPEAKER_06
transcript.pyannote[2280].start 13183.08471875
transcript.pyannote[2280].end 13186.69596875
transcript.pyannote[2281].speaker SPEAKER_06
transcript.pyannote[2281].start 13186.81409375
transcript.pyannote[2281].end 13196.39909375
transcript.pyannote[2282].speaker SPEAKER_06
transcript.pyannote[2282].start 13197.02346875
transcript.pyannote[2282].end 13200.55034375
transcript.pyannote[2283].speaker SPEAKER_06
transcript.pyannote[2283].start 13201.44471875
transcript.pyannote[2283].end 13207.51971875
transcript.pyannote[2284].speaker SPEAKER_06
transcript.pyannote[2284].start 13207.62096875
transcript.pyannote[2284].end 13217.20596875
transcript.pyannote[2285].speaker SPEAKER_06
transcript.pyannote[2285].start 13217.71221875
transcript.pyannote[2285].end 13223.23034375
transcript.pyannote[2286].speaker SPEAKER_06
transcript.pyannote[2286].start 13223.73659375
transcript.pyannote[2286].end 13225.54221875
transcript.pyannote[2287].speaker SPEAKER_06
transcript.pyannote[2287].start 13226.03159375
transcript.pyannote[2287].end 13239.36284375
transcript.pyannote[2288].speaker SPEAKER_06
transcript.pyannote[2288].start 13239.49784375
transcript.pyannote[2288].end 13242.72096875
transcript.pyannote[2289].speaker SPEAKER_06
transcript.pyannote[2289].start 13243.07534375
transcript.pyannote[2289].end 13243.44659375
transcript.pyannote[2290].speaker SPEAKER_06
transcript.pyannote[2290].start 13243.73346875
transcript.pyannote[2290].end 13245.87659375
transcript.pyannote[2291].speaker SPEAKER_06
transcript.pyannote[2291].start 13246.23096875
transcript.pyannote[2291].end 13249.65659375
transcript.pyannote[2292].speaker SPEAKER_06
transcript.pyannote[2292].start 13250.06159375
transcript.pyannote[2292].end 13251.22596875
transcript.pyannote[2293].speaker SPEAKER_06
transcript.pyannote[2293].start 13251.44534375
transcript.pyannote[2293].end 13252.12034375
transcript.pyannote[2294].speaker SPEAKER_06
transcript.pyannote[2294].start 13252.25534375
transcript.pyannote[2294].end 13254.02721875
transcript.pyannote[2295].speaker SPEAKER_06
transcript.pyannote[2295].start 13254.87096875
transcript.pyannote[2295].end 13256.37284375
transcript.pyannote[2296].speaker SPEAKER_06
transcript.pyannote[2296].start 13256.47409375
transcript.pyannote[2296].end 13266.86909375
transcript.pyannote[2297].speaker SPEAKER_06
transcript.pyannote[2297].start 13267.49346875
transcript.pyannote[2297].end 13268.60721875
transcript.pyannote[2298].speaker SPEAKER_06
transcript.pyannote[2298].start 13268.64096875
transcript.pyannote[2298].end 13273.68659375
transcript.pyannote[2299].speaker SPEAKER_06
transcript.pyannote[2299].start 13274.37846875
transcript.pyannote[2299].end 13275.17159375
transcript.pyannote[2300].speaker SPEAKER_06
transcript.pyannote[2300].start 13275.67784375
transcript.pyannote[2300].end 13281.22971875
transcript.pyannote[2301].speaker SPEAKER_06
transcript.pyannote[2301].start 13281.60096875
transcript.pyannote[2301].end 13285.83659375
transcript.pyannote[2302].speaker SPEAKER_06
transcript.pyannote[2302].start 13286.39346875
transcript.pyannote[2302].end 13288.08096875
transcript.pyannote[2303].speaker SPEAKER_06
transcript.pyannote[2303].start 13288.73909375
transcript.pyannote[2303].end 13297.66596875
transcript.pyannote[2304].speaker SPEAKER_06
transcript.pyannote[2304].start 13298.22284375
transcript.pyannote[2304].end 13317.17346875
transcript.pyannote[2305].speaker SPEAKER_06
transcript.pyannote[2305].start 13317.25784375
transcript.pyannote[2305].end 13325.83034375
transcript.pyannote[2306].speaker SPEAKER_06
transcript.pyannote[2306].start 13326.33659375
transcript.pyannote[2306].end 13328.71596875
transcript.pyannote[2307].speaker SPEAKER_06
transcript.pyannote[2307].start 13329.99846875
transcript.pyannote[2307].end 13335.26346875
transcript.pyannote[2308].speaker SPEAKER_02
transcript.pyannote[2308].start 13336.44471875
transcript.pyannote[2308].end 13336.54596875
transcript.pyannote[2309].speaker SPEAKER_03
transcript.pyannote[2309].start 13336.54596875
transcript.pyannote[2309].end 13336.88346875
transcript.pyannote[2310].speaker SPEAKER_06
transcript.pyannote[2310].start 13336.88346875
transcript.pyannote[2310].end 13338.08159375
transcript.pyannote[2311].speaker SPEAKER_03
transcript.pyannote[2311].start 13337.05221875
transcript.pyannote[2311].end 13338.45284375
transcript.pyannote[2312].speaker SPEAKER_03
transcript.pyannote[2312].start 13338.62159375
transcript.pyannote[2312].end 13339.92096875
transcript.pyannote[2313].speaker SPEAKER_03
transcript.pyannote[2313].start 13339.98846875
transcript.pyannote[2313].end 13345.32096875
transcript.pyannote[2314].speaker SPEAKER_03
transcript.pyannote[2314].start 13345.45596875
transcript.pyannote[2314].end 13349.16846875
transcript.pyannote[2315].speaker SPEAKER_17
transcript.pyannote[2315].start 13348.79721875
transcript.pyannote[2315].end 13356.99846875
transcript.pyannote[2316].speaker SPEAKER_03
transcript.pyannote[2316].start 13351.31159375
transcript.pyannote[2316].end 13351.64909375
transcript.pyannote[2317].speaker SPEAKER_03
transcript.pyannote[2317].start 13356.76221875
transcript.pyannote[2317].end 13357.06596875
transcript.pyannote[2318].speaker SPEAKER_17
transcript.pyannote[2318].start 13357.03221875
transcript.pyannote[2318].end 13361.35221875
transcript.pyannote[2319].speaker SPEAKER_03
transcript.pyannote[2319].start 13361.68971875
transcript.pyannote[2319].end 13361.97659375
transcript.pyannote[2320].speaker SPEAKER_03
transcript.pyannote[2320].start 13363.71471875
transcript.pyannote[2320].end 13364.40659375
transcript.pyannote[2321].speaker SPEAKER_03
transcript.pyannote[2321].start 13364.69346875
transcript.pyannote[2321].end 13367.79846875
transcript.pyannote[2322].speaker SPEAKER_03
transcript.pyannote[2322].start 13368.27096875
transcript.pyannote[2322].end 13368.52409375
transcript.pyannote[2323].speaker SPEAKER_03
transcript.pyannote[2323].start 13369.50284375
transcript.pyannote[2323].end 13370.78534375
transcript.pyannote[2324].speaker SPEAKER_03
transcript.pyannote[2324].start 13371.22409375
transcript.pyannote[2324].end 13373.41784375
transcript.pyannote[2325].speaker SPEAKER_24
transcript.pyannote[2325].start 13382.32784375
transcript.pyannote[2325].end 13383.45846875
transcript.pyannote[2326].speaker SPEAKER_03
transcript.pyannote[2326].start 13383.72846875
transcript.pyannote[2326].end 13384.67346875
transcript.pyannote[2327].speaker SPEAKER_03
transcript.pyannote[2327].start 13389.34784375
transcript.pyannote[2327].end 13389.71909375
transcript.pyannote[2328].speaker SPEAKER_27
transcript.pyannote[2328].start 13389.71909375
transcript.pyannote[2328].end 13389.73596875
transcript.pyannote[2329].speaker SPEAKER_03
transcript.pyannote[2329].start 13389.73596875
transcript.pyannote[2329].end 13389.83721875
transcript.pyannote[2330].speaker SPEAKER_27
transcript.pyannote[2330].start 13389.83721875
transcript.pyannote[2330].end 13389.87096875
transcript.pyannote[2331].speaker SPEAKER_24
transcript.pyannote[2331].start 13390.46159375
transcript.pyannote[2331].end 13395.33846875
transcript.pyannote[2332].speaker SPEAKER_24
transcript.pyannote[2332].start 13395.77721875
transcript.pyannote[2332].end 13402.81409375
transcript.pyannote[2333].speaker SPEAKER_02
transcript.pyannote[2333].start 13402.81409375
transcript.pyannote[2333].end 13403.03346875
transcript.pyannote[2334].speaker SPEAKER_24
transcript.pyannote[2334].start 13403.03346875
transcript.pyannote[2334].end 13424.65034375
transcript.pyannote[2335].speaker SPEAKER_24
transcript.pyannote[2335].start 13424.85284375
transcript.pyannote[2335].end 13427.38409375
transcript.pyannote[2336].speaker SPEAKER_27
transcript.pyannote[2336].start 13427.23221875
transcript.pyannote[2336].end 13432.81784375
transcript.pyannote[2337].speaker SPEAKER_24
transcript.pyannote[2337].start 13433.42534375
transcript.pyannote[2337].end 13437.59346875
transcript.pyannote[2338].speaker SPEAKER_27
transcript.pyannote[2338].start 13433.49284375
transcript.pyannote[2338].end 13433.76284375
transcript.pyannote[2339].speaker SPEAKER_27
transcript.pyannote[2339].start 13435.77096875
transcript.pyannote[2339].end 13440.88409375
transcript.pyannote[2340].speaker SPEAKER_27
transcript.pyannote[2340].start 13441.17096875
transcript.pyannote[2340].end 13441.64346875
transcript.pyannote[2341].speaker SPEAKER_27
transcript.pyannote[2341].start 13441.93034375
transcript.pyannote[2341].end 13445.18721875
transcript.pyannote[2342].speaker SPEAKER_24
transcript.pyannote[2342].start 13443.82034375
transcript.pyannote[2342].end 13447.76909375
transcript.pyannote[2343].speaker SPEAKER_27
transcript.pyannote[2343].start 13448.17409375
transcript.pyannote[2343].end 13448.73096875
transcript.pyannote[2344].speaker SPEAKER_24
transcript.pyannote[2344].start 13449.79409375
transcript.pyannote[2344].end 13453.23659375
transcript.pyannote[2345].speaker SPEAKER_27
transcript.pyannote[2345].start 13450.53659375
transcript.pyannote[2345].end 13451.48159375
transcript.pyannote[2346].speaker SPEAKER_27
transcript.pyannote[2346].start 13452.22409375
transcript.pyannote[2346].end 13455.44721875
transcript.pyannote[2347].speaker SPEAKER_24
transcript.pyannote[2347].start 13454.46846875
transcript.pyannote[2347].end 13465.23471875
transcript.pyannote[2348].speaker SPEAKER_27
transcript.pyannote[2348].start 13462.97346875
transcript.pyannote[2348].end 13463.68221875
transcript.pyannote[2349].speaker SPEAKER_00
transcript.pyannote[2349].start 13463.68221875
transcript.pyannote[2349].end 13463.73284375
transcript.pyannote[2350].speaker SPEAKER_24
transcript.pyannote[2350].start 13465.84221875
transcript.pyannote[2350].end 13482.70034375
transcript.pyannote[2351].speaker SPEAKER_27
transcript.pyannote[2351].start 13483.25721875
transcript.pyannote[2351].end 13485.06284375
transcript.pyannote[2352].speaker SPEAKER_27
transcript.pyannote[2352].start 13486.12596875
transcript.pyannote[2352].end 13488.26909375
transcript.pyannote[2353].speaker SPEAKER_27
transcript.pyannote[2353].start 13488.43784375
transcript.pyannote[2353].end 13490.93534375
transcript.pyannote[2354].speaker SPEAKER_24
transcript.pyannote[2354].start 13490.19284375
transcript.pyannote[2354].end 13499.64284375
transcript.pyannote[2355].speaker SPEAKER_24
transcript.pyannote[2355].start 13500.79034375
transcript.pyannote[2355].end 13506.03846875
transcript.pyannote[2356].speaker SPEAKER_27
transcript.pyannote[2356].start 13505.83596875
transcript.pyannote[2356].end 13505.92034375
transcript.pyannote[2357].speaker SPEAKER_27
transcript.pyannote[2357].start 13506.03846875
transcript.pyannote[2357].end 13506.07221875
transcript.pyannote[2358].speaker SPEAKER_27
transcript.pyannote[2358].start 13506.37596875
transcript.pyannote[2358].end 13526.59221875
transcript.pyannote[2359].speaker SPEAKER_24
transcript.pyannote[2359].start 13515.82596875
transcript.pyannote[2359].end 13519.57221875
transcript.pyannote[2360].speaker SPEAKER_24
transcript.pyannote[2360].start 13525.32659375
transcript.pyannote[2360].end 13540.96971875
transcript.pyannote[2361].speaker SPEAKER_27
transcript.pyannote[2361].start 13540.96971875
transcript.pyannote[2361].end 13548.47909375
transcript.pyannote[2362].speaker SPEAKER_24
transcript.pyannote[2362].start 13547.65221875
transcript.pyannote[2362].end 13551.29721875
transcript.pyannote[2363].speaker SPEAKER_24
transcript.pyannote[2363].start 13551.76971875
transcript.pyannote[2363].end 13568.64471875
transcript.pyannote[2364].speaker SPEAKER_27
transcript.pyannote[2364].start 13554.01409375
transcript.pyannote[2364].end 13554.60471875
transcript.pyannote[2365].speaker SPEAKER_24
transcript.pyannote[2365].start 13569.03284375
transcript.pyannote[2365].end 13570.14659375
transcript.pyannote[2366].speaker SPEAKER_27
transcript.pyannote[2366].start 13570.16346875
transcript.pyannote[2366].end 13575.07409375
transcript.pyannote[2367].speaker SPEAKER_27
transcript.pyannote[2367].start 13575.96846875
transcript.pyannote[2367].end 13580.59221875
transcript.pyannote[2368].speaker SPEAKER_24
transcript.pyannote[2368].start 13578.70221875
transcript.pyannote[2368].end 13589.62034375
transcript.pyannote[2369].speaker SPEAKER_27
transcript.pyannote[2369].start 13588.08471875
transcript.pyannote[2369].end 13589.78909375
transcript.pyannote[2370].speaker SPEAKER_27
transcript.pyannote[2370].start 13589.97471875
transcript.pyannote[2370].end 13604.94284375
transcript.pyannote[2371].speaker SPEAKER_24
transcript.pyannote[2371].start 13604.03159375
transcript.pyannote[2371].end 13607.01846875
transcript.pyannote[2372].speaker SPEAKER_27
transcript.pyannote[2372].start 13607.01846875
transcript.pyannote[2372].end 13610.78159375
transcript.pyannote[2373].speaker SPEAKER_24
transcript.pyannote[2373].start 13610.27534375
transcript.pyannote[2373].end 13635.35159375
transcript.pyannote[2374].speaker SPEAKER_24
transcript.pyannote[2374].start 13635.60471875
transcript.pyannote[2374].end 13640.09346875
transcript.pyannote[2375].speaker SPEAKER_27
transcript.pyannote[2375].start 13640.65034375
transcript.pyannote[2375].end 13641.74721875
transcript.pyannote[2376].speaker SPEAKER_24
transcript.pyannote[2376].start 13642.05096875
transcript.pyannote[2376].end 13642.43909375
transcript.pyannote[2377].speaker SPEAKER_27
transcript.pyannote[2377].start 13642.37159375
transcript.pyannote[2377].end 13643.33346875
transcript.pyannote[2378].speaker SPEAKER_24
transcript.pyannote[2378].start 13643.48534375
transcript.pyannote[2378].end 13651.02846875
transcript.pyannote[2379].speaker SPEAKER_24
transcript.pyannote[2379].start 13651.43346875
transcript.pyannote[2379].end 13652.09159375
transcript.pyannote[2380].speaker SPEAKER_24
transcript.pyannote[2380].start 13652.36159375
transcript.pyannote[2380].end 13665.33846875
transcript.pyannote[2381].speaker SPEAKER_24
transcript.pyannote[2381].start 13666.31721875
transcript.pyannote[2381].end 13674.85596875
transcript.pyannote[2382].speaker SPEAKER_00
transcript.pyannote[2382].start 13674.38346875
transcript.pyannote[2382].end 13674.45096875
transcript.pyannote[2383].speaker SPEAKER_28
transcript.pyannote[2383].start 13674.45096875
transcript.pyannote[2383].end 13674.53534375
transcript.pyannote[2384].speaker SPEAKER_00
transcript.pyannote[2384].start 13674.53534375
transcript.pyannote[2384].end 13674.55221875
transcript.pyannote[2385].speaker SPEAKER_24
transcript.pyannote[2385].start 13675.24409375
transcript.pyannote[2385].end 13677.60659375
transcript.pyannote[2386].speaker SPEAKER_24
transcript.pyannote[2386].start 13677.96096875
transcript.pyannote[2386].end 13685.68971875
transcript.pyannote[2387].speaker SPEAKER_02
transcript.pyannote[2387].start 13685.63909375
transcript.pyannote[2387].end 13686.07784375
transcript.pyannote[2388].speaker SPEAKER_24
transcript.pyannote[2388].start 13685.87534375
transcript.pyannote[2388].end 13705.90596875
transcript.pyannote[2389].speaker SPEAKER_03
transcript.pyannote[2389].start 13705.46721875
transcript.pyannote[2389].end 13710.95159375
transcript.pyannote[2390].speaker SPEAKER_20
transcript.pyannote[2390].start 13721.76846875
transcript.pyannote[2390].end 13723.87784375
transcript.pyannote[2391].speaker SPEAKER_20
transcript.pyannote[2391].start 13725.19409375
transcript.pyannote[2391].end 13726.44284375
transcript.pyannote[2392].speaker SPEAKER_03
transcript.pyannote[2392].start 13726.64534375
transcript.pyannote[2392].end 13727.50596875
transcript.pyannote[2393].speaker SPEAKER_20
transcript.pyannote[2393].start 13731.45471875
transcript.pyannote[2393].end 13732.07909375
transcript.pyannote[2394].speaker SPEAKER_20
transcript.pyannote[2394].start 13732.55159375
transcript.pyannote[2394].end 13762.40346875
transcript.pyannote[2395].speaker SPEAKER_20
transcript.pyannote[2395].start 13763.14596875
transcript.pyannote[2395].end 13814.07471875
transcript.pyannote[2396].speaker SPEAKER_20
transcript.pyannote[2396].start 13814.88471875
transcript.pyannote[2396].end 13836.78846875
transcript.pyannote[2397].speaker SPEAKER_20
transcript.pyannote[2397].start 13837.36221875
transcript.pyannote[2397].end 13844.07846875
transcript.pyannote[2398].speaker SPEAKER_00
transcript.pyannote[2398].start 13839.10034375
transcript.pyannote[2398].end 13839.11721875
transcript.pyannote[2399].speaker SPEAKER_02
transcript.pyannote[2399].start 13839.11721875
transcript.pyannote[2399].end 13839.23534375
transcript.pyannote[2400].speaker SPEAKER_02
transcript.pyannote[2400].start 13839.42096875
transcript.pyannote[2400].end 13839.50534375
transcript.pyannote[2401].speaker SPEAKER_00
transcript.pyannote[2401].start 13839.50534375
transcript.pyannote[2401].end 13839.52221875
transcript.pyannote[2402].speaker SPEAKER_20
transcript.pyannote[2402].start 13844.17971875
transcript.pyannote[2402].end 13846.84596875
transcript.pyannote[2403].speaker SPEAKER_20
transcript.pyannote[2403].start 13847.70659375
transcript.pyannote[2403].end 13849.51221875
transcript.pyannote[2404].speaker SPEAKER_27
transcript.pyannote[2404].start 13849.76534375
transcript.pyannote[2404].end 13860.02534375
transcript.pyannote[2405].speaker SPEAKER_27
transcript.pyannote[2405].start 13860.29534375
transcript.pyannote[2405].end 13882.03034375
transcript.pyannote[2406].speaker SPEAKER_20
transcript.pyannote[2406].start 13882.03034375
transcript.pyannote[2406].end 13890.82221875
transcript.pyannote[2407].speaker SPEAKER_27
transcript.pyannote[2407].start 13886.06346875
transcript.pyannote[2407].end 13886.95784375
transcript.pyannote[2408].speaker SPEAKER_27
transcript.pyannote[2408].start 13888.22346875
transcript.pyannote[2408].end 13888.57784375
transcript.pyannote[2409].speaker SPEAKER_27
transcript.pyannote[2409].start 13889.13471875
transcript.pyannote[2409].end 13893.06659375
transcript.pyannote[2410].speaker SPEAKER_20
transcript.pyannote[2410].start 13892.66159375
transcript.pyannote[2410].end 13900.81221875
transcript.pyannote[2411].speaker SPEAKER_27
transcript.pyannote[2411].start 13893.70784375
transcript.pyannote[2411].end 13894.80471875
transcript.pyannote[2412].speaker SPEAKER_27
transcript.pyannote[2412].start 13898.98971875
transcript.pyannote[2412].end 13899.14159375
transcript.pyannote[2413].speaker SPEAKER_27
transcript.pyannote[2413].start 13900.64346875
transcript.pyannote[2413].end 13901.48721875
transcript.pyannote[2414].speaker SPEAKER_20
transcript.pyannote[2414].start 13900.84596875
transcript.pyannote[2414].end 13907.51159375
transcript.pyannote[2415].speaker SPEAKER_27
transcript.pyannote[2415].start 13903.29284375
transcript.pyannote[2415].end 13903.59659375
transcript.pyannote[2416].speaker SPEAKER_27
transcript.pyannote[2416].start 13905.53721875
transcript.pyannote[2416].end 13919.56034375
transcript.pyannote[2417].speaker SPEAKER_20
transcript.pyannote[2417].start 13917.68721875
transcript.pyannote[2417].end 13923.84659375
transcript.pyannote[2418].speaker SPEAKER_20
transcript.pyannote[2418].start 13923.88034375
transcript.pyannote[2418].end 13941.66659375
transcript.pyannote[2419].speaker SPEAKER_00
transcript.pyannote[2419].start 13927.35659375
transcript.pyannote[2419].end 13927.79534375
transcript.pyannote[2420].speaker SPEAKER_00
transcript.pyannote[2420].start 13931.49096875
transcript.pyannote[2420].end 13932.36846875
transcript.pyannote[2421].speaker SPEAKER_00
transcript.pyannote[2421].start 13932.90846875
transcript.pyannote[2421].end 13933.93784375
transcript.pyannote[2422].speaker SPEAKER_02
transcript.pyannote[2422].start 13942.02096875
transcript.pyannote[2422].end 13942.17284375
transcript.pyannote[2423].speaker SPEAKER_20
transcript.pyannote[2423].start 13942.17284375
transcript.pyannote[2423].end 14002.72034375
transcript.pyannote[2424].speaker SPEAKER_00
transcript.pyannote[2424].start 13972.83471875
transcript.pyannote[2424].end 13973.03721875
transcript.pyannote[2425].speaker SPEAKER_02
transcript.pyannote[2425].start 13973.03721875
transcript.pyannote[2425].end 13973.34096875
transcript.pyannote[2426].speaker SPEAKER_00
transcript.pyannote[2426].start 13992.62909375
transcript.pyannote[2426].end 13992.64596875
transcript.pyannote[2427].speaker SPEAKER_02
transcript.pyannote[2427].start 13992.64596875
transcript.pyannote[2427].end 13992.96659375
transcript.pyannote[2428].speaker SPEAKER_00
transcript.pyannote[2428].start 13992.96659375
transcript.pyannote[2428].end 13993.18596875
transcript.pyannote[2429].speaker SPEAKER_20
transcript.pyannote[2429].start 14003.10846875
transcript.pyannote[2429].end 14009.75721875
transcript.pyannote[2430].speaker SPEAKER_02
transcript.pyannote[2430].start 14003.37846875
transcript.pyannote[2430].end 14003.49659375
transcript.pyannote[2431].speaker SPEAKER_20
transcript.pyannote[2431].start 14010.04409375
transcript.pyannote[2431].end 14013.94221875
transcript.pyannote[2432].speaker SPEAKER_20
transcript.pyannote[2432].start 14014.27971875
transcript.pyannote[2432].end 14021.65409375
transcript.pyannote[2433].speaker SPEAKER_20
transcript.pyannote[2433].start 14022.05909375
transcript.pyannote[2433].end 14037.41534375
transcript.pyannote[2434].speaker SPEAKER_27
transcript.pyannote[2434].start 14036.20034375
transcript.pyannote[2434].end 14036.89221875
transcript.pyannote[2435].speaker SPEAKER_27
transcript.pyannote[2435].start 14037.31409375
transcript.pyannote[2435].end 14040.85784375
transcript.pyannote[2436].speaker SPEAKER_27
transcript.pyannote[2436].start 14040.95909375
transcript.pyannote[2436].end 14066.55846875
transcript.pyannote[2437].speaker SPEAKER_20
transcript.pyannote[2437].start 14065.36034375
transcript.pyannote[2437].end 14101.37159375
transcript.pyannote[2438].speaker SPEAKER_02
transcript.pyannote[2438].start 14070.94596875
transcript.pyannote[2438].end 14071.16534375
transcript.pyannote[2439].speaker SPEAKER_27
transcript.pyannote[2439].start 14071.16534375
transcript.pyannote[2439].end 14071.19909375
transcript.pyannote[2440].speaker SPEAKER_02
transcript.pyannote[2440].start 14071.19909375
transcript.pyannote[2440].end 14071.23284375
transcript.pyannote[2441].speaker SPEAKER_27
transcript.pyannote[2441].start 14071.23284375
transcript.pyannote[2441].end 14071.24971875
transcript.pyannote[2442].speaker SPEAKER_02
transcript.pyannote[2442].start 14071.24971875
transcript.pyannote[2442].end 14071.33409375
transcript.pyannote[2443].speaker SPEAKER_27
transcript.pyannote[2443].start 14076.43034375
transcript.pyannote[2443].end 14076.71721875
transcript.pyannote[2444].speaker SPEAKER_00
transcript.pyannote[2444].start 14076.71721875
transcript.pyannote[2444].end 14076.88596875
transcript.pyannote[2445].speaker SPEAKER_27
transcript.pyannote[2445].start 14078.30346875
transcript.pyannote[2445].end 14078.55659375
transcript.pyannote[2446].speaker SPEAKER_27
transcript.pyannote[2446].start 14079.16409375
transcript.pyannote[2446].end 14079.19784375
transcript.pyannote[2447].speaker SPEAKER_14
transcript.pyannote[2447].start 14079.19784375
transcript.pyannote[2447].end 14079.23159375
transcript.pyannote[2448].speaker SPEAKER_27
transcript.pyannote[2448].start 14079.23159375
transcript.pyannote[2448].end 14080.96971875
transcript.pyannote[2449].speaker SPEAKER_14
transcript.pyannote[2449].start 14080.96971875
transcript.pyannote[2449].end 14081.40846875
transcript.pyannote[2450].speaker SPEAKER_02
transcript.pyannote[2450].start 14093.54159375
transcript.pyannote[2450].end 14093.76096875
transcript.pyannote[2451].speaker SPEAKER_03
transcript.pyannote[2451].start 14094.21659375
transcript.pyannote[2451].end 14094.80721875
transcript.pyannote[2452].speaker SPEAKER_03
transcript.pyannote[2452].start 14095.07721875
transcript.pyannote[2452].end 14095.14471875
transcript.pyannote[2453].speaker SPEAKER_02
transcript.pyannote[2453].start 14095.14471875
transcript.pyannote[2453].end 14095.16159375
transcript.pyannote[2454].speaker SPEAKER_03
transcript.pyannote[2454].start 14095.16159375
transcript.pyannote[2454].end 14097.15284375
transcript.pyannote[2455].speaker SPEAKER_02
transcript.pyannote[2455].start 14098.13159375
transcript.pyannote[2455].end 14098.30034375
transcript.pyannote[2456].speaker SPEAKER_03
transcript.pyannote[2456].start 14101.37159375
transcript.pyannote[2456].end 14101.40534375
transcript.pyannote[2457].speaker SPEAKER_20
transcript.pyannote[2457].start 14101.40534375
transcript.pyannote[2457].end 14102.75534375
transcript.pyannote[2458].speaker SPEAKER_03
transcript.pyannote[2458].start 14101.59096875
transcript.pyannote[2458].end 14113.13346875
transcript.pyannote[2459].speaker SPEAKER_03
transcript.pyannote[2459].start 14113.63971875
transcript.pyannote[2459].end 14114.48346875
transcript.pyannote[2460].speaker SPEAKER_03
transcript.pyannote[2460].start 14114.97284375
transcript.pyannote[2460].end 14116.45784375
transcript.pyannote[2461].speaker SPEAKER_03
transcript.pyannote[2461].start 14116.66034375
transcript.pyannote[2461].end 14119.27596875
transcript.pyannote[2462].speaker SPEAKER_15
transcript.pyannote[2462].start 14126.73471875
transcript.pyannote[2462].end 14128.45596875
transcript.pyannote[2463].speaker SPEAKER_03
transcript.pyannote[2463].start 14128.89471875
transcript.pyannote[2463].end 14129.89034375
transcript.pyannote[2464].speaker SPEAKER_15
transcript.pyannote[2464].start 14130.24471875
transcript.pyannote[2464].end 14131.37534375
transcript.pyannote[2465].speaker SPEAKER_15
transcript.pyannote[2465].start 14132.43846875
transcript.pyannote[2465].end 14133.14721875
transcript.pyannote[2466].speaker SPEAKER_03
transcript.pyannote[2466].start 14133.70409375
transcript.pyannote[2466].end 14134.19346875
transcript.pyannote[2467].speaker SPEAKER_15
transcript.pyannote[2467].start 14134.64909375
transcript.pyannote[2467].end 14135.30721875
transcript.pyannote[2468].speaker SPEAKER_15
transcript.pyannote[2468].start 14136.37034375
transcript.pyannote[2468].end 14138.02409375
transcript.pyannote[2469].speaker SPEAKER_15
transcript.pyannote[2469].start 14138.37846875
transcript.pyannote[2469].end 14138.81721875
transcript.pyannote[2470].speaker SPEAKER_15
transcript.pyannote[2470].start 14138.88471875
transcript.pyannote[2470].end 14145.26346875
transcript.pyannote[2471].speaker SPEAKER_15
transcript.pyannote[2471].start 14146.10721875
transcript.pyannote[2471].end 14146.73159375
transcript.pyannote[2472].speaker SPEAKER_15
transcript.pyannote[2472].start 14147.10284375
transcript.pyannote[2472].end 14150.98409375
transcript.pyannote[2473].speaker SPEAKER_15
transcript.pyannote[2473].start 14151.52409375
transcript.pyannote[2473].end 14177.07284375
transcript.pyannote[2474].speaker SPEAKER_15
transcript.pyannote[2474].start 14177.35971875
transcript.pyannote[2474].end 14179.41846875
transcript.pyannote[2475].speaker SPEAKER_15
transcript.pyannote[2475].start 14179.70534375
transcript.pyannote[2475].end 14183.75534375
transcript.pyannote[2476].speaker SPEAKER_15
transcript.pyannote[2476].start 14183.89034375
transcript.pyannote[2476].end 14185.52721875
transcript.pyannote[2477].speaker SPEAKER_15
transcript.pyannote[2477].start 14185.69596875
transcript.pyannote[2477].end 14186.62409375
transcript.pyannote[2478].speaker SPEAKER_15
transcript.pyannote[2478].start 14187.01221875
transcript.pyannote[2478].end 14188.32846875
transcript.pyannote[2479].speaker SPEAKER_15
transcript.pyannote[2479].start 14189.30721875
transcript.pyannote[2479].end 14190.40409375
transcript.pyannote[2480].speaker SPEAKER_27
transcript.pyannote[2480].start 14190.58971875
transcript.pyannote[2480].end 14190.91034375
transcript.pyannote[2481].speaker SPEAKER_15
transcript.pyannote[2481].start 14191.97346875
transcript.pyannote[2481].end 14193.94784375
transcript.pyannote[2482].speaker SPEAKER_15
transcript.pyannote[2482].start 14194.62284375
transcript.pyannote[2482].end 14196.04034375
transcript.pyannote[2483].speaker SPEAKER_27
transcript.pyannote[2483].start 14196.68159375
transcript.pyannote[2483].end 14196.90096875
transcript.pyannote[2484].speaker SPEAKER_15
transcript.pyannote[2484].start 14196.90096875
transcript.pyannote[2484].end 14200.76534375
transcript.pyannote[2485].speaker SPEAKER_27
transcript.pyannote[2485].start 14201.67659375
transcript.pyannote[2485].end 14204.71409375
transcript.pyannote[2486].speaker SPEAKER_27
transcript.pyannote[2486].start 14205.03471875
transcript.pyannote[2486].end 14207.58284375
transcript.pyannote[2487].speaker SPEAKER_27
transcript.pyannote[2487].start 14207.97096875
transcript.pyannote[2487].end 14214.53534375
transcript.pyannote[2488].speaker SPEAKER_27
transcript.pyannote[2488].start 14214.97409375
transcript.pyannote[2488].end 14218.07909375
transcript.pyannote[2489].speaker SPEAKER_15
transcript.pyannote[2489].start 14218.07909375
transcript.pyannote[2489].end 14226.26346875
transcript.pyannote[2490].speaker SPEAKER_27
transcript.pyannote[2490].start 14222.19659375
transcript.pyannote[2490].end 14224.87971875
transcript.pyannote[2491].speaker SPEAKER_15
transcript.pyannote[2491].start 14226.60096875
transcript.pyannote[2491].end 14234.04284375
transcript.pyannote[2492].speaker SPEAKER_15
transcript.pyannote[2492].start 14234.71784375
transcript.pyannote[2492].end 14236.84409375
transcript.pyannote[2493].speaker SPEAKER_15
transcript.pyannote[2493].start 14237.41784375
transcript.pyannote[2493].end 14238.09284375
transcript.pyannote[2494].speaker SPEAKER_27
transcript.pyannote[2494].start 14239.59471875
transcript.pyannote[2494].end 14240.08409375
transcript.pyannote[2495].speaker SPEAKER_27
transcript.pyannote[2495].start 14240.40471875
transcript.pyannote[2495].end 14243.29034375
transcript.pyannote[2496].speaker SPEAKER_27
transcript.pyannote[2496].start 14243.77971875
transcript.pyannote[2496].end 14248.21784375
transcript.pyannote[2497].speaker SPEAKER_15
transcript.pyannote[2497].start 14249.24721875
transcript.pyannote[2497].end 14251.79534375
transcript.pyannote[2498].speaker SPEAKER_27
transcript.pyannote[2498].start 14252.38596875
transcript.pyannote[2498].end 14252.84159375
transcript.pyannote[2499].speaker SPEAKER_27
transcript.pyannote[2499].start 14252.89221875
transcript.pyannote[2499].end 14262.96659375
transcript.pyannote[2500].speaker SPEAKER_27
transcript.pyannote[2500].start 14263.42221875
transcript.pyannote[2500].end 14273.32784375
transcript.pyannote[2501].speaker SPEAKER_27
transcript.pyannote[2501].start 14273.69909375
transcript.pyannote[2501].end 14274.99846875
transcript.pyannote[2502].speaker SPEAKER_15
transcript.pyannote[2502].start 14275.40346875
transcript.pyannote[2502].end 14276.60159375
transcript.pyannote[2503].speaker SPEAKER_15
transcript.pyannote[2503].start 14277.22596875
transcript.pyannote[2503].end 14278.93034375
transcript.pyannote[2504].speaker SPEAKER_15
transcript.pyannote[2504].start 14279.26784375
transcript.pyannote[2504].end 14282.52471875
transcript.pyannote[2505].speaker SPEAKER_15
transcript.pyannote[2505].start 14282.96346875
transcript.pyannote[2505].end 14283.58784375
transcript.pyannote[2506].speaker SPEAKER_15
transcript.pyannote[2506].start 14283.60471875
transcript.pyannote[2506].end 14286.62534375
transcript.pyannote[2507].speaker SPEAKER_27
transcript.pyannote[2507].start 14287.01346875
transcript.pyannote[2507].end 14295.53534375
transcript.pyannote[2508].speaker SPEAKER_27
transcript.pyannote[2508].start 14295.85596875
transcript.pyannote[2508].end 14298.64034375
transcript.pyannote[2509].speaker SPEAKER_27
transcript.pyannote[2509].start 14298.82596875
transcript.pyannote[2509].end 14303.93909375
transcript.pyannote[2510].speaker SPEAKER_00
transcript.pyannote[2510].start 14298.85971875
transcript.pyannote[2510].end 14299.02846875
transcript.pyannote[2511].speaker SPEAKER_02
transcript.pyannote[2511].start 14299.02846875
transcript.pyannote[2511].end 14299.06221875
transcript.pyannote[2512].speaker SPEAKER_00
transcript.pyannote[2512].start 14299.06221875
transcript.pyannote[2512].end 14299.21409375
transcript.pyannote[2513].speaker SPEAKER_27
transcript.pyannote[2513].start 14304.15846875
transcript.pyannote[2513].end 14306.01471875
transcript.pyannote[2514].speaker SPEAKER_27
transcript.pyannote[2514].start 14306.25096875
transcript.pyannote[2514].end 14308.83284375
transcript.pyannote[2515].speaker SPEAKER_27
transcript.pyannote[2515].start 14309.15346875
transcript.pyannote[2515].end 14311.75221875
transcript.pyannote[2516].speaker SPEAKER_27
transcript.pyannote[2516].start 14312.08971875
transcript.pyannote[2516].end 14312.47784375
transcript.pyannote[2517].speaker SPEAKER_27
transcript.pyannote[2517].start 14313.65909375
transcript.pyannote[2517].end 14316.32534375
transcript.pyannote[2518].speaker SPEAKER_15
transcript.pyannote[2518].start 14316.42659375
transcript.pyannote[2518].end 14319.00846875
transcript.pyannote[2519].speaker SPEAKER_15
transcript.pyannote[2519].start 14319.26159375
transcript.pyannote[2519].end 14322.02909375
transcript.pyannote[2520].speaker SPEAKER_27
transcript.pyannote[2520].start 14319.66659375
transcript.pyannote[2520].end 14320.22346875
transcript.pyannote[2521].speaker SPEAKER_15
transcript.pyannote[2521].start 14322.29909375
transcript.pyannote[2521].end 14323.66596875
transcript.pyannote[2522].speaker SPEAKER_27
transcript.pyannote[2522].start 14323.66596875
transcript.pyannote[2522].end 14324.23971875
transcript.pyannote[2523].speaker SPEAKER_15
transcript.pyannote[2523].start 14324.35784375
transcript.pyannote[2523].end 14327.54721875
transcript.pyannote[2524].speaker SPEAKER_27
transcript.pyannote[2524].start 14324.93159375
transcript.pyannote[2524].end 14325.35346875
transcript.pyannote[2525].speaker SPEAKER_27
transcript.pyannote[2525].start 14326.78784375
transcript.pyannote[2525].end 14327.17596875
transcript.pyannote[2526].speaker SPEAKER_27
transcript.pyannote[2526].start 14328.07034375
transcript.pyannote[2526].end 14328.66096875
transcript.pyannote[2527].speaker SPEAKER_15
transcript.pyannote[2527].start 14328.71159375
transcript.pyannote[2527].end 14329.75784375
transcript.pyannote[2528].speaker SPEAKER_27
transcript.pyannote[2528].start 14329.48784375
transcript.pyannote[2528].end 14332.66034375
transcript.pyannote[2529].speaker SPEAKER_15
transcript.pyannote[2529].start 14330.41596875
transcript.pyannote[2529].end 14331.49596875
transcript.pyannote[2530].speaker SPEAKER_15
transcript.pyannote[2530].start 14332.06971875
transcript.pyannote[2530].end 14335.47846875
transcript.pyannote[2531].speaker SPEAKER_27
transcript.pyannote[2531].start 14334.22971875
transcript.pyannote[2531].end 14334.98909375
transcript.pyannote[2532].speaker SPEAKER_27
transcript.pyannote[2532].start 14335.36034375
transcript.pyannote[2532].end 14335.76534375
transcript.pyannote[2533].speaker SPEAKER_15
transcript.pyannote[2533].start 14335.68096875
transcript.pyannote[2533].end 14336.89596875
transcript.pyannote[2534].speaker SPEAKER_27
transcript.pyannote[2534].start 14337.31784375
transcript.pyannote[2534].end 14338.04346875
transcript.pyannote[2535].speaker SPEAKER_15
transcript.pyannote[2535].start 14337.55409375
transcript.pyannote[2535].end 14341.40159375
transcript.pyannote[2536].speaker SPEAKER_27
transcript.pyannote[2536].start 14338.63409375
transcript.pyannote[2536].end 14340.22034375
transcript.pyannote[2537].speaker SPEAKER_15
transcript.pyannote[2537].start 14341.48596875
transcript.pyannote[2537].end 14342.11034375
transcript.pyannote[2538].speaker SPEAKER_27
transcript.pyannote[2538].start 14342.73471875
transcript.pyannote[2538].end 14343.12284375
transcript.pyannote[2539].speaker SPEAKER_15
transcript.pyannote[2539].start 14343.22409375
transcript.pyannote[2539].end 14345.62034375
transcript.pyannote[2540].speaker SPEAKER_27
transcript.pyannote[2540].start 14345.97471875
transcript.pyannote[2540].end 14346.59909375
transcript.pyannote[2541].speaker SPEAKER_27
transcript.pyannote[2541].start 14346.86909375
transcript.pyannote[2541].end 14347.57784375
transcript.pyannote[2542].speaker SPEAKER_15
transcript.pyannote[2542].start 14348.97846875
transcript.pyannote[2542].end 14350.12596875
transcript.pyannote[2543].speaker SPEAKER_27
transcript.pyannote[2543].start 14350.66596875
transcript.pyannote[2543].end 14351.20596875
transcript.pyannote[2544].speaker SPEAKER_15
transcript.pyannote[2544].start 14351.20596875
transcript.pyannote[2544].end 14352.10034375
transcript.pyannote[2545].speaker SPEAKER_02
transcript.pyannote[2545].start 14354.22659375
transcript.pyannote[2545].end 14354.29409375
transcript.pyannote[2546].speaker SPEAKER_15
transcript.pyannote[2546].start 14354.58096875
transcript.pyannote[2546].end 14354.78346875
transcript.pyannote[2547].speaker SPEAKER_15
transcript.pyannote[2547].start 14355.76221875
transcript.pyannote[2547].end 14356.33596875
transcript.pyannote[2548].speaker SPEAKER_15
transcript.pyannote[2548].start 14356.67346875
transcript.pyannote[2548].end 14357.83784375
transcript.pyannote[2549].speaker SPEAKER_15
transcript.pyannote[2549].start 14358.19221875
transcript.pyannote[2549].end 14363.30534375
transcript.pyannote[2550].speaker SPEAKER_27
transcript.pyannote[2550].start 14363.06909375
transcript.pyannote[2550].end 14365.12784375
transcript.pyannote[2551].speaker SPEAKER_15
transcript.pyannote[2551].start 14363.71034375
transcript.pyannote[2551].end 14367.67596875
transcript.pyannote[2552].speaker SPEAKER_27
transcript.pyannote[2552].start 14365.80284375
transcript.pyannote[2552].end 14366.66346875
transcript.pyannote[2553].speaker SPEAKER_27
transcript.pyannote[2553].start 14367.20346875
transcript.pyannote[2553].end 14367.32159375
transcript.pyannote[2554].speaker SPEAKER_27
transcript.pyannote[2554].start 14367.70971875
transcript.pyannote[2554].end 14367.72659375
transcript.pyannote[2555].speaker SPEAKER_27
transcript.pyannote[2555].start 14367.74346875
transcript.pyannote[2555].end 14369.05971875
transcript.pyannote[2556].speaker SPEAKER_27
transcript.pyannote[2556].start 14369.44784375
transcript.pyannote[2556].end 14375.57346875
transcript.pyannote[2557].speaker SPEAKER_15
transcript.pyannote[2557].start 14370.37596875
transcript.pyannote[2557].end 14371.81034375
transcript.pyannote[2558].speaker SPEAKER_15
transcript.pyannote[2558].start 14375.67471875
transcript.pyannote[2558].end 14375.89409375
transcript.pyannote[2559].speaker SPEAKER_27
transcript.pyannote[2559].start 14375.89409375
transcript.pyannote[2559].end 14377.22721875
transcript.pyannote[2560].speaker SPEAKER_15
transcript.pyannote[2560].start 14377.36221875
transcript.pyannote[2560].end 14381.61471875
transcript.pyannote[2561].speaker SPEAKER_27
transcript.pyannote[2561].start 14380.75409375
transcript.pyannote[2561].end 14383.90971875
transcript.pyannote[2562].speaker SPEAKER_27
transcript.pyannote[2562].start 14383.97721875
transcript.pyannote[2562].end 14388.39846875
transcript.pyannote[2563].speaker SPEAKER_15
transcript.pyannote[2563].start 14387.38596875
transcript.pyannote[2563].end 14394.33846875
transcript.pyannote[2564].speaker SPEAKER_27
transcript.pyannote[2564].start 14393.32596875
transcript.pyannote[2564].end 14393.54534375
transcript.pyannote[2565].speaker SPEAKER_27
transcript.pyannote[2565].start 14393.76471875
transcript.pyannote[2565].end 14396.36346875
transcript.pyannote[2566].speaker SPEAKER_15
transcript.pyannote[2566].start 14395.60409375
transcript.pyannote[2566].end 14396.49846875
transcript.pyannote[2567].speaker SPEAKER_27
transcript.pyannote[2567].start 14396.49846875
transcript.pyannote[2567].end 14404.83471875
transcript.pyannote[2568].speaker SPEAKER_15
transcript.pyannote[2568].start 14404.83471875
transcript.pyannote[2568].end 14406.25221875
transcript.pyannote[2569].speaker SPEAKER_15
transcript.pyannote[2569].start 14406.80909375
transcript.pyannote[2569].end 14430.13034375
transcript.pyannote[2570].speaker SPEAKER_15
transcript.pyannote[2570].start 14430.68721875
transcript.pyannote[2570].end 14431.58159375
transcript.pyannote[2571].speaker SPEAKER_15
transcript.pyannote[2571].start 14431.91909375
transcript.pyannote[2571].end 14443.81596875
transcript.pyannote[2572].speaker SPEAKER_15
transcript.pyannote[2572].start 14443.90034375
transcript.pyannote[2572].end 14446.19534375
transcript.pyannote[2573].speaker SPEAKER_15
transcript.pyannote[2573].start 14447.05596875
transcript.pyannote[2573].end 14449.82346875
transcript.pyannote[2574].speaker SPEAKER_02
transcript.pyannote[2574].start 14449.82346875
transcript.pyannote[2574].end 14450.19471875
transcript.pyannote[2575].speaker SPEAKER_02
transcript.pyannote[2575].start 14450.34659375
transcript.pyannote[2575].end 14451.37596875
transcript.pyannote[2576].speaker SPEAKER_15
transcript.pyannote[2576].start 14450.66721875
transcript.pyannote[2576].end 14459.18909375
transcript.pyannote[2577].speaker SPEAKER_15
transcript.pyannote[2577].start 14459.62784375
transcript.pyannote[2577].end 14461.60221875
transcript.pyannote[2578].speaker SPEAKER_27
transcript.pyannote[2578].start 14462.02409375
transcript.pyannote[2578].end 14479.47284375
transcript.pyannote[2579].speaker SPEAKER_27
transcript.pyannote[2579].start 14479.55721875
transcript.pyannote[2579].end 14484.60284375
transcript.pyannote[2580].speaker SPEAKER_27
transcript.pyannote[2580].start 14485.15971875
transcript.pyannote[2580].end 14494.12034375
transcript.pyannote[2581].speaker SPEAKER_27
transcript.pyannote[2581].start 14494.35659375
transcript.pyannote[2581].end 14495.87534375
transcript.pyannote[2582].speaker SPEAKER_15
transcript.pyannote[2582].start 14494.47471875
transcript.pyannote[2582].end 14506.37159375
transcript.pyannote[2583].speaker SPEAKER_02
transcript.pyannote[2583].start 14495.87534375
transcript.pyannote[2583].end 14495.89221875
transcript.pyannote[2584].speaker SPEAKER_15
transcript.pyannote[2584].start 14506.42221875
transcript.pyannote[2584].end 14507.31659375
transcript.pyannote[2585].speaker SPEAKER_15
transcript.pyannote[2585].start 14507.80596875
transcript.pyannote[2585].end 14511.16409375
transcript.pyannote[2586].speaker SPEAKER_15
transcript.pyannote[2586].start 14511.83909375
transcript.pyannote[2586].end 14517.08721875
transcript.pyannote[2587].speaker SPEAKER_15
transcript.pyannote[2587].start 14517.10409375
transcript.pyannote[2587].end 14518.79159375
transcript.pyannote[2588].speaker SPEAKER_15
transcript.pyannote[2588].start 14519.19659375
transcript.pyannote[2588].end 14519.92221875
transcript.pyannote[2589].speaker SPEAKER_15
transcript.pyannote[2589].start 14520.47909375
transcript.pyannote[2589].end 14522.75721875
transcript.pyannote[2590].speaker SPEAKER_02
transcript.pyannote[2590].start 14522.75721875
transcript.pyannote[2590].end 14522.84159375
transcript.pyannote[2591].speaker SPEAKER_15
transcript.pyannote[2591].start 14523.17909375
transcript.pyannote[2591].end 14524.59659375
transcript.pyannote[2592].speaker SPEAKER_02
transcript.pyannote[2592].start 14524.83284375
transcript.pyannote[2592].end 14525.20409375
transcript.pyannote[2593].speaker SPEAKER_15
transcript.pyannote[2593].start 14525.15346875
transcript.pyannote[2593].end 14534.33346875
transcript.pyannote[2594].speaker SPEAKER_15
transcript.pyannote[2594].start 14534.56971875
transcript.pyannote[2594].end 14535.48096875
transcript.pyannote[2595].speaker SPEAKER_15
transcript.pyannote[2595].start 14535.56534375
transcript.pyannote[2595].end 14537.47221875
transcript.pyannote[2596].speaker SPEAKER_15
transcript.pyannote[2596].start 14538.24846875
transcript.pyannote[2596].end 14542.51784375
transcript.pyannote[2597].speaker SPEAKER_15
transcript.pyannote[2597].start 14542.92284375
transcript.pyannote[2597].end 14543.91846875
transcript.pyannote[2598].speaker SPEAKER_15
transcript.pyannote[2598].start 14544.20534375
transcript.pyannote[2598].end 14545.13346875
transcript.pyannote[2599].speaker SPEAKER_15
transcript.pyannote[2599].start 14545.57221875
transcript.pyannote[2599].end 14550.06096875
transcript.pyannote[2600].speaker SPEAKER_15
transcript.pyannote[2600].start 14550.33096875
transcript.pyannote[2600].end 14553.45284375
transcript.pyannote[2601].speaker SPEAKER_15
transcript.pyannote[2601].start 14553.85784375
transcript.pyannote[2601].end 14559.34221875
transcript.pyannote[2602].speaker SPEAKER_15
transcript.pyannote[2602].start 14560.59096875
transcript.pyannote[2602].end 14561.24909375
transcript.pyannote[2603].speaker SPEAKER_27
transcript.pyannote[2603].start 14562.56534375
transcript.pyannote[2603].end 14562.58221875
transcript.pyannote[2604].speaker SPEAKER_15
transcript.pyannote[2604].start 14562.58221875
transcript.pyannote[2604].end 14564.84346875
transcript.pyannote[2605].speaker SPEAKER_27
transcript.pyannote[2605].start 14564.84346875
transcript.pyannote[2605].end 14565.46784375
transcript.pyannote[2606].speaker SPEAKER_15
transcript.pyannote[2606].start 14565.61971875
transcript.pyannote[2606].end 14566.37909375
transcript.pyannote[2607].speaker SPEAKER_27
transcript.pyannote[2607].start 14566.42971875
transcript.pyannote[2607].end 14566.98659375
transcript.pyannote[2608].speaker SPEAKER_27
transcript.pyannote[2608].start 14567.34096875
transcript.pyannote[2608].end 14571.40784375
transcript.pyannote[2609].speaker SPEAKER_27
transcript.pyannote[2609].start 14571.94784375
transcript.pyannote[2609].end 14573.36534375
transcript.pyannote[2610].speaker SPEAKER_15
transcript.pyannote[2610].start 14573.51721875
transcript.pyannote[2610].end 14574.96846875
transcript.pyannote[2611].speaker SPEAKER_15
transcript.pyannote[2611].start 14575.55909375
transcript.pyannote[2611].end 14575.84596875
transcript.pyannote[2612].speaker SPEAKER_15
transcript.pyannote[2612].start 14575.91346875
transcript.pyannote[2612].end 14577.11159375
transcript.pyannote[2613].speaker SPEAKER_15
transcript.pyannote[2613].start 14577.63471875
transcript.pyannote[2613].end 14580.18284375
transcript.pyannote[2614].speaker SPEAKER_15
transcript.pyannote[2614].start 14580.48659375
transcript.pyannote[2614].end 14597.56409375
transcript.pyannote[2615].speaker SPEAKER_15
transcript.pyannote[2615].start 14597.66534375
transcript.pyannote[2615].end 14600.02784375
transcript.pyannote[2616].speaker SPEAKER_15
transcript.pyannote[2616].start 14601.10784375
transcript.pyannote[2616].end 14607.50346875
transcript.pyannote[2617].speaker SPEAKER_15
transcript.pyannote[2617].start 14608.75221875
transcript.pyannote[2617].end 14609.12346875
transcript.pyannote[2618].speaker SPEAKER_27
transcript.pyannote[2618].start 14610.45659375
transcript.pyannote[2618].end 14611.89096875
transcript.pyannote[2619].speaker SPEAKER_15
transcript.pyannote[2619].start 14611.77284375
transcript.pyannote[2619].end 14612.26221875
transcript.pyannote[2620].speaker SPEAKER_27
transcript.pyannote[2620].start 14612.58284375
transcript.pyannote[2620].end 14612.98784375
transcript.pyannote[2621].speaker SPEAKER_15
transcript.pyannote[2621].start 14613.19034375
transcript.pyannote[2621].end 14617.86471875
transcript.pyannote[2622].speaker SPEAKER_27
transcript.pyannote[2622].start 14613.27471875
transcript.pyannote[2622].end 14613.30846875
transcript.pyannote[2623].speaker SPEAKER_27
transcript.pyannote[2623].start 14613.32534375
transcript.pyannote[2623].end 14616.88596875
transcript.pyannote[2624].speaker SPEAKER_27
transcript.pyannote[2624].start 14618.80971875
transcript.pyannote[2624].end 14619.40034375
transcript.pyannote[2625].speaker SPEAKER_27
transcript.pyannote[2625].start 14619.73784375
transcript.pyannote[2625].end 14625.55971875
transcript.pyannote[2626].speaker SPEAKER_15
transcript.pyannote[2626].start 14624.53034375
transcript.pyannote[2626].end 14627.17971875
transcript.pyannote[2627].speaker SPEAKER_27
transcript.pyannote[2627].start 14626.01534375
transcript.pyannote[2627].end 14627.97284375
transcript.pyannote[2628].speaker SPEAKER_15
transcript.pyannote[2628].start 14628.24284375
transcript.pyannote[2628].end 14635.04346875
transcript.pyannote[2629].speaker SPEAKER_27
transcript.pyannote[2629].start 14628.27659375
transcript.pyannote[2629].end 14629.52534375
transcript.pyannote[2630].speaker SPEAKER_15
transcript.pyannote[2630].start 14635.38096875
transcript.pyannote[2630].end 14638.04721875
transcript.pyannote[2631].speaker SPEAKER_27
transcript.pyannote[2631].start 14637.22034375
transcript.pyannote[2631].end 14640.66284375
transcript.pyannote[2632].speaker SPEAKER_15
transcript.pyannote[2632].start 14640.30846875
transcript.pyannote[2632].end 14645.13471875
transcript.pyannote[2633].speaker SPEAKER_15
transcript.pyannote[2633].start 14645.37096875
transcript.pyannote[2633].end 14652.94784375
transcript.pyannote[2634].speaker SPEAKER_02
transcript.pyannote[2634].start 14649.31971875
transcript.pyannote[2634].end 14649.79221875
transcript.pyannote[2635].speaker SPEAKER_15
transcript.pyannote[2635].start 14653.09971875
transcript.pyannote[2635].end 14656.23846875
transcript.pyannote[2636].speaker SPEAKER_02
transcript.pyannote[2636].start 14656.12034375
transcript.pyannote[2636].end 14656.49159375
transcript.pyannote[2637].speaker SPEAKER_15
transcript.pyannote[2637].start 14656.39034375
transcript.pyannote[2637].end 14662.21221875
transcript.pyannote[2638].speaker SPEAKER_15
transcript.pyannote[2638].start 14662.39784375
transcript.pyannote[2638].end 14664.96284375
transcript.pyannote[2639].speaker SPEAKER_02
transcript.pyannote[2639].start 14663.81534375
transcript.pyannote[2639].end 14665.08096875
transcript.pyannote[2640].speaker SPEAKER_15
transcript.pyannote[2640].start 14664.99659375
transcript.pyannote[2640].end 14667.13971875
transcript.pyannote[2641].speaker SPEAKER_02
transcript.pyannote[2641].start 14667.12284375
transcript.pyannote[2641].end 14667.46034375
transcript.pyannote[2642].speaker SPEAKER_15
transcript.pyannote[2642].start 14667.35909375
transcript.pyannote[2642].end 14670.75096875
transcript.pyannote[2643].speaker SPEAKER_02
transcript.pyannote[2643].start 14668.64159375
transcript.pyannote[2643].end 14670.17721875
transcript.pyannote[2644].speaker SPEAKER_02
transcript.pyannote[2644].start 14670.51471875
transcript.pyannote[2644].end 14670.97034375
transcript.pyannote[2645].speaker SPEAKER_15
transcript.pyannote[2645].start 14670.97034375
transcript.pyannote[2645].end 14671.79721875
transcript.pyannote[2646].speaker SPEAKER_15
transcript.pyannote[2646].start 14672.52284375
transcript.pyannote[2646].end 14705.00721875
transcript.pyannote[2647].speaker SPEAKER_15
transcript.pyannote[2647].start 14705.26034375
transcript.pyannote[2647].end 14706.15471875
transcript.pyannote[2648].speaker SPEAKER_15
transcript.pyannote[2648].start 14706.89721875
transcript.pyannote[2648].end 14709.07409375
transcript.pyannote[2649].speaker SPEAKER_15
transcript.pyannote[2649].start 14709.32721875
transcript.pyannote[2649].end 14711.09909375
transcript.pyannote[2650].speaker SPEAKER_15
transcript.pyannote[2650].start 14711.57159375
transcript.pyannote[2650].end 14719.01346875
transcript.pyannote[2651].speaker SPEAKER_15
transcript.pyannote[2651].start 14719.72221875
transcript.pyannote[2651].end 14741.67659375
transcript.pyannote[2652].speaker SPEAKER_15
transcript.pyannote[2652].start 14742.28409375
transcript.pyannote[2652].end 14745.40596875
transcript.pyannote[2653].speaker SPEAKER_15
transcript.pyannote[2653].start 14746.08096875
transcript.pyannote[2653].end 14750.60346875
transcript.pyannote[2654].speaker SPEAKER_15
transcript.pyannote[2654].start 14750.97471875
transcript.pyannote[2654].end 14754.04596875
transcript.pyannote[2655].speaker SPEAKER_15
transcript.pyannote[2655].start 14754.99096875
transcript.pyannote[2655].end 14756.32409375
transcript.pyannote[2656].speaker SPEAKER_15
transcript.pyannote[2656].start 14756.86409375
transcript.pyannote[2656].end 14758.34909375
transcript.pyannote[2657].speaker SPEAKER_15
transcript.pyannote[2657].start 14759.04096875
transcript.pyannote[2657].end 14760.03659375
transcript.pyannote[2658].speaker SPEAKER_15
transcript.pyannote[2658].start 14760.61034375
transcript.pyannote[2658].end 14772.28784375
transcript.pyannote[2659].speaker SPEAKER_15
transcript.pyannote[2659].start 14772.96284375
transcript.pyannote[2659].end 14774.32971875
transcript.pyannote[2660].speaker SPEAKER_15
transcript.pyannote[2660].start 14774.49846875
transcript.pyannote[2660].end 14775.29159375
transcript.pyannote[2661].speaker SPEAKER_15
transcript.pyannote[2661].start 14776.72596875
transcript.pyannote[2661].end 14779.40909375
transcript.pyannote[2662].speaker SPEAKER_15
transcript.pyannote[2662].start 14779.61159375
transcript.pyannote[2662].end 14784.15096875
transcript.pyannote[2663].speaker SPEAKER_15
transcript.pyannote[2663].start 14784.84284375
transcript.pyannote[2663].end 14787.17159375
transcript.pyannote[2664].speaker SPEAKER_15
transcript.pyannote[2664].start 14787.40784375
transcript.pyannote[2664].end 14789.70284375
transcript.pyannote[2665].speaker SPEAKER_15
transcript.pyannote[2665].start 14789.92221875
transcript.pyannote[2665].end 14792.48721875
transcript.pyannote[2666].speaker SPEAKER_15
transcript.pyannote[2666].start 14793.51659375
transcript.pyannote[2666].end 14793.85409375
transcript.pyannote[2667].speaker SPEAKER_15
transcript.pyannote[2667].start 14793.98909375
transcript.pyannote[2667].end 14794.41096875
transcript.pyannote[2668].speaker SPEAKER_15
transcript.pyannote[2668].start 14794.69784375
transcript.pyannote[2668].end 14797.19534375
transcript.pyannote[2669].speaker SPEAKER_15
transcript.pyannote[2669].start 14797.71846875
transcript.pyannote[2669].end 14798.93346875
transcript.pyannote[2670].speaker SPEAKER_02
transcript.pyannote[2670].start 14799.33846875
transcript.pyannote[2670].end 14799.72659375
transcript.pyannote[2671].speaker SPEAKER_15
transcript.pyannote[2671].start 14799.72659375
transcript.pyannote[2671].end 14800.58721875
transcript.pyannote[2672].speaker SPEAKER_15
transcript.pyannote[2672].start 14800.99221875
transcript.pyannote[2672].end 14810.18909375
transcript.pyannote[2673].speaker SPEAKER_15
transcript.pyannote[2673].start 14810.44221875
transcript.pyannote[2673].end 14811.82596875
transcript.pyannote[2674].speaker SPEAKER_15
transcript.pyannote[2674].start 14812.45034375
transcript.pyannote[2674].end 14814.49221875
transcript.pyannote[2675].speaker SPEAKER_27
transcript.pyannote[2675].start 14814.49221875
transcript.pyannote[2675].end 14814.79596875
transcript.pyannote[2676].speaker SPEAKER_27
transcript.pyannote[2676].start 14815.13346875
transcript.pyannote[2676].end 14821.22534375
transcript.pyannote[2677].speaker SPEAKER_27
transcript.pyannote[2677].start 14821.57971875
transcript.pyannote[2677].end 14823.08159375
transcript.pyannote[2678].speaker SPEAKER_27
transcript.pyannote[2678].start 14823.31784375
transcript.pyannote[2678].end 14823.82409375
transcript.pyannote[2679].speaker SPEAKER_27
transcript.pyannote[2679].start 14823.99284375
transcript.pyannote[2679].end 14827.45221875
transcript.pyannote[2680].speaker SPEAKER_27
transcript.pyannote[2680].start 14827.87409375
transcript.pyannote[2680].end 14830.00034375
transcript.pyannote[2681].speaker SPEAKER_15
transcript.pyannote[2681].start 14830.32096875
transcript.pyannote[2681].end 14837.47596875
transcript.pyannote[2682].speaker SPEAKER_27
transcript.pyannote[2682].start 14837.64471875
transcript.pyannote[2682].end 14837.81346875
transcript.pyannote[2683].speaker SPEAKER_15
transcript.pyannote[2683].start 14837.81346875
transcript.pyannote[2683].end 14841.00284375
transcript.pyannote[2684].speaker SPEAKER_27
transcript.pyannote[2684].start 14837.84721875
transcript.pyannote[2684].end 14837.86409375
transcript.pyannote[2685].speaker SPEAKER_27
transcript.pyannote[2685].start 14842.52159375
transcript.pyannote[2685].end 14843.97284375
transcript.pyannote[2686].speaker SPEAKER_15
transcript.pyannote[2686].start 14844.42846875
transcript.pyannote[2686].end 14845.79534375
transcript.pyannote[2687].speaker SPEAKER_27
transcript.pyannote[2687].start 14845.45784375
transcript.pyannote[2687].end 14847.61784375
transcript.pyannote[2688].speaker SPEAKER_15
transcript.pyannote[2688].start 14848.41096875
transcript.pyannote[2688].end 14849.23784375
transcript.pyannote[2689].speaker SPEAKER_15
transcript.pyannote[2689].start 14850.11534375
transcript.pyannote[2689].end 14851.38096875
transcript.pyannote[2690].speaker SPEAKER_27
transcript.pyannote[2690].start 14851.38096875
transcript.pyannote[2690].end 14853.57471875
transcript.pyannote[2691].speaker SPEAKER_15
transcript.pyannote[2691].start 14852.24159375
transcript.pyannote[2691].end 14852.59596875
transcript.pyannote[2692].speaker SPEAKER_15
transcript.pyannote[2692].start 14853.57471875
transcript.pyannote[2692].end 14855.17784375
transcript.pyannote[2693].speaker SPEAKER_27
transcript.pyannote[2693].start 14854.11471875
transcript.pyannote[2693].end 14854.67159375
transcript.pyannote[2694].speaker SPEAKER_15
transcript.pyannote[2694].start 14855.29596875
transcript.pyannote[2694].end 14860.67909375
transcript.pyannote[2695].speaker SPEAKER_27
transcript.pyannote[2695].start 14859.21096875
transcript.pyannote[2695].end 14859.27846875
transcript.pyannote[2696].speaker SPEAKER_02
transcript.pyannote[2696].start 14859.27846875
transcript.pyannote[2696].end 14860.13909375
transcript.pyannote[2697].speaker SPEAKER_02
transcript.pyannote[2697].start 14860.57784375
transcript.pyannote[2697].end 14860.96596875
transcript.pyannote[2698].speaker SPEAKER_15
transcript.pyannote[2698].start 14861.15159375
transcript.pyannote[2698].end 14871.44534375
transcript.pyannote[2699].speaker SPEAKER_02
transcript.pyannote[2699].start 14862.31596875
transcript.pyannote[2699].end 14862.70409375
transcript.pyannote[2700].speaker SPEAKER_15
transcript.pyannote[2700].start 14871.59721875
transcript.pyannote[2700].end 14882.07659375
transcript.pyannote[2701].speaker SPEAKER_15
transcript.pyannote[2701].start 14882.46471875
transcript.pyannote[2701].end 14884.60784375
transcript.pyannote[2702].speaker SPEAKER_15
transcript.pyannote[2702].start 14885.23221875
transcript.pyannote[2702].end 14886.64971875
transcript.pyannote[2703].speaker SPEAKER_03
transcript.pyannote[2703].start 14886.64971875
transcript.pyannote[2703].end 14886.90284375
transcript.pyannote[2704].speaker SPEAKER_15
transcript.pyannote[2704].start 14886.98721875
transcript.pyannote[2704].end 14887.64534375
transcript.pyannote[2705].speaker SPEAKER_03
transcript.pyannote[2705].start 14887.84784375
transcript.pyannote[2705].end 14888.84346875
transcript.pyannote[2706].speaker SPEAKER_03
transcript.pyannote[2706].start 14889.36659375
transcript.pyannote[2706].end 14892.97784375
transcript.pyannote[2707].speaker SPEAKER_10
transcript.pyannote[2707].start 14900.97659375
transcript.pyannote[2707].end 14904.28409375
transcript.pyannote[2708].speaker SPEAKER_10
transcript.pyannote[2708].start 14907.06846875
transcript.pyannote[2708].end 14908.53659375
transcript.pyannote[2709].speaker SPEAKER_02
transcript.pyannote[2709].start 14907.94596875
transcript.pyannote[2709].end 14908.01346875
transcript.pyannote[2710].speaker SPEAKER_27
transcript.pyannote[2710].start 14908.01346875
transcript.pyannote[2710].end 14908.35096875
transcript.pyannote[2711].speaker SPEAKER_02
transcript.pyannote[2711].start 14908.35096875
transcript.pyannote[2711].end 14908.36784375
transcript.pyannote[2712].speaker SPEAKER_10
transcript.pyannote[2712].start 14908.78971875
transcript.pyannote[2712].end 14915.43846875
transcript.pyannote[2713].speaker SPEAKER_10
transcript.pyannote[2713].start 14915.72534375
transcript.pyannote[2713].end 14921.85096875
transcript.pyannote[2714].speaker SPEAKER_27
transcript.pyannote[2714].start 14917.02471875
transcript.pyannote[2714].end 14917.53096875
transcript.pyannote[2715].speaker SPEAKER_27
transcript.pyannote[2715].start 14921.58096875
transcript.pyannote[2715].end 14927.57159375
transcript.pyannote[2716].speaker SPEAKER_10
transcript.pyannote[2716].start 14925.14159375
transcript.pyannote[2716].end 14926.08659375
transcript.pyannote[2717].speaker SPEAKER_10
transcript.pyannote[2717].start 14927.57159375
transcript.pyannote[2717].end 14928.78659375
transcript.pyannote[2718].speaker SPEAKER_27
transcript.pyannote[2718].start 14928.14534375
transcript.pyannote[2718].end 14929.03971875
transcript.pyannote[2719].speaker SPEAKER_10
transcript.pyannote[2719].start 14929.24221875
transcript.pyannote[2719].end 14946.77534375
transcript.pyannote[2720].speaker SPEAKER_09
transcript.pyannote[2720].start 14943.16409375
transcript.pyannote[2720].end 14943.18096875
transcript.pyannote[2721].speaker SPEAKER_27
transcript.pyannote[2721].start 14943.18096875
transcript.pyannote[2721].end 14943.56909375
transcript.pyannote[2722].speaker SPEAKER_00
transcript.pyannote[2722].start 14943.83909375
transcript.pyannote[2722].end 14943.85596875
transcript.pyannote[2723].speaker SPEAKER_27
transcript.pyannote[2723].start 14943.85596875
transcript.pyannote[2723].end 14944.24409375
transcript.pyannote[2724].speaker SPEAKER_10
transcript.pyannote[2724].start 14947.29846875
transcript.pyannote[2724].end 14947.88909375
transcript.pyannote[2725].speaker SPEAKER_10
transcript.pyannote[2725].start 14948.63159375
transcript.pyannote[2725].end 14949.13784375
transcript.pyannote[2726].speaker SPEAKER_27
transcript.pyannote[2726].start 14948.76659375
transcript.pyannote[2726].end 14959.27971875
transcript.pyannote[2727].speaker SPEAKER_27
transcript.pyannote[2727].start 14959.33034375
transcript.pyannote[2727].end 14965.84409375
transcript.pyannote[2728].speaker SPEAKER_00
transcript.pyannote[2728].start 14965.00034375
transcript.pyannote[2728].end 14968.74659375
transcript.pyannote[2729].speaker SPEAKER_27
transcript.pyannote[2729].start 14966.50221875
transcript.pyannote[2729].end 14968.29096875
transcript.pyannote[2730].speaker SPEAKER_27
transcript.pyannote[2730].start 14968.74659375
transcript.pyannote[2730].end 14973.13409375
transcript.pyannote[2731].speaker SPEAKER_00
transcript.pyannote[2731].start 14973.42096875
transcript.pyannote[2731].end 14973.53909375
transcript.pyannote[2732].speaker SPEAKER_27
transcript.pyannote[2732].start 14973.53909375
transcript.pyannote[2732].end 14977.84221875
transcript.pyannote[2733].speaker SPEAKER_10
transcript.pyannote[2733].start 14977.77471875
transcript.pyannote[2733].end 14978.92221875
transcript.pyannote[2734].speaker SPEAKER_27
transcript.pyannote[2734].start 14978.65221875
transcript.pyannote[2734].end 14984.18721875
transcript.pyannote[2735].speaker SPEAKER_10
transcript.pyannote[2735].start 14984.25471875
transcript.pyannote[2735].end 15001.02846875
transcript.pyannote[2736].speaker SPEAKER_27
transcript.pyannote[2736].start 15001.02846875
transcript.pyannote[2736].end 15007.25534375
transcript.pyannote[2737].speaker SPEAKER_10
transcript.pyannote[2737].start 15007.06971875
transcript.pyannote[2737].end 15007.08659375
transcript.pyannote[2738].speaker SPEAKER_02
transcript.pyannote[2738].start 15007.08659375
transcript.pyannote[2738].end 15007.79534375
transcript.pyannote[2739].speaker SPEAKER_27
transcript.pyannote[2739].start 15007.33971875
transcript.pyannote[2739].end 15016.11471875
transcript.pyannote[2740].speaker SPEAKER_02
transcript.pyannote[2740].start 15010.44471875
transcript.pyannote[2740].end 15011.06909375
transcript.pyannote[2741].speaker SPEAKER_10
transcript.pyannote[2741].start 15011.06909375
transcript.pyannote[2741].end 15011.08596875
transcript.pyannote[2742].speaker SPEAKER_10
transcript.pyannote[2742].start 15014.46096875
transcript.pyannote[2742].end 15017.76846875
transcript.pyannote[2743].speaker SPEAKER_27
transcript.pyannote[2743].start 15017.32971875
transcript.pyannote[2743].end 15018.88221875
transcript.pyannote[2744].speaker SPEAKER_10
transcript.pyannote[2744].start 15019.30409375
transcript.pyannote[2744].end 15021.44721875
transcript.pyannote[2745].speaker SPEAKER_27
transcript.pyannote[2745].start 15021.56534375
transcript.pyannote[2745].end 15025.75034375
transcript.pyannote[2746].speaker SPEAKER_10
transcript.pyannote[2746].start 15025.07534375
transcript.pyannote[2746].end 15026.83034375
transcript.pyannote[2747].speaker SPEAKER_27
transcript.pyannote[2747].start 15026.67846875
transcript.pyannote[2747].end 15035.21721875
transcript.pyannote[2748].speaker SPEAKER_10
transcript.pyannote[2748].start 15035.21721875
transcript.pyannote[2748].end 15059.51721875
transcript.pyannote[2749].speaker SPEAKER_10
transcript.pyannote[2749].start 15059.78721875
transcript.pyannote[2749].end 15069.43971875
transcript.pyannote[2750].speaker SPEAKER_10
transcript.pyannote[2750].start 15069.67596875
transcript.pyannote[2750].end 15074.14784375
transcript.pyannote[2751].speaker SPEAKER_10
transcript.pyannote[2751].start 15074.31659375
transcript.pyannote[2751].end 15084.47534375
transcript.pyannote[2752].speaker SPEAKER_10
transcript.pyannote[2752].start 15084.96471875
transcript.pyannote[2752].end 15095.08971875
transcript.pyannote[2753].speaker SPEAKER_10
transcript.pyannote[2753].start 15095.22471875
transcript.pyannote[2753].end 15096.20346875
transcript.pyannote[2754].speaker SPEAKER_10
transcript.pyannote[2754].start 15096.37221875
transcript.pyannote[2754].end 15101.78909375
transcript.pyannote[2755].speaker SPEAKER_02
transcript.pyannote[2755].start 15101.63721875
transcript.pyannote[2755].end 15101.73846875
transcript.pyannote[2756].speaker SPEAKER_02
transcript.pyannote[2756].start 15101.78909375
transcript.pyannote[2756].end 15101.80596875
transcript.pyannote[2757].speaker SPEAKER_10
transcript.pyannote[2757].start 15101.80596875
transcript.pyannote[2757].end 15107.57721875
transcript.pyannote[2758].speaker SPEAKER_02
transcript.pyannote[2758].start 15101.83971875
transcript.pyannote[2758].end 15101.87346875
transcript.pyannote[2759].speaker SPEAKER_10
transcript.pyannote[2759].start 15107.81346875
transcript.pyannote[2759].end 15109.77096875
transcript.pyannote[2760].speaker SPEAKER_02
transcript.pyannote[2760].start 15109.90596875
transcript.pyannote[2760].end 15110.05784375
transcript.pyannote[2761].speaker SPEAKER_02
transcript.pyannote[2761].start 15110.12534375
transcript.pyannote[2761].end 15110.17596875
transcript.pyannote[2762].speaker SPEAKER_10
transcript.pyannote[2762].start 15110.26034375
transcript.pyannote[2762].end 15111.86346875
transcript.pyannote[2763].speaker SPEAKER_27
transcript.pyannote[2763].start 15112.38659375
transcript.pyannote[2763].end 15116.13284375
transcript.pyannote[2764].speaker SPEAKER_27
transcript.pyannote[2764].start 15116.26784375
transcript.pyannote[2764].end 15118.25909375
transcript.pyannote[2765].speaker SPEAKER_27
transcript.pyannote[2765].start 15118.41096875
transcript.pyannote[2765].end 15119.86221875
transcript.pyannote[2766].speaker SPEAKER_27
transcript.pyannote[2766].start 15120.35159375
transcript.pyannote[2766].end 15122.89971875
transcript.pyannote[2767].speaker SPEAKER_27
transcript.pyannote[2767].start 15123.30471875
transcript.pyannote[2767].end 15129.41346875
transcript.pyannote[2768].speaker SPEAKER_10
transcript.pyannote[2768].start 15128.36721875
transcript.pyannote[2768].end 15132.68721875
transcript.pyannote[2769].speaker SPEAKER_27
transcript.pyannote[2769].start 15130.84784375
transcript.pyannote[2769].end 15138.05346875
transcript.pyannote[2770].speaker SPEAKER_27
transcript.pyannote[2770].start 15138.17159375
transcript.pyannote[2770].end 15145.54596875
transcript.pyannote[2771].speaker SPEAKER_27
transcript.pyannote[2771].start 15145.73159375
transcript.pyannote[2771].end 15155.02971875
transcript.pyannote[2772].speaker SPEAKER_27
transcript.pyannote[2772].start 15155.45159375
transcript.pyannote[2772].end 15160.39596875
transcript.pyannote[2773].speaker SPEAKER_27
transcript.pyannote[2773].start 15160.66596875
transcript.pyannote[2773].end 15161.20596875
transcript.pyannote[2774].speaker SPEAKER_27
transcript.pyannote[2774].start 15161.59409375
transcript.pyannote[2774].end 15162.20159375
transcript.pyannote[2775].speaker SPEAKER_27
transcript.pyannote[2775].start 15162.84284375
transcript.pyannote[2775].end 15163.21409375
transcript.pyannote[2776].speaker SPEAKER_27
transcript.pyannote[2776].start 15163.61909375
transcript.pyannote[2776].end 15171.33096875
transcript.pyannote[2777].speaker SPEAKER_10
transcript.pyannote[2777].start 15167.39909375
transcript.pyannote[2777].end 15168.37784375
transcript.pyannote[2778].speaker SPEAKER_10
transcript.pyannote[2778].start 15168.68159375
transcript.pyannote[2778].end 15168.93471875
transcript.pyannote[2779].speaker SPEAKER_10
transcript.pyannote[2779].start 15171.24659375
transcript.pyannote[2779].end 15171.29721875
transcript.pyannote[2780].speaker SPEAKER_10
transcript.pyannote[2780].start 15171.33096875
transcript.pyannote[2780].end 15172.76534375
transcript.pyannote[2781].speaker SPEAKER_27
transcript.pyannote[2781].start 15172.57971875
transcript.pyannote[2781].end 15179.98784375
transcript.pyannote[2782].speaker SPEAKER_10
transcript.pyannote[2782].start 15177.84471875
transcript.pyannote[2782].end 15182.40096875
transcript.pyannote[2783].speaker SPEAKER_27
transcript.pyannote[2783].start 15183.09284375
transcript.pyannote[2783].end 15186.09659375
transcript.pyannote[2784].speaker SPEAKER_10
transcript.pyannote[2784].start 15185.92784375
transcript.pyannote[2784].end 15193.15034375
transcript.pyannote[2785].speaker SPEAKER_10
transcript.pyannote[2785].start 15193.75784375
transcript.pyannote[2785].end 15199.71471875
transcript.pyannote[2786].speaker SPEAKER_10
transcript.pyannote[2786].start 15200.06909375
transcript.pyannote[2786].end 15217.02846875
transcript.pyannote[2787].speaker SPEAKER_10
transcript.pyannote[2787].start 15217.28159375
transcript.pyannote[2787].end 15228.01409375
transcript.pyannote[2788].speaker SPEAKER_10
transcript.pyannote[2788].start 15228.41909375
transcript.pyannote[2788].end 15232.68846875
transcript.pyannote[2789].speaker SPEAKER_10
transcript.pyannote[2789].start 15233.02596875
transcript.pyannote[2789].end 15244.29846875
transcript.pyannote[2790].speaker SPEAKER_10
transcript.pyannote[2790].start 15244.70346875
transcript.pyannote[2790].end 15266.13471875
transcript.pyannote[2791].speaker SPEAKER_10
transcript.pyannote[2791].start 15266.60721875
transcript.pyannote[2791].end 15271.85534375
transcript.pyannote[2792].speaker SPEAKER_10
transcript.pyannote[2792].start 15272.19284375
transcript.pyannote[2792].end 15276.83346875
transcript.pyannote[2793].speaker SPEAKER_10
transcript.pyannote[2793].start 15277.57596875
transcript.pyannote[2793].end 15290.58659375
transcript.pyannote[2794].speaker SPEAKER_28
transcript.pyannote[2794].start 15282.03096875
transcript.pyannote[2794].end 15282.06471875
transcript.pyannote[2795].speaker SPEAKER_10
transcript.pyannote[2795].start 15290.92409375
transcript.pyannote[2795].end 15305.11596875
transcript.pyannote[2796].speaker SPEAKER_02
transcript.pyannote[2796].start 15292.52721875
transcript.pyannote[2796].end 15292.81409375
transcript.pyannote[2797].speaker SPEAKER_10
transcript.pyannote[2797].start 15305.60534375
transcript.pyannote[2797].end 15308.32221875
transcript.pyannote[2798].speaker SPEAKER_02
transcript.pyannote[2798].start 15308.42346875
transcript.pyannote[2798].end 15308.64284375
transcript.pyannote[2799].speaker SPEAKER_02
transcript.pyannote[2799].start 15308.71034375
transcript.pyannote[2799].end 15308.74409375
transcript.pyannote[2800].speaker SPEAKER_10
transcript.pyannote[2800].start 15308.74409375
transcript.pyannote[2800].end 15310.16159375
transcript.pyannote[2801].speaker SPEAKER_10
transcript.pyannote[2801].start 15310.19534375
transcript.pyannote[2801].end 15332.13284375
transcript.pyannote[2802].speaker SPEAKER_27
transcript.pyannote[2802].start 15332.13284375
transcript.pyannote[2802].end 15333.71909375
transcript.pyannote[2803].speaker SPEAKER_10
transcript.pyannote[2803].start 15332.82471875
transcript.pyannote[2803].end 15335.44034375
transcript.pyannote[2804].speaker SPEAKER_27
transcript.pyannote[2804].start 15334.42784375
transcript.pyannote[2804].end 15337.09409375
transcript.pyannote[2805].speaker SPEAKER_03
transcript.pyannote[2805].start 15337.09409375
transcript.pyannote[2805].end 15337.93784375
transcript.pyannote[2806].speaker SPEAKER_27
transcript.pyannote[2806].start 15337.11096875
transcript.pyannote[2806].end 15337.16159375
transcript.pyannote[2807].speaker SPEAKER_10
transcript.pyannote[2807].start 15337.16159375
transcript.pyannote[2807].end 15337.85346875
transcript.pyannote[2808].speaker SPEAKER_10
transcript.pyannote[2808].start 15337.93784375
transcript.pyannote[2808].end 15338.03909375
transcript.pyannote[2809].speaker SPEAKER_03
transcript.pyannote[2809].start 15338.03909375
transcript.pyannote[2809].end 15338.61284375
transcript.pyannote[2810].speaker SPEAKER_10
transcript.pyannote[2810].start 15338.61284375
transcript.pyannote[2810].end 15338.64659375
transcript.pyannote[2811].speaker SPEAKER_03
transcript.pyannote[2811].start 15340.23284375
transcript.pyannote[2811].end 15343.84409375
transcript.pyannote[2812].speaker SPEAKER_08
transcript.pyannote[2812].start 15353.66534375
transcript.pyannote[2812].end 15357.02346875
transcript.pyannote[2813].speaker SPEAKER_08
transcript.pyannote[2813].start 15357.79971875
transcript.pyannote[2813].end 15357.91784375
transcript.pyannote[2814].speaker SPEAKER_08
transcript.pyannote[2814].start 15358.67721875
transcript.pyannote[2814].end 15363.40221875
transcript.pyannote[2815].speaker SPEAKER_27
transcript.pyannote[2815].start 15360.19596875
transcript.pyannote[2815].end 15360.90471875
transcript.pyannote[2816].speaker SPEAKER_08
transcript.pyannote[2816].start 15365.34284375
transcript.pyannote[2816].end 15365.91659375
transcript.pyannote[2817].speaker SPEAKER_08
transcript.pyannote[2817].start 15368.97096875
transcript.pyannote[2817].end 15369.54471875
transcript.pyannote[2818].speaker SPEAKER_08
transcript.pyannote[2818].start 15371.92409375
transcript.pyannote[2818].end 15373.47659375
transcript.pyannote[2819].speaker SPEAKER_08
transcript.pyannote[2819].start 15374.33721875
transcript.pyannote[2819].end 15374.69159375
transcript.pyannote[2820].speaker SPEAKER_08
transcript.pyannote[2820].start 15375.63659375
transcript.pyannote[2820].end 15376.12596875
transcript.pyannote[2821].speaker SPEAKER_08
transcript.pyannote[2821].start 15379.21409375
transcript.pyannote[2821].end 15396.25784375
transcript.pyannote[2822].speaker SPEAKER_08
transcript.pyannote[2822].start 15396.74721875
transcript.pyannote[2822].end 15398.70471875
transcript.pyannote[2823].speaker SPEAKER_08
transcript.pyannote[2823].start 15399.07596875
transcript.pyannote[2823].end 15431.77971875
transcript.pyannote[2824].speaker SPEAKER_08
transcript.pyannote[2824].start 15432.52221875
transcript.pyannote[2824].end 15434.66534375
transcript.pyannote[2825].speaker SPEAKER_08
transcript.pyannote[2825].start 15435.32346875
transcript.pyannote[2825].end 15452.04659375
transcript.pyannote[2826].speaker SPEAKER_08
transcript.pyannote[2826].start 15452.21534375
transcript.pyannote[2826].end 15457.22721875
transcript.pyannote[2827].speaker SPEAKER_08
transcript.pyannote[2827].start 15457.95284375
transcript.pyannote[2827].end 15464.07846875
transcript.pyannote[2828].speaker SPEAKER_08
transcript.pyannote[2828].start 15464.75346875
transcript.pyannote[2828].end 15471.23346875
transcript.pyannote[2829].speaker SPEAKER_08
transcript.pyannote[2829].start 15472.49909375
transcript.pyannote[2829].end 15480.09284375
transcript.pyannote[2830].speaker SPEAKER_08
transcript.pyannote[2830].start 15480.68346875
transcript.pyannote[2830].end 15487.02846875
transcript.pyannote[2831].speaker SPEAKER_08
transcript.pyannote[2831].start 15487.46721875
transcript.pyannote[2831].end 15504.34221875
transcript.pyannote[2832].speaker SPEAKER_08
transcript.pyannote[2832].start 15505.16909375
transcript.pyannote[2832].end 15510.65346875
transcript.pyannote[2833].speaker SPEAKER_08
transcript.pyannote[2833].start 15511.34534375
transcript.pyannote[2833].end 15526.33034375
transcript.pyannote[2834].speaker SPEAKER_27
transcript.pyannote[2834].start 15530.16096875
transcript.pyannote[2834].end 15538.63221875
transcript.pyannote[2835].speaker SPEAKER_00
transcript.pyannote[2835].start 15534.41346875
transcript.pyannote[2835].end 15534.56534375
transcript.pyannote[2836].speaker SPEAKER_08
transcript.pyannote[2836].start 15534.56534375
transcript.pyannote[2836].end 15534.59909375
transcript.pyannote[2837].speaker SPEAKER_00
transcript.pyannote[2837].start 15534.59909375
transcript.pyannote[2837].end 15534.64971875
transcript.pyannote[2838].speaker SPEAKER_08
transcript.pyannote[2838].start 15534.64971875
transcript.pyannote[2838].end 15534.66659375
transcript.pyannote[2839].speaker SPEAKER_00
transcript.pyannote[2839].start 15534.66659375
transcript.pyannote[2839].end 15534.70034375
transcript.pyannote[2840].speaker SPEAKER_27
transcript.pyannote[2840].start 15538.91909375
transcript.pyannote[2840].end 15540.10034375
transcript.pyannote[2841].speaker SPEAKER_27
transcript.pyannote[2841].start 15540.31971875
transcript.pyannote[2841].end 15543.71159375
transcript.pyannote[2842].speaker SPEAKER_27
transcript.pyannote[2842].start 15544.06596875
transcript.pyannote[2842].end 15552.08159375
transcript.pyannote[2843].speaker SPEAKER_08
transcript.pyannote[2843].start 15551.28846875
transcript.pyannote[2843].end 15581.62971875
transcript.pyannote[2844].speaker SPEAKER_08
transcript.pyannote[2844].start 15582.49034375
transcript.pyannote[2844].end 15604.66409375
transcript.pyannote[2845].speaker SPEAKER_27
transcript.pyannote[2845].start 15603.11159375
transcript.pyannote[2845].end 15603.38159375
transcript.pyannote[2846].speaker SPEAKER_27
transcript.pyannote[2846].start 15604.07346875
transcript.pyannote[2846].end 15619.80096875
transcript.pyannote[2847].speaker SPEAKER_00
transcript.pyannote[2847].start 15612.88221875
transcript.pyannote[2847].end 15613.33784375
transcript.pyannote[2848].speaker SPEAKER_00
transcript.pyannote[2848].start 15617.03346875
transcript.pyannote[2848].end 15617.45534375
transcript.pyannote[2849].speaker SPEAKER_27
transcript.pyannote[2849].start 15620.34096875
transcript.pyannote[2849].end 15622.66971875
transcript.pyannote[2850].speaker SPEAKER_27
transcript.pyannote[2850].start 15622.99034375
transcript.pyannote[2850].end 15625.06596875
transcript.pyannote[2851].speaker SPEAKER_27
transcript.pyannote[2851].start 15625.62284375
transcript.pyannote[2851].end 15631.49534375
transcript.pyannote[2852].speaker SPEAKER_08
transcript.pyannote[2852].start 15626.63534375
transcript.pyannote[2852].end 15627.49596875
transcript.pyannote[2853].speaker SPEAKER_08
transcript.pyannote[2853].start 15630.29721875
transcript.pyannote[2853].end 15630.88784375
transcript.pyannote[2854].speaker SPEAKER_08
transcript.pyannote[2854].start 15631.46159375
transcript.pyannote[2854].end 15655.67721875
transcript.pyannote[2855].speaker SPEAKER_27
transcript.pyannote[2855].start 15656.26784375
transcript.pyannote[2855].end 15678.52596875
transcript.pyannote[2856].speaker SPEAKER_08
transcript.pyannote[2856].start 15667.42221875
transcript.pyannote[2856].end 15667.99596875
transcript.pyannote[2857].speaker SPEAKER_08
transcript.pyannote[2857].start 15668.21534375
transcript.pyannote[2857].end 15668.80596875
transcript.pyannote[2858].speaker SPEAKER_08
transcript.pyannote[2858].start 15678.52596875
transcript.pyannote[2858].end 15687.36846875
transcript.pyannote[2859].speaker SPEAKER_08
transcript.pyannote[2859].start 15688.04346875
transcript.pyannote[2859].end 15689.84909375
transcript.pyannote[2860].speaker SPEAKER_08
transcript.pyannote[2860].start 15690.62534375
transcript.pyannote[2860].end 15691.70534375
transcript.pyannote[2861].speaker SPEAKER_27
transcript.pyannote[2861].start 15692.80221875
transcript.pyannote[2861].end 15699.95721875
transcript.pyannote[2862].speaker SPEAKER_03
transcript.pyannote[2862].start 15699.26534375
transcript.pyannote[2862].end 15700.51409375
transcript.pyannote[2863].speaker SPEAKER_03
transcript.pyannote[2863].start 15701.22284375
transcript.pyannote[2863].end 15705.69471875
transcript.pyannote[2864].speaker SPEAKER_14
transcript.pyannote[2864].start 15722.77221875
transcript.pyannote[2864].end 15723.53159375
transcript.pyannote[2865].speaker SPEAKER_03
transcript.pyannote[2865].start 15723.98721875
transcript.pyannote[2865].end 15725.18534375
transcript.pyannote[2866].speaker SPEAKER_03
transcript.pyannote[2866].start 15728.84721875
transcript.pyannote[2866].end 15729.35346875
transcript.pyannote[2867].speaker SPEAKER_27
transcript.pyannote[2867].start 15729.35346875
transcript.pyannote[2867].end 15729.38721875
transcript.pyannote[2868].speaker SPEAKER_14
transcript.pyannote[2868].start 15730.70346875
transcript.pyannote[2868].end 15742.61721875
transcript.pyannote[2869].speaker SPEAKER_14
transcript.pyannote[2869].start 15742.98846875
transcript.pyannote[2869].end 15752.77596875
transcript.pyannote[2870].speaker SPEAKER_14
transcript.pyannote[2870].start 15753.01221875
transcript.pyannote[2870].end 15755.47596875
transcript.pyannote[2871].speaker SPEAKER_14
transcript.pyannote[2871].start 15755.93159375
transcript.pyannote[2871].end 15756.91034375
transcript.pyannote[2872].speaker SPEAKER_14
transcript.pyannote[2872].start 15757.51784375
transcript.pyannote[2872].end 15762.32721875
transcript.pyannote[2873].speaker SPEAKER_14
transcript.pyannote[2873].start 15763.01909375
transcript.pyannote[2873].end 15768.30096875
transcript.pyannote[2874].speaker SPEAKER_14
transcript.pyannote[2874].start 15768.82409375
transcript.pyannote[2874].end 15772.03034375
transcript.pyannote[2875].speaker SPEAKER_14
transcript.pyannote[2875].start 15772.48596875
transcript.pyannote[2875].end 15774.67971875
transcript.pyannote[2876].speaker SPEAKER_14
transcript.pyannote[2876].start 15775.18596875
transcript.pyannote[2876].end 15782.13846875
transcript.pyannote[2877].speaker SPEAKER_27
transcript.pyannote[2877].start 15783.10034375
transcript.pyannote[2877].end 15785.86784375
transcript.pyannote[2878].speaker SPEAKER_27
transcript.pyannote[2878].start 15786.23909375
transcript.pyannote[2878].end 15787.25159375
transcript.pyannote[2879].speaker SPEAKER_02
transcript.pyannote[2879].start 15787.25159375
transcript.pyannote[2879].end 15787.55534375
transcript.pyannote[2880].speaker SPEAKER_27
transcript.pyannote[2880].start 15787.55534375
transcript.pyannote[2880].end 15789.20909375
transcript.pyannote[2881].speaker SPEAKER_27
transcript.pyannote[2881].start 15789.36096875
transcript.pyannote[2881].end 15790.98096875
transcript.pyannote[2882].speaker SPEAKER_27
transcript.pyannote[2882].start 15791.36909375
transcript.pyannote[2882].end 15793.51221875
transcript.pyannote[2883].speaker SPEAKER_27
transcript.pyannote[2883].start 15793.57971875
transcript.pyannote[2883].end 15795.60471875
transcript.pyannote[2884].speaker SPEAKER_27
transcript.pyannote[2884].start 15796.07721875
transcript.pyannote[2884].end 15797.86596875
transcript.pyannote[2885].speaker SPEAKER_27
transcript.pyannote[2885].start 15798.15284375
transcript.pyannote[2885].end 15803.77221875
transcript.pyannote[2886].speaker SPEAKER_14
transcript.pyannote[2886].start 15803.14784375
transcript.pyannote[2886].end 15818.08221875
transcript.pyannote[2887].speaker SPEAKER_27
transcript.pyannote[2887].start 15803.90721875
transcript.pyannote[2887].end 15804.78471875
transcript.pyannote[2888].speaker SPEAKER_25
transcript.pyannote[2888].start 15813.05346875
transcript.pyannote[2888].end 15814.13346875
transcript.pyannote[2889].speaker SPEAKER_25
transcript.pyannote[2889].start 15818.08221875
transcript.pyannote[2889].end 15818.50409375
transcript.pyannote[2890].speaker SPEAKER_14
transcript.pyannote[2890].start 15818.72346875
transcript.pyannote[2890].end 15819.26346875
transcript.pyannote[2891].speaker SPEAKER_14
transcript.pyannote[2891].start 15819.60096875
transcript.pyannote[2891].end 15823.80284375
transcript.pyannote[2892].speaker SPEAKER_14
transcript.pyannote[2892].start 15823.87034375
transcript.pyannote[2892].end 15843.02346875
transcript.pyannote[2893].speaker SPEAKER_14
transcript.pyannote[2893].start 15844.10346875
transcript.pyannote[2893].end 15860.23596875
transcript.pyannote[2894].speaker SPEAKER_14
transcript.pyannote[2894].start 15860.74221875
transcript.pyannote[2894].end 15863.94846875
transcript.pyannote[2895].speaker SPEAKER_14
transcript.pyannote[2895].start 15864.20159375
transcript.pyannote[2895].end 15892.51784375
transcript.pyannote[2896].speaker SPEAKER_14
transcript.pyannote[2896].start 15892.87221875
transcript.pyannote[2896].end 15895.47096875
transcript.pyannote[2897].speaker SPEAKER_14
transcript.pyannote[2897].start 15895.84221875
transcript.pyannote[2897].end 15901.02284375
transcript.pyannote[2898].speaker SPEAKER_14
transcript.pyannote[2898].start 15901.64721875
transcript.pyannote[2898].end 15904.12784375
transcript.pyannote[2899].speaker SPEAKER_14
transcript.pyannote[2899].start 15904.21221875
transcript.pyannote[2899].end 15916.46346875
transcript.pyannote[2900].speaker SPEAKER_27
transcript.pyannote[2900].start 15917.42534375
transcript.pyannote[2900].end 15917.50971875
transcript.pyannote[2901].speaker SPEAKER_27
transcript.pyannote[2901].start 15917.99909375
transcript.pyannote[2901].end 15932.49471875
transcript.pyannote[2902].speaker SPEAKER_27
transcript.pyannote[2902].start 15932.66346875
transcript.pyannote[2902].end 15940.76346875
transcript.pyannote[2903].speaker SPEAKER_27
transcript.pyannote[2903].start 15940.96596875
transcript.pyannote[2903].end 15946.83846875
transcript.pyannote[2904].speaker SPEAKER_27
transcript.pyannote[2904].start 15947.41221875
transcript.pyannote[2904].end 15951.02346875
transcript.pyannote[2905].speaker SPEAKER_14
transcript.pyannote[2905].start 15949.69034375
transcript.pyannote[2905].end 15952.42409375
transcript.pyannote[2906].speaker SPEAKER_14
transcript.pyannote[2906].start 15953.33534375
transcript.pyannote[2906].end 15964.05096875
transcript.pyannote[2907].speaker SPEAKER_27
transcript.pyannote[2907].start 15963.10596875
transcript.pyannote[2907].end 15965.78909375
transcript.pyannote[2908].speaker SPEAKER_14
transcript.pyannote[2908].start 15964.89471875
transcript.pyannote[2908].end 15965.31659375
transcript.pyannote[2909].speaker SPEAKER_14
transcript.pyannote[2909].start 15965.55284375
transcript.pyannote[2909].end 15980.03159375
transcript.pyannote[2910].speaker SPEAKER_14
transcript.pyannote[2910].start 15980.53784375
transcript.pyannote[2910].end 15986.34284375
transcript.pyannote[2911].speaker SPEAKER_27
transcript.pyannote[2911].start 15987.72659375
transcript.pyannote[2911].end 15989.51534375
transcript.pyannote[2912].speaker SPEAKER_27
transcript.pyannote[2912].start 15990.00471875
transcript.pyannote[2912].end 15993.26159375
transcript.pyannote[2913].speaker SPEAKER_14
transcript.pyannote[2913].start 15993.26159375
transcript.pyannote[2913].end 15993.44721875
transcript.pyannote[2914].speaker SPEAKER_27
transcript.pyannote[2914].start 15993.44721875
transcript.pyannote[2914].end 15993.51471875
transcript.pyannote[2915].speaker SPEAKER_14
transcript.pyannote[2915].start 15993.51471875
transcript.pyannote[2915].end 15993.54846875
transcript.pyannote[2916].speaker SPEAKER_27
transcript.pyannote[2916].start 15993.54846875
transcript.pyannote[2916].end 15994.03784375
transcript.pyannote[2917].speaker SPEAKER_14
transcript.pyannote[2917].start 15993.83534375
transcript.pyannote[2917].end 16002.44159375
transcript.pyannote[2918].speaker SPEAKER_27
transcript.pyannote[2918].start 16004.80409375
transcript.pyannote[2918].end 16005.19221875
transcript.pyannote[2919].speaker SPEAKER_27
transcript.pyannote[2919].start 16006.94721875
transcript.pyannote[2919].end 16014.82784375
transcript.pyannote[2920].speaker SPEAKER_00
transcript.pyannote[2920].start 16012.61721875
transcript.pyannote[2920].end 16012.70159375
transcript.pyannote[2921].speaker SPEAKER_14
transcript.pyannote[2921].start 16012.70159375
transcript.pyannote[2921].end 16013.96721875
transcript.pyannote[2922].speaker SPEAKER_00
transcript.pyannote[2922].start 16013.96721875
transcript.pyannote[2922].end 16014.00096875
transcript.pyannote[2923].speaker SPEAKER_14
transcript.pyannote[2923].start 16014.00096875
transcript.pyannote[2923].end 16014.08534375
transcript.pyannote[2924].speaker SPEAKER_00
transcript.pyannote[2924].start 16014.08534375
transcript.pyannote[2924].end 16014.15284375
transcript.pyannote[2925].speaker SPEAKER_27
transcript.pyannote[2925].start 16015.55346875
transcript.pyannote[2925].end 16048.71284375
transcript.pyannote[2926].speaker SPEAKER_00
transcript.pyannote[2926].start 16020.51471875
transcript.pyannote[2926].end 16021.03784375
transcript.pyannote[2927].speaker SPEAKER_28
transcript.pyannote[2927].start 16021.03784375
transcript.pyannote[2927].end 16022.86034375
transcript.pyannote[2928].speaker SPEAKER_28
transcript.pyannote[2928].start 16024.59846875
transcript.pyannote[2928].end 16025.00346875
transcript.pyannote[2929].speaker SPEAKER_14
transcript.pyannote[2929].start 16048.20659375
transcript.pyannote[2929].end 16056.94784375
transcript.pyannote[2930].speaker SPEAKER_27
transcript.pyannote[2930].start 16055.93534375
transcript.pyannote[2930].end 16061.11596875
transcript.pyannote[2931].speaker SPEAKER_27
transcript.pyannote[2931].start 16061.35221875
transcript.pyannote[2931].end 16068.03471875
transcript.pyannote[2932].speaker SPEAKER_14
transcript.pyannote[2932].start 16068.15284375
transcript.pyannote[2932].end 16073.58659375
transcript.pyannote[2933].speaker SPEAKER_03
transcript.pyannote[2933].start 16075.40909375
transcript.pyannote[2933].end 16077.38346875
transcript.pyannote[2934].speaker SPEAKER_03
transcript.pyannote[2934].start 16077.48471875
transcript.pyannote[2934].end 16078.24409375
transcript.pyannote[2935].speaker SPEAKER_03
transcript.pyannote[2935].start 16078.53096875
transcript.pyannote[2935].end 16080.01596875
transcript.pyannote[2936].speaker SPEAKER_03
transcript.pyannote[2936].start 16080.60659375
transcript.pyannote[2936].end 16082.78346875
transcript.pyannote[2937].speaker SPEAKER_03
transcript.pyannote[2937].start 16083.03659375
transcript.pyannote[2937].end 16084.69034375
transcript.pyannote[2938].speaker SPEAKER_03
transcript.pyannote[2938].start 16085.19659375
transcript.pyannote[2938].end 16087.01909375
transcript.pyannote[2939].speaker SPEAKER_03
transcript.pyannote[2939].start 16087.33971875
transcript.pyannote[2939].end 16088.57159375
transcript.pyannote[2940].speaker SPEAKER_03
transcript.pyannote[2940].start 16088.94284375
transcript.pyannote[2940].end 16090.54596875
transcript.pyannote[2941].speaker SPEAKER_03
transcript.pyannote[2941].start 16090.95096875
transcript.pyannote[2941].end 16092.80721875
transcript.pyannote[2942].speaker SPEAKER_03
transcript.pyannote[2942].start 16093.07721875
transcript.pyannote[2942].end 16094.32596875
transcript.pyannote[2943].speaker SPEAKER_03
transcript.pyannote[2943].start 16094.47784375
transcript.pyannote[2943].end 16096.14846875
transcript.pyannote[2944].speaker SPEAKER_03
transcript.pyannote[2944].start 16096.33409375
transcript.pyannote[2944].end 16098.51096875
transcript.pyannote[2945].speaker SPEAKER_19
transcript.pyannote[2945].start 16110.84659375
transcript.pyannote[2945].end 16114.81221875
transcript.pyannote[2946].speaker SPEAKER_03
transcript.pyannote[2946].start 16114.93034375
transcript.pyannote[2946].end 16115.77409375
transcript.pyannote[2947].speaker SPEAKER_19
transcript.pyannote[2947].start 16117.76534375
transcript.pyannote[2947].end 16120.11096875
transcript.pyannote[2948].speaker SPEAKER_19
transcript.pyannote[2948].start 16120.43159375
transcript.pyannote[2948].end 16121.29221875
transcript.pyannote[2949].speaker SPEAKER_19
transcript.pyannote[2949].start 16121.71409375
transcript.pyannote[2949].end 16140.95159375
transcript.pyannote[2950].speaker SPEAKER_02
transcript.pyannote[2950].start 16125.47721875
transcript.pyannote[2950].end 16126.45596875
transcript.pyannote[2951].speaker SPEAKER_19
transcript.pyannote[2951].start 16141.33971875
transcript.pyannote[2951].end 16152.51096875
transcript.pyannote[2952].speaker SPEAKER_19
transcript.pyannote[2952].start 16152.64596875
transcript.pyannote[2952].end 16155.83534375
transcript.pyannote[2953].speaker SPEAKER_02
transcript.pyannote[2953].start 16155.83534375
transcript.pyannote[2953].end 16156.15596875
transcript.pyannote[2954].speaker SPEAKER_19
transcript.pyannote[2954].start 16156.15596875
transcript.pyannote[2954].end 16167.29346875
transcript.pyannote[2955].speaker SPEAKER_19
transcript.pyannote[2955].start 16168.25534375
transcript.pyannote[2955].end 16170.88784375
transcript.pyannote[2956].speaker SPEAKER_19
transcript.pyannote[2956].start 16171.19159375
transcript.pyannote[2956].end 16197.26346875
transcript.pyannote[2957].speaker SPEAKER_19
transcript.pyannote[2957].start 16197.78659375
transcript.pyannote[2957].end 16207.99596875
transcript.pyannote[2958].speaker SPEAKER_19
transcript.pyannote[2958].start 16208.41784375
transcript.pyannote[2958].end 16209.85221875
transcript.pyannote[2959].speaker SPEAKER_19
transcript.pyannote[2959].start 16210.25721875
transcript.pyannote[2959].end 16216.58534375
transcript.pyannote[2960].speaker SPEAKER_02
transcript.pyannote[2960].start 16216.58534375
transcript.pyannote[2960].end 16217.04096875
transcript.pyannote[2961].speaker SPEAKER_19
transcript.pyannote[2961].start 16217.12534375
transcript.pyannote[2961].end 16229.37659375
transcript.pyannote[2962].speaker SPEAKER_19
transcript.pyannote[2962].start 16230.22034375
transcript.pyannote[2962].end 16232.97096875
transcript.pyannote[2963].speaker SPEAKER_19
transcript.pyannote[2963].start 16233.73034375
transcript.pyannote[2963].end 16249.67721875
transcript.pyannote[2964].speaker SPEAKER_19
transcript.pyannote[2964].start 16250.01471875
transcript.pyannote[2964].end 16282.53284375
transcript.pyannote[2965].speaker SPEAKER_27
transcript.pyannote[2965].start 16282.83659375
transcript.pyannote[2965].end 16286.16096875
transcript.pyannote[2966].speaker SPEAKER_27
transcript.pyannote[2966].start 16287.40971875
transcript.pyannote[2966].end 16289.95784375
transcript.pyannote[2967].speaker SPEAKER_27
transcript.pyannote[2967].start 16290.12659375
transcript.pyannote[2967].end 16294.07534375
transcript.pyannote[2968].speaker SPEAKER_27
transcript.pyannote[2968].start 16294.36221875
transcript.pyannote[2968].end 16295.45909375
transcript.pyannote[2969].speaker SPEAKER_27
transcript.pyannote[2969].start 16295.71221875
transcript.pyannote[2969].end 16298.64846875
transcript.pyannote[2970].speaker SPEAKER_27
transcript.pyannote[2970].start 16298.85096875
transcript.pyannote[2970].end 16301.88846875
transcript.pyannote[2971].speaker SPEAKER_27
transcript.pyannote[2971].start 16302.15846875
transcript.pyannote[2971].end 16303.62659375
transcript.pyannote[2972].speaker SPEAKER_27
transcript.pyannote[2972].start 16303.96409375
transcript.pyannote[2972].end 16311.03471875
transcript.pyannote[2973].speaker SPEAKER_02
transcript.pyannote[2973].start 16305.33096875
transcript.pyannote[2973].end 16306.44471875
transcript.pyannote[2974].speaker SPEAKER_02
transcript.pyannote[2974].start 16307.05221875
transcript.pyannote[2974].end 16307.69346875
transcript.pyannote[2975].speaker SPEAKER_02
transcript.pyannote[2975].start 16308.16596875
transcript.pyannote[2975].end 16308.67221875
transcript.pyannote[2976].speaker SPEAKER_02
transcript.pyannote[2976].start 16310.32596875
transcript.pyannote[2976].end 16311.16971875
transcript.pyannote[2977].speaker SPEAKER_27
transcript.pyannote[2977].start 16311.28784375
transcript.pyannote[2977].end 16318.08846875
transcript.pyannote[2978].speaker SPEAKER_27
transcript.pyannote[2978].start 16318.89846875
transcript.pyannote[2978].end 16320.63659375
transcript.pyannote[2979].speaker SPEAKER_19
transcript.pyannote[2979].start 16320.63659375
transcript.pyannote[2979].end 16326.71159375
transcript.pyannote[2980].speaker SPEAKER_02
transcript.pyannote[2980].start 16326.69471875
transcript.pyannote[2980].end 16327.33596875
transcript.pyannote[2981].speaker SPEAKER_19
transcript.pyannote[2981].start 16327.16721875
transcript.pyannote[2981].end 16383.76596875
transcript.pyannote[2982].speaker SPEAKER_02
transcript.pyannote[2982].start 16327.47096875
transcript.pyannote[2982].end 16327.67346875
transcript.pyannote[2983].speaker SPEAKER_02
transcript.pyannote[2983].start 16327.92659375
transcript.pyannote[2983].end 16328.14596875
transcript.pyannote[2984].speaker SPEAKER_19
transcript.pyannote[2984].start 16384.17096875
transcript.pyannote[2984].end 16392.13596875
transcript.pyannote[2985].speaker SPEAKER_19
transcript.pyannote[2985].start 16392.69284375
transcript.pyannote[2985].end 16420.77284375
transcript.pyannote[2986].speaker SPEAKER_27
transcript.pyannote[2986].start 16421.11034375
transcript.pyannote[2986].end 16433.32784375
transcript.pyannote[2987].speaker SPEAKER_19
transcript.pyannote[2987].start 16421.75159375
transcript.pyannote[2987].end 16422.15659375
transcript.pyannote[2988].speaker SPEAKER_19
transcript.pyannote[2988].start 16423.59096875
transcript.pyannote[2988].end 16426.34159375
transcript.pyannote[2989].speaker SPEAKER_19
transcript.pyannote[2989].start 16432.58534375
transcript.pyannote[2989].end 16449.08909375
transcript.pyannote[2990].speaker SPEAKER_27
transcript.pyannote[2990].start 16433.49659375
transcript.pyannote[2990].end 16434.05346875
transcript.pyannote[2991].speaker SPEAKER_27
transcript.pyannote[2991].start 16448.95409375
transcript.pyannote[2991].end 16450.52346875
transcript.pyannote[2992].speaker SPEAKER_19
transcript.pyannote[2992].start 16449.74721875
transcript.pyannote[2992].end 16468.68096875
transcript.pyannote[2993].speaker SPEAKER_27
transcript.pyannote[2993].start 16450.89471875
transcript.pyannote[2993].end 16450.96221875
transcript.pyannote[2994].speaker SPEAKER_27
transcript.pyannote[2994].start 16452.12659375
transcript.pyannote[2994].end 16452.76784375
transcript.pyannote[2995].speaker SPEAKER_19
transcript.pyannote[2995].start 16469.23784375
transcript.pyannote[2995].end 16470.99284375
transcript.pyannote[2996].speaker SPEAKER_02
transcript.pyannote[2996].start 16470.99284375
transcript.pyannote[2996].end 16471.51596875
transcript.pyannote[2997].speaker SPEAKER_19
transcript.pyannote[2997].start 16471.88721875
transcript.pyannote[2997].end 16479.63284375
transcript.pyannote[2998].speaker SPEAKER_02
transcript.pyannote[2998].start 16473.74346875
transcript.pyannote[2998].end 16475.26221875
transcript.pyannote[2999].speaker SPEAKER_19
transcript.pyannote[2999].start 16479.80159375
transcript.pyannote[2999].end 16483.66596875
transcript.pyannote[3000].speaker SPEAKER_19
transcript.pyannote[3000].start 16484.08784375
transcript.pyannote[3000].end 16500.01784375
transcript.pyannote[3001].speaker SPEAKER_02
transcript.pyannote[3001].start 16485.23534375
transcript.pyannote[3001].end 16485.84284375
transcript.pyannote[3002].speaker SPEAKER_02
transcript.pyannote[3002].start 16490.21346875
transcript.pyannote[3002].end 16490.33159375
transcript.pyannote[3003].speaker SPEAKER_02
transcript.pyannote[3003].start 16490.41596875
transcript.pyannote[3003].end 16490.48346875
transcript.pyannote[3004].speaker SPEAKER_02
transcript.pyannote[3004].start 16494.01034375
transcript.pyannote[3004].end 16494.36471875
transcript.pyannote[3005].speaker SPEAKER_02
transcript.pyannote[3005].start 16499.98409375
transcript.pyannote[3005].end 16500.37221875
transcript.pyannote[3006].speaker SPEAKER_19
transcript.pyannote[3006].start 16500.49034375
transcript.pyannote[3006].end 16502.98784375
transcript.pyannote[3007].speaker SPEAKER_03
transcript.pyannote[3007].start 16502.22846875
transcript.pyannote[3007].end 16503.12284375
transcript.pyannote[3008].speaker SPEAKER_03
transcript.pyannote[3008].start 16504.50659375
transcript.pyannote[3008].end 16506.71721875
transcript.pyannote[3009].speaker SPEAKER_03
transcript.pyannote[3009].start 16506.90284375
transcript.pyannote[3009].end 16511.81346875
transcript.pyannote[3010].speaker SPEAKER_03
transcript.pyannote[3010].start 16512.13409375
transcript.pyannote[3010].end 16517.77034375
transcript.pyannote[3011].speaker SPEAKER_03
transcript.pyannote[3011].start 16518.15846875
transcript.pyannote[3011].end 16522.64721875
transcript.pyannote[3012].speaker SPEAKER_03
transcript.pyannote[3012].start 16522.93409375
transcript.pyannote[3012].end 16524.77346875
transcript.pyannote[3013].speaker SPEAKER_03
transcript.pyannote[3013].start 16525.02659375
transcript.pyannote[3013].end 16526.24159375
transcript.pyannote[3014].speaker SPEAKER_03
transcript.pyannote[3014].start 16526.44409375
transcript.pyannote[3014].end 16527.92909375
transcript.pyannote[3015].speaker SPEAKER_03
transcript.pyannote[3015].start 16528.23284375
transcript.pyannote[3015].end 16533.12659375
transcript.pyannote[3016].speaker SPEAKER_03
transcript.pyannote[3016].start 16533.48096875
transcript.pyannote[3016].end 16538.10471875
transcript.pyannote[3017].speaker SPEAKER_03
transcript.pyannote[3017].start 16538.39159375
transcript.pyannote[3017].end 16543.50471875
transcript.pyannote[3018].speaker SPEAKER_03
transcript.pyannote[3018].start 16543.89284375
transcript.pyannote[3018].end 16548.33096875
transcript.pyannote[3019].speaker SPEAKER_03
transcript.pyannote[3019].start 16548.68534375
transcript.pyannote[3019].end 16553.30909375
transcript.pyannote[3020].speaker SPEAKER_03
transcript.pyannote[3020].start 16553.64659375
transcript.pyannote[3020].end 16556.73471875
transcript.pyannote[3021].speaker SPEAKER_03
transcript.pyannote[3021].start 16556.93721875
transcript.pyannote[3021].end 16558.57409375
transcript.pyannote[3022].speaker SPEAKER_03
transcript.pyannote[3022].start 16558.79346875
transcript.pyannote[3022].end 16560.51471875
transcript.pyannote[3023].speaker SPEAKER_09
transcript.pyannote[3023].start 16567.41659375
transcript.pyannote[3023].end 16572.00659375
transcript.pyannote[3024].speaker SPEAKER_23
transcript.pyannote[3024].start 16576.41096875
transcript.pyannote[3024].end 16576.93409375
transcript.pyannote[3025].speaker SPEAKER_09
transcript.pyannote[3025].start 16577.13659375
transcript.pyannote[3025].end 16620.43784375
transcript.pyannote[3026].speaker SPEAKER_23
transcript.pyannote[3026].start 16620.96096875
transcript.pyannote[3026].end 16630.74846875
transcript.pyannote[3027].speaker SPEAKER_23
transcript.pyannote[3027].start 16631.37284375
transcript.pyannote[3027].end 16631.87909375
transcript.pyannote[3028].speaker SPEAKER_23
transcript.pyannote[3028].start 16632.33471875
transcript.pyannote[3028].end 16634.02221875
transcript.pyannote[3029].speaker SPEAKER_09
transcript.pyannote[3029].start 16634.96721875
transcript.pyannote[3029].end 16635.89534375
transcript.pyannote[3030].speaker SPEAKER_09
transcript.pyannote[3030].start 16636.36784375
transcript.pyannote[3030].end 16640.97471875
transcript.pyannote[3031].speaker SPEAKER_23
transcript.pyannote[3031].start 16641.29534375
transcript.pyannote[3031].end 16642.84784375
transcript.pyannote[3032].speaker SPEAKER_23
transcript.pyannote[3032].start 16642.88159375
transcript.pyannote[3032].end 16642.89846875
transcript.pyannote[3033].speaker SPEAKER_09
transcript.pyannote[3033].start 16642.89846875
transcript.pyannote[3033].end 16649.00721875
transcript.pyannote[3034].speaker SPEAKER_23
transcript.pyannote[3034].start 16649.61471875
transcript.pyannote[3034].end 16652.93909375
transcript.pyannote[3035].speaker SPEAKER_23
transcript.pyannote[3035].start 16653.41159375
transcript.pyannote[3035].end 16654.17096875
transcript.pyannote[3036].speaker SPEAKER_23
transcript.pyannote[3036].start 16655.09909375
transcript.pyannote[3036].end 16656.68534375
transcript.pyannote[3037].speaker SPEAKER_09
transcript.pyannote[3037].start 16655.13284375
transcript.pyannote[3037].end 16655.79096875
transcript.pyannote[3038].speaker SPEAKER_09
transcript.pyannote[3038].start 16656.16221875
transcript.pyannote[3038].end 16658.38971875
transcript.pyannote[3039].speaker SPEAKER_23
transcript.pyannote[3039].start 16656.80346875
transcript.pyannote[3039].end 16659.03096875
transcript.pyannote[3040].speaker SPEAKER_09
transcript.pyannote[3040].start 16659.36846875
transcript.pyannote[3040].end 16660.26284375
transcript.pyannote[3041].speaker SPEAKER_09
transcript.pyannote[3041].start 16660.73534375
transcript.pyannote[3041].end 16665.15659375
transcript.pyannote[3042].speaker SPEAKER_23
transcript.pyannote[3042].start 16665.15659375
transcript.pyannote[3042].end 16669.12221875
transcript.pyannote[3043].speaker SPEAKER_23
transcript.pyannote[3043].start 16669.44284375
transcript.pyannote[3043].end 16672.90221875
transcript.pyannote[3044].speaker SPEAKER_09
transcript.pyannote[3044].start 16671.36659375
transcript.pyannote[3044].end 16672.31159375
transcript.pyannote[3045].speaker SPEAKER_09
transcript.pyannote[3045].start 16672.90221875
transcript.pyannote[3045].end 16673.84721875
transcript.pyannote[3046].speaker SPEAKER_23
transcript.pyannote[3046].start 16673.96534375
transcript.pyannote[3046].end 16675.24784375
transcript.pyannote[3047].speaker SPEAKER_23
transcript.pyannote[3047].start 16675.34909375
transcript.pyannote[3047].end 16677.66096875
transcript.pyannote[3048].speaker SPEAKER_23
transcript.pyannote[3048].start 16678.53846875
transcript.pyannote[3048].end 16681.72784375
transcript.pyannote[3049].speaker SPEAKER_09
transcript.pyannote[3049].start 16681.93034375
transcript.pyannote[3049].end 16685.57534375
transcript.pyannote[3050].speaker SPEAKER_23
transcript.pyannote[3050].start 16684.79909375
transcript.pyannote[3050].end 16685.60909375
transcript.pyannote[3051].speaker SPEAKER_02
transcript.pyannote[3051].start 16685.60909375
transcript.pyannote[3051].end 16685.69346875
transcript.pyannote[3052].speaker SPEAKER_09
transcript.pyannote[3052].start 16686.45284375
transcript.pyannote[3052].end 16701.74159375
transcript.pyannote[3053].speaker SPEAKER_23
transcript.pyannote[3053].start 16702.34909375
transcript.pyannote[3053].end 16704.18846875
transcript.pyannote[3054].speaker SPEAKER_09
transcript.pyannote[3054].start 16705.06596875
transcript.pyannote[3054].end 16706.66909375
transcript.pyannote[3055].speaker SPEAKER_09
transcript.pyannote[3055].start 16706.77034375
transcript.pyannote[3055].end 16708.23846875
transcript.pyannote[3056].speaker SPEAKER_09
transcript.pyannote[3056].start 16708.35659375
transcript.pyannote[3056].end 16722.61596875
transcript.pyannote[3057].speaker SPEAKER_09
transcript.pyannote[3057].start 16722.83534375
transcript.pyannote[3057].end 16735.98096875
transcript.pyannote[3058].speaker SPEAKER_09
transcript.pyannote[3058].start 16736.33534375
transcript.pyannote[3058].end 16740.01409375
transcript.pyannote[3059].speaker SPEAKER_09
transcript.pyannote[3059].start 16740.80721875
transcript.pyannote[3059].end 16762.57596875
transcript.pyannote[3060].speaker SPEAKER_09
transcript.pyannote[3060].start 16763.03159375
transcript.pyannote[3060].end 16770.45659375
transcript.pyannote[3061].speaker SPEAKER_09
transcript.pyannote[3061].start 16770.54096875
transcript.pyannote[3061].end 16773.71346875
transcript.pyannote[3062].speaker SPEAKER_23
transcript.pyannote[3062].start 16775.18159375
transcript.pyannote[3062].end 16777.99971875
transcript.pyannote[3063].speaker SPEAKER_09
transcript.pyannote[3063].start 16778.53971875
transcript.pyannote[3063].end 16790.16659375
transcript.pyannote[3064].speaker SPEAKER_02
transcript.pyannote[3064].start 16790.16659375
transcript.pyannote[3064].end 16790.35221875
transcript.pyannote[3065].speaker SPEAKER_09
transcript.pyannote[3065].start 16790.90909375
transcript.pyannote[3065].end 16792.63034375
transcript.pyannote[3066].speaker SPEAKER_09
transcript.pyannote[3066].start 16793.65971875
transcript.pyannote[3066].end 16802.58659375
transcript.pyannote[3067].speaker SPEAKER_09
transcript.pyannote[3067].start 16802.97471875
transcript.pyannote[3067].end 16806.65346875
transcript.pyannote[3068].speaker SPEAKER_09
transcript.pyannote[3068].start 16811.66534375
transcript.pyannote[3068].end 16826.19471875
transcript.pyannote[3069].speaker SPEAKER_09
transcript.pyannote[3069].start 16827.25784375
transcript.pyannote[3069].end 16838.04096875
transcript.pyannote[3070].speaker SPEAKER_09
transcript.pyannote[3070].start 16838.73284375
transcript.pyannote[3070].end 16842.04034375
transcript.pyannote[3071].speaker SPEAKER_09
transcript.pyannote[3071].start 16842.27659375
transcript.pyannote[3071].end 16874.49096875
transcript.pyannote[3072].speaker SPEAKER_09
transcript.pyannote[3072].start 16875.06471875
transcript.pyannote[3072].end 16881.20721875
transcript.pyannote[3073].speaker SPEAKER_09
transcript.pyannote[3073].start 16881.78096875
transcript.pyannote[3073].end 16887.28221875
transcript.pyannote[3074].speaker SPEAKER_09
transcript.pyannote[3074].start 16887.92346875
transcript.pyannote[3074].end 16897.01909375
transcript.pyannote[3075].speaker SPEAKER_09
transcript.pyannote[3075].start 16898.01471875
transcript.pyannote[3075].end 16898.60534375
transcript.pyannote[3076].speaker SPEAKER_09
transcript.pyannote[3076].start 16899.02721875
transcript.pyannote[3076].end 16901.01846875
transcript.pyannote[3077].speaker SPEAKER_09
transcript.pyannote[3077].start 16902.58784375
transcript.pyannote[3077].end 16905.94596875
transcript.pyannote[3078].speaker SPEAKER_09
transcript.pyannote[3078].start 16906.50284375
transcript.pyannote[3078].end 16908.22409375
transcript.pyannote[3079].speaker SPEAKER_09
transcript.pyannote[3079].start 16908.67971875
transcript.pyannote[3079].end 16909.33784375
transcript.pyannote[3080].speaker SPEAKER_09
transcript.pyannote[3080].start 16910.11409375
transcript.pyannote[3080].end 16916.40846875
transcript.pyannote[3081].speaker SPEAKER_09
transcript.pyannote[3081].start 16917.38721875
transcript.pyannote[3081].end 16917.79221875
transcript.pyannote[3082].speaker SPEAKER_09
transcript.pyannote[3082].start 16917.99471875
transcript.pyannote[3082].end 16927.84971875
transcript.pyannote[3083].speaker SPEAKER_09
transcript.pyannote[3083].start 16928.44034375
transcript.pyannote[3083].end 16934.90346875
transcript.pyannote[3084].speaker SPEAKER_09
transcript.pyannote[3084].start 16935.47721875
transcript.pyannote[3084].end 16940.43846875
transcript.pyannote[3085].speaker SPEAKER_09
transcript.pyannote[3085].start 16940.62409375
transcript.pyannote[3085].end 16941.55221875
transcript.pyannote[3086].speaker SPEAKER_23
transcript.pyannote[3086].start 16942.81784375
transcript.pyannote[3086].end 16950.00659375
transcript.pyannote[3087].speaker SPEAKER_09
transcript.pyannote[3087].start 16949.01096875
transcript.pyannote[3087].end 16956.62159375
transcript.pyannote[3088].speaker SPEAKER_23
transcript.pyannote[3088].start 16950.24284375
transcript.pyannote[3088].end 16950.32721875
transcript.pyannote[3089].speaker SPEAKER_23
transcript.pyannote[3089].start 16955.62596875
transcript.pyannote[3089].end 16961.98784375
transcript.pyannote[3090].speaker SPEAKER_09
transcript.pyannote[3090].start 16963.57409375
transcript.pyannote[3090].end 16965.27846875
transcript.pyannote[3091].speaker SPEAKER_23
transcript.pyannote[3091].start 16965.27846875
transcript.pyannote[3091].end 16975.75784375
transcript.pyannote[3092].speaker SPEAKER_09
transcript.pyannote[3092].start 16975.09971875
transcript.pyannote[3092].end 17001.32346875
transcript.pyannote[3093].speaker SPEAKER_06
transcript.pyannote[3093].start 16991.67096875
transcript.pyannote[3093].end 16992.00846875
transcript.pyannote[3094].speaker SPEAKER_23
transcript.pyannote[3094].start 17001.62721875
transcript.pyannote[3094].end 17006.85846875
transcript.pyannote[3095].speaker SPEAKER_09
transcript.pyannote[3095].start 17005.82909375
transcript.pyannote[3095].end 17009.23784375
transcript.pyannote[3096].speaker SPEAKER_23
transcript.pyannote[3096].start 17008.57971875
transcript.pyannote[3096].end 17009.89596875
transcript.pyannote[3097].speaker SPEAKER_23
transcript.pyannote[3097].start 17010.55409375
transcript.pyannote[3097].end 17014.62096875
transcript.pyannote[3098].speaker SPEAKER_09
transcript.pyannote[3098].start 17012.47784375
transcript.pyannote[3098].end 17012.84909375
transcript.pyannote[3099].speaker SPEAKER_23
transcript.pyannote[3099].start 17014.82346875
transcript.pyannote[3099].end 17015.93721875
transcript.pyannote[3100].speaker SPEAKER_09
transcript.pyannote[3100].start 17015.63346875
transcript.pyannote[3100].end 17026.87221875
transcript.pyannote[3101].speaker SPEAKER_09
transcript.pyannote[3101].start 17027.15909375
transcript.pyannote[3101].end 17028.05346875
transcript.pyannote[3102].speaker SPEAKER_09
transcript.pyannote[3102].start 17028.20534375
transcript.pyannote[3102].end 17030.83784375
transcript.pyannote[3103].speaker SPEAKER_09
transcript.pyannote[3103].start 17031.36096875
transcript.pyannote[3103].end 17035.27596875
transcript.pyannote[3104].speaker SPEAKER_09
transcript.pyannote[3104].start 17035.34346875
transcript.pyannote[3104].end 17046.32909375
transcript.pyannote[3105].speaker SPEAKER_09
transcript.pyannote[3105].start 17047.22346875
transcript.pyannote[3105].end 17049.19784375
transcript.pyannote[3106].speaker SPEAKER_09
transcript.pyannote[3106].start 17049.55221875
transcript.pyannote[3106].end 17051.96534375
transcript.pyannote[3107].speaker SPEAKER_09
transcript.pyannote[3107].start 17052.33659375
transcript.pyannote[3107].end 17054.14221875
transcript.pyannote[3108].speaker SPEAKER_09
transcript.pyannote[3108].start 17054.27721875
transcript.pyannote[3108].end 17080.29846875
transcript.pyannote[3109].speaker SPEAKER_09
transcript.pyannote[3109].start 17081.15909375
transcript.pyannote[3109].end 17081.66534375
transcript.pyannote[3110].speaker SPEAKER_09
transcript.pyannote[3110].start 17082.54284375
transcript.pyannote[3110].end 17083.77471875
transcript.pyannote[3111].speaker SPEAKER_09
transcript.pyannote[3111].start 17084.14596875
transcript.pyannote[3111].end 17111.11221875
transcript.pyannote[3112].speaker SPEAKER_09
transcript.pyannote[3112].start 17111.77034375
transcript.pyannote[3112].end 17112.71534375
transcript.pyannote[3113].speaker SPEAKER_23
transcript.pyannote[3113].start 17112.95159375
transcript.pyannote[3113].end 17123.95409375
transcript.pyannote[3114].speaker SPEAKER_09
transcript.pyannote[3114].start 17123.81909375
transcript.pyannote[3114].end 17126.85659375
transcript.pyannote[3115].speaker SPEAKER_09
transcript.pyannote[3115].start 17127.12659375
transcript.pyannote[3115].end 17142.43221875
transcript.pyannote[3116].speaker SPEAKER_09
transcript.pyannote[3116].start 17142.85409375
transcript.pyannote[3116].end 17148.82784375
transcript.pyannote[3117].speaker SPEAKER_09
transcript.pyannote[3117].start 17149.33409375
transcript.pyannote[3117].end 17153.06346875
transcript.pyannote[3118].speaker SPEAKER_09
transcript.pyannote[3118].start 17153.35034375
transcript.pyannote[3118].end 17154.90284375
transcript.pyannote[3119].speaker SPEAKER_09
transcript.pyannote[3119].start 17155.32471875
transcript.pyannote[3119].end 17156.94471875
transcript.pyannote[3120].speaker SPEAKER_09
transcript.pyannote[3120].start 17158.27784375
transcript.pyannote[3120].end 17164.96034375
transcript.pyannote[3121].speaker SPEAKER_23
transcript.pyannote[3121].start 17159.67846875
transcript.pyannote[3121].end 17159.91471875
transcript.pyannote[3122].speaker SPEAKER_23
transcript.pyannote[3122].start 17164.63971875
transcript.pyannote[3122].end 17167.93034375
transcript.pyannote[3123].speaker SPEAKER_09
transcript.pyannote[3123].start 17167.25534375
transcript.pyannote[3123].end 17168.60534375
transcript.pyannote[3124].speaker SPEAKER_23
transcript.pyannote[3124].start 17168.40284375
transcript.pyannote[3124].end 17169.29721875
transcript.pyannote[3125].speaker SPEAKER_23
transcript.pyannote[3125].start 17169.34784375
transcript.pyannote[3125].end 17180.33346875
transcript.pyannote[3126].speaker SPEAKER_09
transcript.pyannote[3126].start 17179.70909375
transcript.pyannote[3126].end 17185.27784375
transcript.pyannote[3127].speaker SPEAKER_23
transcript.pyannote[3127].start 17183.13471875
transcript.pyannote[3127].end 17183.64096875
transcript.pyannote[3128].speaker SPEAKER_23
transcript.pyannote[3128].start 17184.82221875
transcript.pyannote[3128].end 17186.66159375
transcript.pyannote[3129].speaker SPEAKER_09
transcript.pyannote[3129].start 17186.42534375
transcript.pyannote[3129].end 17190.62721875
transcript.pyannote[3130].speaker SPEAKER_09
transcript.pyannote[3130].start 17192.26409375
transcript.pyannote[3130].end 17199.50346875
transcript.pyannote[3131].speaker SPEAKER_09
transcript.pyannote[3131].start 17199.58784375
transcript.pyannote[3131].end 17200.33034375
transcript.pyannote[3132].speaker SPEAKER_09
transcript.pyannote[3132].start 17201.79846875
transcript.pyannote[3132].end 17205.40971875
transcript.pyannote[3133].speaker SPEAKER_23
transcript.pyannote[3133].start 17205.44346875
transcript.pyannote[3133].end 17210.59034375
transcript.pyannote[3134].speaker SPEAKER_09
transcript.pyannote[3134].start 17210.15159375
transcript.pyannote[3134].end 17214.53909375
transcript.pyannote[3135].speaker SPEAKER_09
transcript.pyannote[3135].start 17214.96096875
transcript.pyannote[3135].end 17216.83409375
transcript.pyannote[3136].speaker SPEAKER_09
transcript.pyannote[3136].start 17216.96909375
transcript.pyannote[3136].end 17220.29346875
transcript.pyannote[3137].speaker SPEAKER_23
transcript.pyannote[3137].start 17220.52971875
transcript.pyannote[3137].end 17225.38971875
transcript.pyannote[3138].speaker SPEAKER_09
transcript.pyannote[3138].start 17225.47409375
transcript.pyannote[3138].end 17247.93471875
transcript.pyannote[3139].speaker SPEAKER_09
transcript.pyannote[3139].start 17249.01471875
transcript.pyannote[3139].end 17249.60534375
transcript.pyannote[3140].speaker SPEAKER_09
transcript.pyannote[3140].start 17249.94284375
transcript.pyannote[3140].end 17256.20346875
transcript.pyannote[3141].speaker SPEAKER_09
transcript.pyannote[3141].start 17257.48596875
transcript.pyannote[3141].end 17260.30409375
transcript.pyannote[3142].speaker SPEAKER_23
transcript.pyannote[3142].start 17260.15221875
transcript.pyannote[3142].end 17266.10909375
transcript.pyannote[3143].speaker SPEAKER_09
transcript.pyannote[3143].start 17264.72534375
transcript.pyannote[3143].end 17267.77971875
transcript.pyannote[3144].speaker SPEAKER_23
transcript.pyannote[3144].start 17268.13409375
transcript.pyannote[3144].end 17270.86784375
transcript.pyannote[3145].speaker SPEAKER_09
transcript.pyannote[3145].start 17269.21409375
transcript.pyannote[3145].end 17269.82159375
transcript.pyannote[3146].speaker SPEAKER_09
transcript.pyannote[3146].start 17270.86784375
transcript.pyannote[3146].end 17279.08596875
transcript.pyannote[3147].speaker SPEAKER_23
transcript.pyannote[3147].start 17279.54159375
transcript.pyannote[3147].end 17281.04346875
transcript.pyannote[3148].speaker SPEAKER_09
transcript.pyannote[3148].start 17282.68034375
transcript.pyannote[3148].end 17289.27846875
transcript.pyannote[3149].speaker SPEAKER_09
transcript.pyannote[3149].start 17289.90284375
transcript.pyannote[3149].end 17291.10096875
transcript.pyannote[3150].speaker SPEAKER_09
transcript.pyannote[3150].start 17291.75909375
transcript.pyannote[3150].end 17294.07096875
transcript.pyannote[3151].speaker SPEAKER_09
transcript.pyannote[3151].start 17294.52659375
transcript.pyannote[3151].end 17297.61471875
transcript.pyannote[3152].speaker SPEAKER_09
transcript.pyannote[3152].start 17297.80034375
transcript.pyannote[3152].end 17299.01534375
transcript.pyannote[3153].speaker SPEAKER_09
transcript.pyannote[3153].start 17299.53846875
transcript.pyannote[3153].end 17304.66846875
transcript.pyannote[3154].speaker SPEAKER_09
transcript.pyannote[3154].start 17305.42784375
transcript.pyannote[3154].end 17307.25034375
transcript.pyannote[3155].speaker SPEAKER_09
transcript.pyannote[3155].start 17307.26721875
transcript.pyannote[3155].end 17311.63784375
transcript.pyannote[3156].speaker SPEAKER_09
transcript.pyannote[3156].start 17312.02596875
transcript.pyannote[3156].end 17318.43846875
transcript.pyannote[3157].speaker SPEAKER_23
transcript.pyannote[3157].start 17319.77159375
transcript.pyannote[3157].end 17324.02409375
transcript.pyannote[3158].speaker SPEAKER_09
transcript.pyannote[3158].start 17323.92284375
transcript.pyannote[3158].end 17329.22159375
transcript.pyannote[3159].speaker SPEAKER_23
transcript.pyannote[3159].start 17329.60971875
transcript.pyannote[3159].end 17330.45346875
transcript.pyannote[3160].speaker SPEAKER_23
transcript.pyannote[3160].start 17331.82034375
transcript.pyannote[3160].end 17331.83721875
transcript.pyannote[3161].speaker SPEAKER_09
transcript.pyannote[3161].start 17331.83721875
transcript.pyannote[3161].end 17332.12409375
transcript.pyannote[3162].speaker SPEAKER_09
transcript.pyannote[3162].start 17332.96784375
transcript.pyannote[3162].end 17334.31784375
transcript.pyannote[3163].speaker SPEAKER_09
transcript.pyannote[3163].start 17335.39784375
transcript.pyannote[3163].end 17342.83971875
transcript.pyannote[3164].speaker SPEAKER_09
transcript.pyannote[3164].start 17343.32909375
transcript.pyannote[3164].end 17349.06659375
transcript.pyannote[3165].speaker SPEAKER_09
transcript.pyannote[3165].start 17349.42096875
transcript.pyannote[3165].end 17350.66971875
transcript.pyannote[3166].speaker SPEAKER_09
transcript.pyannote[3166].start 17351.07471875
transcript.pyannote[3166].end 17358.07784375
transcript.pyannote[3167].speaker SPEAKER_09
transcript.pyannote[3167].start 17359.79909375
transcript.pyannote[3167].end 17362.66784375
transcript.pyannote[3168].speaker SPEAKER_09
transcript.pyannote[3168].start 17363.88284375
transcript.pyannote[3168].end 17364.70971875
transcript.pyannote[3169].speaker SPEAKER_09
transcript.pyannote[3169].start 17365.01346875
transcript.pyannote[3169].end 17376.37034375
transcript.pyannote[3170].speaker SPEAKER_09
transcript.pyannote[3170].start 17377.31534375
transcript.pyannote[3170].end 17379.47534375
transcript.pyannote[3171].speaker SPEAKER_09
transcript.pyannote[3171].start 17379.94784375
transcript.pyannote[3171].end 17388.33471875
transcript.pyannote[3172].speaker SPEAKER_09
transcript.pyannote[3172].start 17388.58784375
transcript.pyannote[3172].end 17404.29846875
transcript.pyannote[3173].speaker SPEAKER_09
transcript.pyannote[3173].start 17404.77096875
transcript.pyannote[3173].end 17418.11909375
transcript.pyannote[3174].speaker SPEAKER_09
transcript.pyannote[3174].start 17418.22034375
transcript.pyannote[3174].end 17445.00096875
transcript.pyannote[3175].speaker SPEAKER_02
transcript.pyannote[3175].start 17445.30471875
transcript.pyannote[3175].end 17445.82784375
transcript.pyannote[3176].speaker SPEAKER_03
transcript.pyannote[3176].start 17446.19909375
transcript.pyannote[3176].end 17478.61596875
transcript.pyannote[3177].speaker SPEAKER_21
transcript.pyannote[3177].start 17498.35971875
transcript.pyannote[3177].end 17498.62971875
transcript.whisperx[0].start 734.619
transcript.whisperx[0].end 734.639
transcript.whisperx[0].text 委員會議
transcript.whisperx[1].start 1795.539
transcript.whisperx[1].end 1809.392
transcript.whisperx[1].text 出席委員已逐法定人數現在開會請議事人員宣讀上次會議議事錄立法院第11屆第1會期社會福利及衛生環境委員會第4次全體委員會議議事錄時間113年3月7日星期四9時至13時12分
transcript.whisperx[2].start 1813.496
transcript.whisperx[2].end 1834.485
transcript.whisperx[2].text 地點群賢樓801會議室出席委員陳昭芝等15人列席委員王宏偉等20人列席官員衛生福利部部長薛瑞元等相關人員主席王兆吉委員玉敏宣讀上次會議議事錄決定確定邀請衛生福利部部長中央健康保險署食品藥物管理署就健保藥價調整藥廠停產慢性病用藥製因應作為進行專題報告並備質詢
transcript.whisperx[3].start 1840.808
transcript.whisperx[3].end 1866.862
transcript.whisperx[3].text 本次會議由衛生福利部部長報告後委員陳昭芝等23人提出質詢均經衛生福利部部長及各相關主管等及其答覆委員楊耀及楊瓊英所提書面質詢列入紀錄刊登公報決定一報告及詢答完畢二委員質詢未及答覆或請補充資料者請相關機關於2週內以書面答覆委員令要求期限者從其所定通過臨時提案6項宣讀完畢
transcript.whisperx[4].start 1870.718
transcript.whisperx[4].end 1890.206
transcript.whisperx[4].text 請問委員會上次議事錄有無錯誤或遺漏之處沒有那議事錄確定本日會議議程為邀請勞動部部長列席報告業務概況並備質詢那現在我們介紹在場的委員王振旭委員陳昭芝委員陳金輝委員
transcript.whisperx[5].start 1900.626
transcript.whisperx[5].end 1926.337
transcript.whisperx[5].text 如現役委員現場今天來我們列席的官員有勞動部部長許明春許部長勞動力發展署蔡猛良署長勞工保險局白立貞局長勞動基金運用局蘇玉清局長
transcript.whisperx[6].start 1928.005
transcript.whisperx[6].end 1951.857
transcript.whisperx[6].text 職業安全衛生署周子蓮署長勞動及職業安全衛生研究所李伯昌所長綜合規劃司王厚誠司長勞動關係司王厚偉司長勞動保險司陳美女司長勞動福祉退休司謝倩倩司長
transcript.whisperx[7].start 1954.004
transcript.whisperx[7].end 1969.708
transcript.whisperx[7].text 勞動條件及就業平等司黃維琛司長勞動法務司傅惠芝司長秘書處丁玉珍處長人事處江碧玲處長政風處邱鴻達處長會計處林美信處長統計處梅嘉源處長資訊處劉純
transcript.whisperx[8].start 1982.386
transcript.whisperx[8].end 1994.439
transcript.whisperx[8].text 留存坤處長才團法人職業災害預防及重建中心執行長和俊傑和執行長好那接下來請勞動部部長許部長報告時間5分鐘
transcript.whisperx[9].start 2001.929
transcript.whisperx[9].end 2030.698
transcript.whisperx[9].text 主席各位委員先進各位記者女士先生大家好感謝貴委員會的邀請由本人向委員們進行本部業務報告進行各位委員給予指教在勞動情勢方面112年度勞動力人數較前一年同期增加9萬人就業人數增加11萬人失業率下降0.19個百分點男性與女性的勞參率差距減少0.3個百分點全體經常性的薪資增加了百分之0.2
transcript.whisperx[10].start 2032.079
transcript.whisperx[10].end 2032.299
transcript.whisperx[10].text 一致一致
transcript.whisperx[11].start 2052.282
transcript.whisperx[11].end 2074.307
transcript.whisperx[11].text 此外針對契格行業的減班休息勞工推動僱用安定措施提供最長6個月的薪資補貼並且與內政部合作實施在台移工以再次申請聘僱及居留整合服務預期每年受益的僱主及移工約有20萬人接下來依照本部三大施政目標回顧過去一年到現在的重要施政成果
transcript.whisperx[12].start 2075.257
transcript.whisperx[12].end 2090.874
transcript.whisperx[12].text 為了協助青年就業我們持續推動投資青年就業方案第二期去年到現在已經協助了226000多人至於在提升中高齡及高齡勞動力方面協助大概207000人就業另外在今年的2月發布55plus
transcript.whisperx[13].start 2092.876
transcript.whisperx[13].end 2093.216
transcript.whisperx[13].text 獲得獲得獲得
transcript.whisperx[14].start 2117.813
transcript.whisperx[14].end 2124.455
transcript.whisperx[14].text 我們也透過多元方式提供在職勞工或失業者需要的就業訓練服務去年到現在合撥了26萬5000餘張的技術事證並且鼓勵青少年學習技能
transcript.whisperx[15].start 2131.877
transcript.whisperx[15].end 2155.924
transcript.whisperx[15].text 去年第二屆亞洲技能競賽中我國獲得了十二金六銀四桶三優勝的好成績同時我們也持續結合民間團體的力量推動多元就業方案及賠率就業計畫創造在地就業的機會並且持續推動移工政策強化移工的權益保障到現在已經核准了近兩萬四千名資深移工轉任中階技術工作
transcript.whisperx[16].start 2156.764
transcript.whisperx[16].end 2177.14
transcript.whisperx[16].text 另外為了加強保障基層勞工維持生活水準於上會期完成制定最低工資法並於今年1月1日開始上路專法將使最低工資的審議制度更為完善周延在強化職場性騷擾方面配合性別平等工作法的修正本部完成了7項執法的訂修
transcript.whisperx[17].start 2177.94
transcript.whisperx[17].end 2202.858
transcript.whisperx[17].text 後續將會加強職場性騷擾防治教育訓練及宣導穩健落實相關的防治工作並為了建構安心的職場環境除了補助453家企業提供托兒設措施提高育嬰津貼及薪資補助措施讓236,000多位的新手爸媽受惠我們持續推動創造勞資雙贏的良性制度除了積極輔導
transcript.whisperx[18].start 2204.139
transcript.whisperx[18].end 2209.547
transcript.whisperx[18].text 並且鼓勵勞資雙方簽訂團體協約同時建置了超過700名的勞動教育專業人員資料庫作為各界推動勞動教育的實質參考期盼能使勞動意識持續上下扎根
transcript.whisperx[19].start 2220.003
transcript.whisperx[19].end 2227.408
transcript.whisperx[19].text 接著在確保勞工退休生活經濟安全方面,勞退救濟的足額提撥率已達到99.8%,勞退薪資提繳人數已達751萬4千多人,自願提繳人數達到106萬4千多人,勞動基金累計收益數為2兆1千
transcript.whisperx[20].start 2237.774
transcript.whisperx[20].end 2259.888
transcript.whisperx[20].text 一百三十四議員累計收益率為百分之五十三點五三四年化收益率為百分之五點三六此外勞工職業安全也一直是本部重視的重點工作我們除了持續辦理各項檢查以外並採行輔導及法尊房事等措施每年也針對中小企業高風險企業及3K特定製程產業執行臨場房事輔導
transcript.whisperx[21].start 2263.01
transcript.whisperx[21].end 2279.947
transcript.whisperx[21].text 並且加強推動營造工程的減災機制以及持續列管容易發生火災爆炸的石化及大型化學工廠等場所在保障職災勞工及其家屬基本經濟生活方面去年職災保險現金給付共合幅9萬4千多件醫療給付為143萬2千多件
transcript.whisperx[22].start 2284.011
transcript.whisperx[22].end 2310.552
transcript.whisperx[22].text 其次我們持續擴充職業傷病診治服務網絡至今年起職災職能復健專者醫院擴增為36家職災職能復健身心理強化機構擴增為22家提供3萬人次以上的職業傷病診治及相關的復工服務展望未來本部除了持續推動提升中高齡及高齡者與婦女勞動參與以及強化青年救援協助外人家積極回應
transcript.whisperx[23].start 2311.647
transcript.whisperx[23].end 2312.307
transcript.whisperx[23].text 以上報告 敬請各位委員指教謝謝
transcript.whisperx[24].start 2334.328
transcript.whisperx[24].end 2348.697
transcript.whisperx[24].text 謝謝部長有關本次會議各項書面資料均列入紀錄刊登公報接下來開始做以下的宣告本會委員尋答時間6加2分鐘列席委員4加1分鐘10點30分截止發言登記委員如有書面質詢
transcript.whisperx[25].start 2355.681
transcript.whisperx[25].end 2371.673
transcript.whisperx[25].text 請於散會前提出預期不受理暫定10點30分休息10分鐘原則上11點30分處理臨時提案10點30分截止收案那現在請登記第一位委員陳昭芝委員有請部長及安署州署長謝謝
transcript.whisperx[26].start 2385.29
transcript.whisperx[26].end 2407.671
transcript.whisperx[26].text 部長好貼實認證是我國根據職業安全衛生法令等辦理的一個合格驗證證明那只有符合標準的這個機械設備甚至防爆管配件才可以在我國的石化工廠或電廠內的高危險區來使用目的是讓這些工廠發生危險的時候能夠把災害控制到一個範圍內但是2018年的時候我們當委員有
transcript.whisperx[27].start 2412.395
transcript.whisperx[27].end 2420.524
transcript.whisperx[27].text 臺電的大林場它的高風險場區使用的防暴管材有使用到東元系統的安博產品那那個產品是偽造臺灣TS認證的部長您還記得這件事嗎
transcript.whisperx[28].start 2426.411
transcript.whisperx[28].end 2445.886
transcript.whisperx[28].text 就是當時臺電有要求同胞商這現代樂鐵跟榮工公司把這個所有不合格的產品要做一個更換但是臺電也有提出對這個同胞商提出要求就是要求使用所謂的可斷鑄鐵這個材質來作為這個防爆管配件那我先把這個背景跟部長說明一下
transcript.whisperx[29].start 2448.087
transcript.whisperx[29].end 2455.775
transcript.whisperx[29].text 這一家廠商叫做深芳公司他也有許多防爆管配件的這個也向職安署登錄取得這個TS認證但是我要強調是他眾多產品當中只有這個
transcript.whisperx[30].start 2461.434
transcript.whisperx[30].end 2478.159
transcript.whisperx[30].text 可斷鑄鐵的材質有TS認證他的效期有3年部長根據那個職業安全衛生法的規定是不是只有經過測試檢定而且在職安署的網站上去登錄的你才可以在銷售的時候宣稱說你是具有這個TS認證我這個說法正確嗎
transcript.whisperx[31].start 2481.328
transcript.whisperx[31].end 2484.13
transcript.whisperx[31].text 我們製造輸入使用我們指定的機械設備必須取得安全標準才可以來做實施,因為我們有管理系統和制製來執行
transcript.whisperx[32].start 2497.459
transcript.whisperx[32].end 2510.384
transcript.whisperx[32].text 那下一張就是我前面提到2019 2019臺電大臨場因為需要因為不合格嘛再更換這個防爆這個氣管材的時候這家生方公司他明明知道自己取得ts認證的產品只限於這個鑄鐵合金
transcript.whisperx[33].start 2515.29
transcript.whisperx[33].end 2537.686
transcript.whisperx[33].text 但是他在送審的這個產品的送審證書上寫的注鐵合金但實際成分是球末注鐵以後交貨也會是球末注鐵當然我們沒有否定球末注鐵也許他的材質是更好的但是他可以這樣濫用他的貼紙證照嗎就是說他合什麼是什麼他可以拿別的東西來抵嗎當然不行
transcript.whisperx[34].start 2538.686
transcript.whisperx[34].end 2549.71
transcript.whisperx[34].text 那我們都知道部長說是不行這個灰口鑄鐵可斷鑄鐵或這個球木鑄鐵他完全不同的材質所以生方拿出這樣證書交給台電還好台電當時覺得有點問題是沒有採購但是我要談的是台電沒有採購但是廠商可以這樣做嗎所以就是說
transcript.whisperx[35].start 2558.573
transcript.whisperx[35].end 2578.396
transcript.whisperx[35].text 上個月底我的辦公室同仁也有到職安署大林電廠去檢查去參與這個檢查那麼現場台電也承認說當時是有接到這樣的文件那部長你何時要依法去裁罰呢就是廠商這樣的做法何時要去裁罰呢因為這個部分229我們去查
transcript.whisperx[36].start 2580.418
transcript.whisperx[36].end 2593.815
transcript.whisperx[36].text 確實是有一些異議目前是在請台電公司要提供相關的合約部長這個去年就有立委檢舉了很久了但是我們都有按照程序要進行詳細我請署長來說明
transcript.whisperx[37].start 2597.318
transcript.whisperx[37].end 2619.904
transcript.whisperx[37].text 我跟您簡單解釋因為大林電廠是舊的電廠它是用原來是用美規的標準來做設置跟施工的製造那我們慈安法在103年開始試用的時候有關我們是用新的歐規的標準所以這兩個標準在融合過程中臺電大林電廠用既有的標準在設置那現在是依照用電用戶建設裝置規則
transcript.whisperx[38].start 2622.765
transcript.whisperx[38].end 2649.566
transcript.whisperx[38].text 來做進步的釐清我們勞動部會跟經濟部做進步更化設計安裝的設備做有效來做確認這一次的重點就是像申方他認證的配管件因為他的效期是3年那他會不會一併到其他的地方中油啦台塑啦中頂公司也是用同樣的證明文件去處理你要不可以一併謝謝委員其實包括原來的委員跟您非常關心這個我非常非常感謝因為在
transcript.whisperx[39].start 2650.026
transcript.whisperx[39].end 2667.329
transcript.whisperx[39].text ​​​​​​​​​​
transcript.whisperx[40].start 2667.329
transcript.whisperx[40].end 2697.329
transcript.whisperx[40].text
transcript.whisperx[41].start 2697.869
transcript.whisperx[41].end 2698.809
transcript.whisperx[41].text 對不起委員可不可以插個話
transcript.whisperx[42].start 2721.674
transcript.whisperx[42].end 2749.683
transcript.whisperx[42].text 這個部份是不是在防暴區因為我剛才跟委員解釋大聯想是用舊的美規標準設施規劃所以我現在就請經濟部做進一步的釐清如果這個區塊是真的需要屬於防暴區的話當然台電這個部份就要做比較明確的違反規定就是說那一天台電說要去帶大家去看防暴區啦說該處使用需要符合防暴標準的防暴管材那參加抽驗的人都有職安署官員啊公研院的專家在
transcript.whisperx[43].start 2750.563
transcript.whisperx[43].end 2750.943
transcript.whisperx[43].text 是他是這麼說的
transcript.whisperx[44].start 2780.883
transcript.whisperx[44].end 2782.966
transcript.whisperx[44].text 部長這個職聘這個是移工職聘的部分首次招募右邊是這個再次招募重新招募你看那個職聘的比率這10年來離1%很遙遠的0.2%
transcript.whisperx[45].start 2797.805
transcript.whisperx[45].end 2815.986
transcript.whisperx[45].text 然後對於重新這個招募的部分這個理論上說移工工作滿3年僱主要繼續聘照理說他們有經驗了那應該還要再發這個仲介費嗎我是說他們為什麼職域也是1%所以部長勞動部雖然說職聘是你的既定政策但是效果不好嗎是不是對對效果不好
transcript.whisperx[46].start 2816.406
transcript.whisperx[46].end 2836.254
transcript.whisperx[46].text 那效果在上次我質詢也有提出來那後來就有專家就是所謂的前勞發署跨國勞動力管理組組長薛建忠他指出說整個職聘有三大難關移工人選難密、語言密不通、申請程序繁複部長您同意這三個是一個障礙或難關嗎?部長您同意這三點?
transcript.whisperx[47].start 2837.868
transcript.whisperx[47].end 2855.134
transcript.whisperx[47].text 這個因為是我們之前組長他是這個主辦的人他應該是很瞭解的其實我知道勞動部很努力但是就是說我們看看哪一些可以再繼續做得更好難關一人選難密部長現在問題是有移工團體指控他們到就業服務站
transcript.whisperx[48].start 2855.974
transcript.whisperx[48].end 2873.317
transcript.whisperx[48].text 我說全臺灣都有就業服戰他不只幫外國本國人沒有也有幫助外籍外移工但是移工到了現場你看他們他到現場沒有僱主來他要他簽到因為如果不簽到的話他就會被強制反國那這個就是他簽到但是到了他們問僱主在哪裡
transcript.whisperx[49].start 2874.839
transcript.whisperx[49].end 2891.277
transcript.whisperx[49].text 那個工作人員竟然說你們要自己找那不像求職的時候你這個人事部叫你來面試那你說面試官呢沒有面試官面試官你要自己去104這個銀行網站找這個這樣這個就業服務站只簽名不媒合這樣可以嗎部長
transcript.whisperx[50].start 2892.661
transcript.whisperx[50].end 2917.608
transcript.whisperx[50].text 這當然不行所以移工抗議了嘛這個我們改變好不好改進好不好了解一下也要針對這些缺失來具體來講一下那因為還有兩個點一個是言語不通啦那這個就是說我們知道全臺灣總共有48座就業服務中心如果要提供這個媒合可能要有雙語服務部長你知道這48座就業服務中心有幾家是提供的四國雙語服務
transcript.whisperx[51].start 2920.1
transcript.whisperx[51].end 2941.147
transcript.whisperx[51].text 我們其實現在就是在各就福站透過三方有兩家一個桃園一個在彰化去年成立的我覺得這個很棒這是專設的但是我們其實各就福站都可以透過三方的一個因為我們現在還在談職聘中心怎麼來鼓勵那一年當中大概有多少移工會轉換雇主
transcript.whisperx[52].start 2943.782
transcript.whisperx[52].end 2960.21
transcript.whisperx[52].text 大概有多少位要轉換雇主會需要這樣的服務大概兩萬多兩萬多每年大概有兩萬多那因為這樣的兩座老實說48座裡面兩座這樣子是不是說這種算是很好的服務是不是可能再考慮再擴大一下那最後沒問題我們這兩座是先示範謝謝謝謝部長的承諾
transcript.whisperx[53].start 2965.632
transcript.whisperx[53].end 2979.685
transcript.whisperx[53].text 好那最後一個是身體法上次我在質詢就是說執聘手續非常的繁複啊簡直像這個玩大地遊戲我覺得玩大風吹他進進出出很多的機構但是這個勞動部已經做到了一個部分點就是說
transcript.whisperx[54].start 2981.124
transcript.whisperx[54].end 3003.966
transcript.whisperx[54].text 高雄跟長高雄的桃園高高雄成立一站式服務我覺得很棒的內動內政部勞動部跨跨服務的跨部會合作這種就是最便民的一個做法這個一站式的服務啊移工可以在這裡中心接受三天兩夜的這個講習來來瞭解在臺灣生活需知啊為衛生保健還有勞動權益等等那雇主這邊可以一次性的辦好對
transcript.whisperx[55].start 3004.967
transcript.whisperx[55].end 3005.407
transcript.whisperx[55].text 謝謝陳昭芝委員接下來我們請陳金輝委員
transcript.whisperx[56].start 3032.731
transcript.whisperx[56].end 3056.491
transcript.whisperx[56].text 主席主席各位同事媒體朋友還有各位官員大家早安我想請部長請部長部長剛剛陳昭之委員講的所有的問題我上禮拜有問你有一本移工管理及調查報告每年都會出一本您上禮拜說您沒有看請問這週您看了嗎
transcript.whisperx[57].start 3061.078
transcript.whisperx[57].end 3074.069
transcript.whisperx[57].text 我會來看我會來看報告委員因為同仁都會整給我啦因為那個報告有時候我比較沒有時間他們都會把重點載入給我好可以你太忙了但是焦志偉人剛剛講的所有問題
transcript.whisperx[58].start 3075.67
transcript.whisperx[58].end 3089.955
transcript.whisperx[58].text 報告都已經寫了但這些問題已經連續3年沒有改善包括文件繁瑣找不到職聘中心還有招牌越來越少連職聘中心的後面沒有附英文
transcript.whisperx[59].start 3092.114
transcript.whisperx[59].end 3108.274
transcript.whisperx[59].text 質詢中心的招牌後面沒有英文但是勞動部的後面有英文那個我來看一下如果沒有我們馬上改善應該要這個基本的好謝謝部長因為我上禮拜就說過質詢中心假使沒有發揮您預期的功能的話其實
transcript.whisperx[60].start 3110.114
transcript.whisperx[60].end 3134.9
transcript.whisperx[60].text 報告委員我們這個真的會來努力因為齁仲介的制度已經大家習慣使用了而且說職聘齁還是有他的困難點不過我們會努力來突破包括程序的繁瑣文件怎麼樣簡化流程怎麼樣讓大家方便這個我們要來努力真的很希望明年不會再看到這個移工管理及調查報告還在反映文件很繁瑣這樣子的問題了那我們來看這個
transcript.whisperx[61].start 3139.212
transcript.whisperx[61].end 3154.861
transcript.whisperx[61].text 您自己公布的同工同酬立法已經兩性平等法已經20年了結果呢女生還是要多工作54天薪資才可以追平男性跟男性平起平坐
transcript.whisperx[62].start 3156.587
transcript.whisperx[62].end 3173.462
transcript.whisperx[62].text 我只要這個是跟2019 2019年蔡英文總統相任的時候一模一樣的天數欸所以我們的總統是女性我們高官勞動部長是女性但是我們經過了8年我們的同工同酬日還是54天
transcript.whisperx[63].start 3175.453
transcript.whisperx[63].end 3202.854
transcript.whisperx[63].text 會不會覺得這個數據是不是我們努力的方向錯了我是覺得我們還在努力不過其實我要跟委員報告我們其實這樣的一個差距相對於美國的17日本的韓國的30我們其實是更平等但是我覺得這個是還有要大大努力的空間不過有時候這個薪資差距主要是來自於所謂性別職業的隔離那這個部分就是跨部會要努力
transcript.whisperx[64].start 3203.715
transcript.whisperx[64].end 3228.183
transcript.whisperx[64].text 那這個就是要透過教育啦職業訓練來改善我們等一下來看另外一個數據好除了我們的薪資落後喔這個薪資差距這個也是您發布的我們算是27個國家排名中第20名倒數第8名所以臺灣每一位男性勞動者每個月平均收入是61150元女性勞動者平均每個月49809元每個月會少11341
transcript.whisperx[65].start 3232.464
transcript.whisperx[65].end 3234.807
transcript.whisperx[65].text 一年就少了13點6萬報告委員這個他這個統計是統計前段班的部分我們是在前段班的排名我們不是說整個全世界我們
transcript.whisperx[66].start 3248.126
transcript.whisperx[66].end 3259.178
transcript.whisperx[66].text 最差不是這樣子他是取前段班那我們的排名在我懂我們需要更好所以我們過去8年其實是沒有進步過去8年沒有進步但您剛講到說這個選工作科系學歷但我跟部長update一下
transcript.whisperx[67].start 3270.53
transcript.whisperx[67].end 3292.02
transcript.whisperx[67].text 最新的數據有110年其實50歲以下的女性他讀大專的比例已經高過男性了但當然在研究所的比例男性還是高過女性如果我們的學金力過去幾十年大幅的提升我們的勞參率還有我們的薪資的差異不是應該也要改善嗎這個我想
transcript.whisperx[68].start 3296.991
transcript.whisperx[68].end 3319.107
transcript.whisperx[68].text 這個應該我們會努力逐年會改善這個部分好所以剛好看到說如果我跟我先生是做一樣的工作但是我已經預期我會少他一萬多又看到新聞時不時可能會有很害怕的這個脫音脫語的虐待等等的事件其實每一個女生想一想算一算自然就不會去參與勞動嗎
transcript.whisperx[69].start 3321.289
transcript.whisperx[69].end 3338.037
transcript.whisperx[69].text 但是您這邊也有寫到啊建構友善生養環境促進雇主提供子女托育及工作平衡措施如果你這些沒有跟上的話我們怎麼可能可以改善我們的勞資差異呢
transcript.whisperx[70].start 3339.008
transcript.whisperx[70].end 3356.502
transcript.whisperx[70].text 所以我們一直都在各項的友善的育兒措施或設施都一直努力在推啦好我們等一下來看一下你其他的KPI從國內來看呢過去10年喔剛講過去8年我們從100年到110年兩性的勞參率的差距只有從16%降到15%欸
transcript.whisperx[71].start 3367.421
transcript.whisperx[71].end 3377.134
transcript.whisperx[71].text 一趴十年降了一趴差距還是非常的巨大從這個數據來看我真的很難看出勞動部這個業務報告有什麼很明顯的改善
transcript.whisperx[72].start 3385.257
transcript.whisperx[72].end 3404.366
transcript.whisperx[72].text 當然因為在國內還是女性有時候會因為育兒婚育照顧的因素會離開不過我們這幾年一直在針對女性的就業的一些促進的措施那我們等一下再來看我們會持續來努力因此我們的在就業狀況
transcript.whisperx[73].start 3406.227
transcript.whisperx[73].end 3421.804
transcript.whisperx[73].text 剛您提到再就業嘛因為他們育兒啊進入家庭所以對他們而言最重要就是當他們中斷了一長個時間以後他們願意再回職場的這樣意願高不高嘛我們圈起來看女性不管哪一國臺灣日本韓國高點就是25到29歲
transcript.whisperx[74].start 3425.268
transcript.whisperx[74].end 3452.181
transcript.whisperx[74].text 但是台灣在29歲以後一路往下滑日本跟韓國在45到49 50到54都有兩個高點所以我們要看女性幫你們圈起來了紅色這邊50歲以後的就業率65%46 26我們跟日本韓國比起來真的太丟臉了我們是不到人家的二分之一甚至不到接近三分之一耶
transcript.whisperx[75].start 3454.243
transcript.whisperx[75].end 3465.487
transcript.whisperx[75].text 的確在國內我們的女性勞參與在101年首次突破50%以後然後一直穩定成長了112年51.93那基本上25到29的勞參與大概九成可是
transcript.whisperx[76].start 3471.889
transcript.whisperx[76].end 3487.669
transcript.whisperx[76].text 三十歲以後就逐年下降吼所以表示臺灣女生就沒有雙峰國外有雙峰吶所以我們現在也跟尾巴我們有去年就推那個婦女二度就業那去年推薦的人次有兩萬
transcript.whisperx[77].start 3488.71
transcript.whisperx[77].end 3506.617
transcript.whisperx[77].text 婦女在就業計畫一年花3.5億三年要花10.5億結果你幫自己訂的KPI是女性勞動力三年增加14萬好請問你這個女性勞動力不就包括全部的女生嗎你有特別把二度就業挑出來嗎
transcript.whisperx[78].start 3508.232
transcript.whisperx[78].end 3516.498
transcript.whisperx[78].text 這是二度就業喔這是再就業報告委員這不是全體這是針對二度就業你要再增加14萬人對對對這是新的計畫
transcript.whisperx[79].start 3521.894
transcript.whisperx[79].end 3542.603
transcript.whisperx[79].text 我想問一下你這個KPI是不是應該重新調整因為我們在沒有這個就業計畫的時候105到108年自然成長的女性就業就已經12萬了對但你如果要特別把它挑出來的話你這些表格應該要分成在就業率在就業的人還有對
transcript.whisperx[80].start 3544.507
transcript.whisperx[80].end 3559.637
transcript.whisperx[80].text 剛講到薪資嘛我們不能只看這個kpi只看數字因爲他現在連薪資都非常的不平等所以你應該要仔細把你的kpi去分析我這些二度在就業他的薪資結構是高的是中的是低的
transcript.whisperx[81].start 3561.351
transcript.whisperx[81].end 3585.607
transcript.whisperx[81].text 是嗎?不然你如果是低的在就這個薪資比較低的在就業率幫他媒合的是優質的職缺啦其實剛剛我跟委員講我們那個KPI其實有跨部會大家討論那因為這個部分是二度就業婦女那我們會考慮這種狀況當然我們也希望能夠把那個人數KPI再提高不過我們
transcript.whisperx[82].start 3586.167
transcript.whisperx[82].end 3612.41
transcript.whisperx[82].text 我們會滾動檢討啦一定會滾動檢討我是很希望啦在這邊給部長一個建議請您回去要稍微調整一下這個KPI因為你如果光是解決人數或是比例或是勞動力的話你沒有辦法解決你明年發布同工同酬日還是54天的問題那個同工同酬其實跟這個不一定是有相關聯我剛剛講的就是說這個其實要從整個的
transcript.whisperx[83].start 3616.934
transcript.whisperx[83].end 3629.922
transcript.whisperx[83].text 我希望你們還是可以稍微把你們這些在就業的人或是初次就業的人要稍微分層一下不然你們永遠找不出這些問題在哪裡好謝謝陳委員接下來我們請盧憲一委員
transcript.whisperx[84].start 3656.48
transcript.whisperx[84].end 3656.78
transcript.whisperx[84].text 有請部長請許部長
transcript.whisperx[85].start 3667.762
transcript.whisperx[85].end 3684.396
transcript.whisperx[85].text 大概查了資料就是在投資青年就業方案這個部分大概在3年的時間花了133億可是我們的整體的青年的失業率還是在超過兩倍未達預期目標請問部長這問題出在哪裡
transcript.whisperx[86].start 3687.159
transcript.whisperx[86].end 3705.779
transcript.whisperx[86].text 報告委員我們剛剛講的那個是第一期的投資青年就業方案因為全世界都一樣青年的失業率都高於全體國人的這個失業率那過去我記得數據曾經到10點12%所以我們其實在推第一年的投資
transcript.whisperx[87].start 3708.564
transcript.whisperx[87].end 3725.759
transcript.whisperx[87].text 投資青年方案之後這個失業率是有降下來而且我們從10.76降到8.38跟委員報告這中間還報告三年的疫情喔照理說如果疫情的時候其實可能青年失業率會更高但是我們反而是這樣我們有好幾個計畫
transcript.whisperx[88].start 3730.063
transcript.whisperx[88].end 3757.178
transcript.whisperx[88].text 好我們有在學的離校的各種計劃就針對15到29歲的青年所以我們的目標是要兩倍以內嗎對不對目標是這樣當初是希望但是委員因為也碰到疫情所以這個請委員特別能夠來理解在原住民的一些教育訓練方面連續大概1234年的部分他的最主要他
transcript.whisperx[89].start 3758.138
transcript.whisperx[89].end 3782.517
transcript.whisperx[89].text 不滿意的就是他的無法配合到執訊上課的時間也是說這4年裡面永遠問題第一名都是這個那既然都是這個的話為什麼不去調整上課的時間呢為什麼一直都是第一名報告委員我記得好不好我這個我可以來再瞭解我記得我們各分署會針對我們原住民的
transcript.whisperx[90].start 3783.464
transcript.whisperx[90].end 3811.892
transcript.whisperx[90].text 那個老公朋友會有專班專班的職業訓練所以應該他的上課時間我在想應該大部分都是6日對不對我在想啦我不知道這個沒關係對可是因為既然沒有辦法配合的話你應該要調整那個上課時間這個會報告委員這個我來請齁同源他們來做改善第二個也是蠻高的就是沒有想要參加的課程所以你是不是應該先做一個類似像調查他們想要上什麼課才開那樣的課
transcript.whisperx[91].start 3812.552
transcript.whisperx[91].end 3818.257
transcript.whisperx[91].text 目前公部門他有些應該是應該要足以運用原住民的他還是有一些地方是缺15還有缺16的這個部分希望你能夠去了解為什麼他們沒有辦法達到好不好
transcript.whisperx[92].start 3843.601
transcript.whisperx[92].end 3864.342
transcript.whisperx[92].text 好,這個我來瞭解一下,我請同仁來瞭解目前做得最好,全國做得最好是桃園市就原住民就業這個部分那我希望如果你覺得桃園市現在的數據是桃園市最好的話你們應該去參考桃園市是怎麼做的然後再推廣到全省這樣,可以嗎?可以,會後來瞭解
transcript.whisperx[93].start 3865.92
transcript.whisperx[93].end 3894.868
transcript.whisperx[93].text 現在一直在做多元就業開發方案也就是說希望留住在地的青年來培育我們或者是中老年的一些在地就業目前我看到的一個比較好的一個是叫沙老部落我們這樣念他的主語叫沙道我看到的是他原本是沒有一個遊客可以造訪那個地區經過他們的努力一年可以超過400人也就是說可能就產生一些超過60萬台幣的一個產值就可以養活在地的人
transcript.whisperx[94].start 3895.128
transcript.whisperx[94].end 3909.531
transcript.whisperx[94].text ﹏﹏﹏
transcript.whisperx[95].start 3909.864
transcript.whisperx[95].end 3929.576
transcript.whisperx[95].text 那我們最後來萬美指可一下目前南韓的那個最低薪資是在OECD的排名是這樣子是在不是在前面是在等於是在十幾名如果這樣子看12345678913名那13名的最低薪資遠高於我們
transcript.whisperx[96].start 3930.762
transcript.whisperx[96].end 3931.463
transcript.whisperx[96].text 報告委員我們其實去年年底已經
transcript.whisperx[97].start 3947.063
transcript.whisperx[97].end 3957.83
transcript.whisperx[97].text 通過最低工資法那未來我們在最低工資的審議的時候會有專家先提出研究的報告那勞資政學雙方也會在討論的時候會斟酌各種這個
transcript.whisperx[98].start 3962.813
transcript.whisperx[98].end 3987.89
transcript.whisperx[98].text 這個我們的數據啦吼相關的一些我給你看一下南海是295元那個南海的消費水準讓我們三倍是啦那不過我們不會看這個我們還是看數據嘛對對對啊我們的我們現在像我們的時薪是到183吶吼那就是以我們消費水平跟南海的比較我們應該不會比較厲害他們的薪資已經到達這樣的一個程度他們的醫生還要罷工
transcript.whisperx[99].start 3988.69
transcript.whisperx[99].end 4007.749
transcript.whisperx[99].text 那如果說我們相對就我們這樣的心智的話我們是不是應該都有罷工的權利我希望還是省省的思考一個機制這個提升勞工的心智是我們一直要努力的目標我們會持續來努力那我們再做一些先進國家的一個年收入跟月收入一個比較
transcript.whisperx[100].start 4009.693
transcript.whisperx[100].end 4026.14
transcript.whisperx[100].text 而在這裡面只有新加坡有在這個比較下面的排名也就是說新加坡的一個如果是就月收入來說已經到達5600美金是目前我們台灣如果換算台幣的話是17萬這是他平均的
transcript.whisperx[101].start 4026.8
transcript.whisperx[101].end 4045.844
transcript.whisperx[101].text 獲得的收入不是最高跟最低所以我們還是要檢討我們為什麼國內的收入是普遍低於我們之前可以相並比的四小龍可以嗎親自的提高其實跨部會大家一起來努力本以各自的選擇來朝這個目標來邁進
transcript.whisperx[102].start 4057.694
transcript.whisperx[102].end 4086.324
transcript.whisperx[102].text 我因為還有一點時間我還是希望能夠講一下職業安全的部分那因為在我們知道在桃園尤其是很多工廠的地方有沒有想過如果當時如果發生一些比如說工廠的爆炸啦或者是一些重大的一些職業災害啊有沒有在地可以處理的一個醫療院所因為基本上我知道如果說像桃園的福地也蠻大的如果說全部送到林口常科醫院的話
transcript.whisperx[103].start 4087.344
transcript.whisperx[103].end 4116.203
transcript.whisperx[103].text 那可能會爆量或者是我們所謂的不利桃園醫院所以在沿海地區的一些緊急救治的一些傷患的一些急救站你們有沒有考慮過說要去設置因為它的工廠的密度非常高所以你們在規劃的時候是不是應該要去想說為了防範以後發生的重大意外那你在後送的時候或是緊急處理的時候是不是有一個相對的一個治療點你們有沒有在這樣想
transcript.whisperx[104].start 4116.983
transcript.whisperx[104].end 4131.93
transcript.whisperx[104].text 有有報告委員我們其實現在就是有陸續建置我們的那個整治的專者醫院還有我們的那個網絡醫院那個就是說要真讓用幾公里算還是用幾分鐘算
transcript.whisperx[105].start 4132.89
transcript.whisperx[105].end 4148.902
transcript.whisperx[105].text 好應該是要有一個數據來出來讓我們讓我們的老公朋友能夠安心可以嗎就是盡量進變啦就是我們鼓勵像網絡醫院我們盡量把它擴大就是有有意願要來加入網絡醫院的我們都對那你建制好以後你建制好應該要
transcript.whisperx[106].start 4149.462
transcript.whisperx[106].end 4175.213
transcript.whisperx[106].text 獲獲獲
transcript.whisperx[107].start 4178.097
transcript.whisperx[107].end 4193.495
transcript.whisperx[107].text 謝謝盧憲宜委員接下來請邱政軍委員好我們有請部長請許部長
transcript.whisperx[108].start 4198.737
transcript.whisperx[108].end 4226.755
transcript.whisperx[108].text 邱委員好部長我請問一下上週本席才關心過我們勞保2028破產的問題是那我這幾天又看到頭版我們勞保精算出負債13兆465億那我也看了您的這個業務報告根據研議勞工保險財務危機改善因應對策這句話是什麼意思準備有做什麼準備嗎
transcript.whisperx[109].start 4227.793
transcript.whisperx[109].end 4230.154
transcript.whisperx[109].text 我想問的是你這個對策是什麼?
transcript.whisperx[110].start 4254.707
transcript.whisperx[110].end 4268.228
transcript.whisperx[110].text 我們的對策第一個報告委員我們現在當然就是費率的調整我們每兩年調一次還有這個保費的一個收取也要強化另外就是說我們的那個
transcript.whisperx[111].start 4270.05
transcript.whisperx[111].end 4283.777
transcript.whisperx[111].text 幾副審核要確實從部長上任然後另外就是撥補報告員撥補的部分是目前各界有共識的所以這部分我們先做所以從2020到現在你一直撥補錢從哪裡來
transcript.whisperx[112].start 4288.484
transcript.whisperx[112].end 4316.61
transcript.whisperx[112].text 就是政府編列預算公務預算撥補另外還有個特別預算我覺得你們應該要有一個好的一個政策出來吧一個方案出來這樣用撥補的永遠都是在撥補那要補到什麼時候那個報告委員其實調整的方向這個就是不會只有撥補這個部分那當然還有其他方面像要來因為這個問題已經講了很久了我希望我們到現在還沒有看到一個具體的做法
transcript.whisperx[113].start 4318.471
transcript.whisperx[113].end 4341.163
transcript.whisperx[113].text 只是說我們會研議改善因應對策那講了那麼久那所謂的政策是什麼我希望部長這邊給我一個明確的說明好嗎好因為我們這樣看齁我們目前看起來只是暫時不會餓死也不會馬上爆發但是長久下來這個問題還是存在的
transcript.whisperx[114].start 4344.096
transcript.whisperx[114].end 4359.665
transcript.whisperx[114].text 部長認同我的說法嗎那是不是我們應該在這個時候還有時間我們盡快來處理這個問題包括你這個問題是一定要處理不過就是我剛剛講的這個是一個蠻複雜的工程包括各個勞資團體包括各政黨大家可能對調整的方向調整的面向可能大家還是要有一些溝通
transcript.whisperx[115].start 4370.511
transcript.whisperx[115].end 4390.281
transcript.whisperx[115].text 然後有一定的共識這樣要推可能會比較順因為在我看到這個報告我們自己勞動部精算過2039年以後勞保將會達到這個給付的高峰每年都要給付超過一兆如果是這個而且連續30年你認為我們勞退基金不會破產嗎
transcript.whisperx[116].start 4391.633
transcript.whisperx[116].end 4404.934
transcript.whisperx[116].text 老保老保老保不會破產嗎因為財務的問題啊吼的確就是要去面對了吼那所以但是這個也是政府辦的保險吼政府一定會負起給付的責任不過
transcript.whisperx[117].start 4406.515
transcript.whisperx[117].end 4429.096
transcript.whisperx[117].text 財務的問題一定要是解決了那當然我們現在我剛講目前波普只是先踏出第一步而已那其他的面向還要去做檢討所以部長一直講說波普波普那波普就是我們的一種改革是嗎波普怎麼會是改革呢波普是調整的面向之一因為我們本來在原來的
transcript.whisperx[118].start 4430.748
transcript.whisperx[118].end 4431.168
transcript.whisperx[118].text 你覺得撥補要補多少才會平啊?
transcript.whisperx[119].start 4455.173
transcript.whisperx[119].end 4461.74
transcript.whisperx[119].text 當然這個要看整個基金的餘有狀況還有政府的財政狀況希望部長這邊能夠有一個具體的說法跟做法那什麼時候可以給我資料我們一個月提個報告給您
transcript.whisperx[120].start 4478.215
transcript.whisperx[120].end 4498.861
transcript.whisperx[120].text 再來第二個問題我們民洋大火燒出了很多的問題那去年9月我們部長也承諾一個月決議是不是要收回我們產業園區的這個勞檢權那後來周署長也說涉及這個範圍很廣還是要跨部會討論那大概今年初會進一步討論那目前的進度在哪裡
transcript.whisperx[121].start 4500.849
transcript.whisperx[121].end 4516.863
transcript.whisperx[121].text 這個行政院有邀集相關部會討論過目前是還沒有這個決定收回的這件事情但是有要求督導的這個機制要更確實然後有關於這個
transcript.whisperx[122].start 4518.865
transcript.whisperx[122].end 4523.088
transcript.whisperx[122].text 那我這樣講,如果要說回勞安檢查權,勞動部有沒有盤點過說需要修改的法規有多少?很多,非常多那會不會有困難?
transcript.whisperx[123].start 4540.482
transcript.whisperx[123].end 4541.182
transcript.whisperx[123].text 我請署長說明一下
transcript.whisperx[124].start 4561.222
transcript.whisperx[124].end 4568.245
transcript.whisperx[124].text 好了我希望勞動部能夠積極一點該收回就要收回那或者是採取用合作的模式研議我們具有可行性的方案來確保我們產業園區和科學園區裡面的工業安全衛生這樣可以嗎?好
transcript.whisperx[125].start 4589.178
transcript.whisperx[125].end 4612.872
transcript.whisperx[125].text 那我再問我們非典型勞工要保障這個問題跟訴求其實已經很多年了那我們的賴清德準總統也說過面對臺灣非典型勞工占比已經達到15%了那要強化非典型勞工在薪資工時休假保障等基本勞動權利給予更周延的保障那部長這邊有討論過這個問題嗎過去有
transcript.whisperx[126].start 4618.554
transcript.whisperx[126].end 4644.075
transcript.whisperx[126].text 這個部分有關於非典勞工尤其像外送員的部分的權益保障其實一直也是勞動部非常關注的工作重點然後這個部分我們其實在勞動部部分首要從他的權益的安全還有他的薪酬的一個這個權益的這個保障還有包括他的保險我們從這三方面去做
transcript.whisperx[127].start 4645.676
transcript.whisperx[127].end 4649.979
transcript.whisperx[127].text 一切規劃,那我們也建制他們外送平台跟外送員的對話平台
transcript.whisperx[128].start 4675.556
transcript.whisperx[128].end 4678.578
transcript.whisperx[128].text 謝謝主席我們請部長
transcript.whisperx[129].start 4700.386
transcript.whisperx[129].end 4720.231
transcript.whisperx[129].text 部長好部長我今天也是要跟部長討論這個移工的政策啦那前陣子我們看到這個剛結束奧斯卡的頒獎典禮那我們看得到就是說很多電影都是反映現實那有一部電影這個復讀青年我不知道部長有沒有看過
transcript.whisperx[130].start 4720.991
transcript.whisperx[130].end 4749.534
transcript.whisperx[130].text 我沒有看過那個我有看稍微看一下大家知道嗎那這個這個背景是在馬來西亞的副都那這個也是反映就是移工移工在當地的一個生活狀況那我們看到就是說在反映到臺灣這邊我們看到就是監察院在去年也有發表一本書就是說一群在臺灣沒有身份的人移工為什麼要失聯那我不知道部長
transcript.whisperx[131].start 4750.575
transcript.whisperx[131].end 4761.645
transcript.whisperx[131].text 你有看過嗎這本書監察院這本有載入重點有載入重點那我想說藉由今天的這個質詢希望部長針對我們現在所面臨的這個問題就是失聯的移工到目前為止有8萬多人
transcript.whisperx[132].start 4772.895
transcript.whisperx[132].end 4798.862
transcript.whisperx[132].text 當然部長你有特別提到就是說要鼓勵就是我們鼓勵合法的聘僱放寬機構看護移工等等的做法來改善移工失聯的這個狀況可是我們從監察院的這一本書當中他就提出說移工他在工作中可能遭逢危機或者是求助無門所以只好選擇合法的僱主另謀生路
transcript.whisperx[133].start 4799.702
transcript.whisperx[133].end 4818.298
transcript.whisperx[133].text 所以我這個我們勞動部跟這個監察院的這個看起來好像互相矛盾我想請教就是勞動部針對這個部分就是說有沒有什麼樣補充說明或者是我們的跨部會合作怎樣來改善這個移工失聯的這個做法
transcript.whisperx[134].start 4818.638
transcript.whisperx[134].end 4839.499
transcript.whisperx[134].text 其實報告委員移工失聯問題那個原因很多啦吼像這邊嚴建山說低薪又滅勞我們講的這個部分當然是其中之一啦吼包括說也說經濟因素啦或者他勞動環境等等這個也都是有那其實在院裡面針對這個問題其實都是召集跨部會在做討論就是說這個對策戰尤其像
transcript.whisperx[135].start 4842.342
transcript.whisperx[135].end 4857.825
transcript.whisperx[135].text 過去3年的疫情造成整個移工失聯人數飆升所以到底要如何把它降下來我們也在前年其實開了好幾次的這個跨部會的會議所以去年是有降下來是 去年有降了從1.96降下來
transcript.whisperx[136].start 4858.206
transcript.whisperx[136].end 4870.011
transcript.whisperx[136].text 部長你之前說就是鼓勵合法的聘僱然後就引進譬如說這個農業移工需要可能一些更多的這個移工進來幫忙那你們這邊也樂觀其成也開放那可是這樣子的話確實有減少這樣的移工的這個失聯的這個狀況嗎有這個有幫助
transcript.whisperx[137].start 4877.994
transcript.whisperx[137].end 4904.775
transcript.whisperx[137].text 其實報告委員因為我們適度的就是把這個名額增加了其實農業外勞農業移工是從那個疫情前我們的6000放到12000放到12000那包括很多失點移工他會跑到民間的營造業過去沒有開放的我們去年也開了所以我覺得合法的聘僱會讓失點的人數因為他可以合法聘僱我想僱主也不要冒險他也不願意去冒險所以
transcript.whisperx[138].start 4906.837
transcript.whisperx[138].end 4934.113
transcript.whisperx[138].text 將來這個我想這個合法的移工能夠引進之後那再加上我們現在疫情的趨緩的整個邊境管制都解除都可以正常進來我想整個移工失聯的狀況應該會再陸續的降下那針對監察院的這一個報告裡面他還有寫低薪又虐勞那如果真的後面這個狀況的話心知的部分那個報告員主要是家庭家庭的看護工他因為他
transcript.whisperx[139].start 4934.873
transcript.whisperx[139].end 4954.134
transcript.whisperx[139].text 家庭剛剛不適用勞基法其實本國的家庭剛剛一樣也不適用勞基法本國本外籍的勞工通通是平等待遇所以過去只有一萬七所以在前年我們也把它調升到兩萬讓它能夠跟市場的行情比較一致
transcript.whisperx[140].start 4957.136
transcript.whisperx[140].end 4984.802
transcript.whisperx[140].text 這也是慢慢的去解決低薪的問題那當然那還有這個休假的部分過老因為看護工確實24小時所以我們有這個喘息服務我們有喘息服務我們現在他家庭的看護工他一年可以52次就有52天的休息時間那配合喘息服務這個經費都是勞動部支持的所以就是希望能夠改善這個
transcript.whisperx[141].start 4986.042
transcript.whisperx[141].end 5013.82
transcript.whisperx[141].text 而勞工的這個移工的這個呃過勞的情形吼那再來就是說當然那個虐噢虐勞的問題吼雇主不當對待我們也強化吼檢舉吼我們1955專線也讓我們的移工透過多元的宣傳管道用不同的語言讓他們知道包括現在一再式的服務中心一進來我們就會告訴他你的勞動權益你怎麼求助你的申訴管道通通讓他們知道我想這樣會降低這個吼虐待的一個情勢啦
transcript.whisperx[142].start 5014.821
transcript.whisperx[142].end 5043.852
transcript.whisperx[142].text 其實我們看到臺灣不論是產業移工或者是我們這個家庭看護移工其實他們到臺灣來一方面也是這個滿懷著憧憬希望到這個環境來就是最主要也要賺錢嘛那改善他們母國的可能這個整個經濟狀況那我們希望就是說他來到臺灣整個工作的環境也許需要這個我們這個雇主還有政府這邊要互相
transcript.whisperx[143].start 5044.432
transcript.whisperx[143].end 5047.654
transcript.whisperx[143].text 我相信我們大部分的僱主都是善待移工的啦但是
transcript.whisperx[144].start 5072.867
transcript.whisperx[144].end 5090.499
transcript.whisperx[144].text 也不好還是有些人吼對這個這個我們的移工沒有很吼這個合理的對待吼甚至虐虐待吼我覺得這都不應該啦我覺得說大家可能在心態上觀念上要做一些改變吼就是說雇主你應該他來當然是要賺錢沒有問題但是他也
transcript.whisperx[145].start 5091.239
transcript.whisperx[145].end 5115.697
transcript.whisperx[145].text 幫忙你不管是家庭的一些照顧等等我們應該是一個感恩的心把它當一個家人這樣對待我相信就不會有虐待的問題再來就是在勞動部的部分我們就是透過我們的家庭訪視我們那個訪有訪視員訪查員我們各地方政府我們補助他訪查員就是加強訪查再來就是移工很重要受到虐待他一定要申訴他一定要勇敢站出來
transcript.whisperx[146].start 5116.477
transcript.whisperx[146].end 5137.848
transcript.whisperx[146].text 你聲述我們一定會查辦到底,一定絕不寬待,用這樣的方式去阻止這個虐待移工的情勢來一再的發生其實我會覺得說這個產業移工的部分可能還沒有那麼嚴重那我覺得說這個看護工的部分是比較嚴重的一個問題
transcript.whisperx[147].start 5139.088
transcript.whisperx[147].end 5166.577
transcript.whisperx[147].text 對因為第一個就是說薪資可能跟廠工比起來是有一些落差那另外廠工的話他還有工作可能8小時之後是加班就是可以加班嘛有加班費那這個看護工的話他可能也沒有這樣的一個加班費可以請領所以有很多看護工其實他一段時間之後他可能有的會受到一些影響可能有的就逃跑那我們當然就是說這個
transcript.whisperx[148].start 5168.437
transcript.whisperx[148].end 5196.574
transcript.whisperx[148].text 看護工的話其實未來也是我們很重要的一個看護的一個長道一個很重要的一個主力因為很多家庭他確實需要這樣子看護移工來幫忙所以我們也希望就是說從政策方面能夠讓這些這個看護移工到台灣來他一方面雖然說薪資可能跟長工還是有一些落差可是如果說他的整個工作環境有改善的話我覺得他還是會願意
transcript.whisperx[149].start 5198.595
transcript.whisperx[149].end 5210.999
transcript.whisperx[149].text 來擔任我們這樣的一個非常重要的一個整個長照體系其中的一環所以我也希望就是說勞動部可能跟各部會還是要繼續努力尤其是監察院這樣寫我都覺得說這個
transcript.whisperx[150].start 5213.96
transcript.whisperx[150].end 5214.861
transcript.whisperx[150].text 謝謝防洩網委員的諮詢謝謝部長的答詢
transcript.whisperx[151].start 5244.15
transcript.whisperx[151].end 5262.061
transcript.whisperx[151].text 謝謝接下來請蘇清泉委員謝謝主席我請部長跟老安老安署長請子安署啦對不起子安子安署子安署蘇委員好
transcript.whisperx[152].start 5267.813
transcript.whisperx[152].end 5273.457
transcript.whisperx[152].text 副部長,你是屏東人,屏東人口80萬,內地農民就要38萬,其他就是勞工
transcript.whisperx[153].start 5282.526
transcript.whisperx[153].end 5301.711
transcript.whisperx[153].text 我們勞工我不覺得勞動部對屏東有什麼好部長這個你要反省一下我今天要講的是你們大家都忘了但是這件事情就是民養大活那個時候吵得灰灰洋洋但是現在去年9月我來喚起大家的
transcript.whisperx[154].start 5308.613
transcript.whisperx[154].end 5334.753
transcript.whisperx[154].text 不要攻擊完就忘記了十條人命九十幾個人受傷我們都參與在裡面救救人那我要這裡要講的是冰凍關的職災的發生率是全台灣第一名4.196台灣的平均是2點多這個我們史蘭史林族在做事情嗎
transcript.whisperx[155].start 5339.492
transcript.whisperx[155].end 5339.695
transcript.whisperx[155].text 然後
transcript.whisperx[156].start 5343.03
transcript.whisperx[156].end 5370.651
transcript.whisperx[156].text 這個10條的命令有4個是我們的消防員那這消防員我們去跟他去給他衛護跟侯友宇去的時候那家屬緊緊的拉著我的手說希望我們幫他們的忙不要下一個受害者那現在有一個問題就是我們治安署這邊是用職業安全衛生法嘛對吧那這是公務人員消防隊員是用公務人員安全防護辦法
transcript.whisperx[157].start 5372.509
transcript.whisperx[157].end 5382.305
transcript.whisperx[157].text 這個辦法什麼都不是嘛,也不是法,這是根據那些細節啦,訂出來的規範啦,辦法。這個你有,部長你有辦法介入嗎?這個很重要喔。
transcript.whisperx[158].start 5386.23
transcript.whisperx[158].end 5409.243
transcript.whisperx[158].text 這個報告委員其實這個大火發生以後那個行政院都有召集相關的部會那從彼此的權責去看怎麼樣強化未來的這些防災的管理不要讓這樣一個悲劇再次的發生所以我們自己部會像那個我們就是消防員的部分我們就是
transcript.whisperx[159].start 5410.564
transcript.whisperx[159].end 5432.532
transcript.whisperx[159].text 就是他的防護就是由內政部消防法在消防法裡面去參考我們一些職我們職災保險或者我們的那個職安法的相關的規範去做職安的專章這部分是有責成行政院有責成內政部要去把法治完善所以他們的裝備武器裝備保養
transcript.whisperx[160].start 5434.733
transcript.whisperx[160].end 5459.548
transcript.whisperx[160].text 阿他人生阿人生我覺得我們職安署做的比這個公家單位做的公務員這邊還好捏職安署謝謝委員的那個的這個垂詢因為有關消防法消防隊員確實在我們的國家法制裡面他的安全是依照公務員安全的防護辦法來辦理但是其實有特別指示因為這次民營大火之後有關消防隊員職安的部分
transcript.whisperx[161].start 5460.188
transcript.whisperx[161].end 5475.01
transcript.whisperx[161].text 有明確的指示要求由內政部由在那個消防法裡面定職安專章職安專章的法條目前消防署來找我們職安署提供我們提供的建議條文的內容給他們參考那邏輯上就是消防隊員的職業安全他做
transcript.whisperx[162].start 5475.49
transcript.whisperx[162].end 5502.087
transcript.whisperx[162].text 封寫評估控制再救災跟我們執安法保障保障給那邊多一點啊你看多少個消防弟兄沒命去放啊發聲啊屏東這個大家受不了十幾個家庭破碎啊受傷的九十幾個現在在補皮啊還在復健啊那這個這個這個你說有執安的工廠地圖我看屏東
transcript.whisperx[163].start 5507.544
transcript.whisperx[163].end 5516.919
transcript.whisperx[163].text 但是我今天早上看Google有名揚這個公司在但是我們的職安地圖裡面居然沒有名揚欸
transcript.whisperx[164].start 5519.833
transcript.whisperx[164].end 5520.833
transcript.whisperx[164].text 好,你看屏東縣的治安地圖那個那個一點一點那個
transcript.whisperx[165].start 5548.236
transcript.whisperx[165].end 5551.038
transcript.whisperx[165].text 有在close follow up
transcript.whisperx[166].start 5575.916
transcript.whisperx[166].end 5578.439
transcript.whisperx[166].text 民洋因為全世界的高爾夫球的球感台灣做了30%那全世界的高爾夫球的球台灣做了將近30%
transcript.whisperx[167].start 5596.403
transcript.whisperx[167].end 5616.067
transcript.whisperx[167].text 台灣就是六家在搬啦 六家都有互相交叉 所以民營他沒做 其他就也不如何啊 也不差啊民營這個出事了 我是覺得很糟糕的就是他這個董事長是台大發公室的喔 台大發公室真的是 聲報夠賣欸
transcript.whisperx[168].start 5619.926
transcript.whisperx[168].end 5646.899
transcript.whisperx[168].text 一個高級的球心是順勢丁二溪然後一些coating一層一層coating上去那個球那個是全部都是粉塵類的然後裡面還有鋰碰到所謂的爆炸那裡面的顏料跟TNT炸藥我當海軍陸戰隊我跟你講跟TNT炸彈是炸藥是一模一樣那這個廠商廠他把
transcript.whisperx[169].start 5648.25
transcript.whisperx[169].end 5676.655
transcript.whisperx[169].text 儲存的場 儲存的地方 跟製造的地方 跟辦公室 都要合作一下 有這麼要事的一年做三四十億 一年賺五六億 改善那些工作 我都去現場看 看我很痛心去一年要開五六千萬 就改善了 都改善了 結果又不改善這是很糟糕的事情 那我現在要強調的是這些東西等於坐在炸藥上在做東西
transcript.whisperx[170].start 5677.645
transcript.whisperx[170].end 5705.16
transcript.whisperx[170].text 那其他的5家你們有去查嗎這個是更嚴肅的問題喔我們第一時間就有盤整有關這個原料我們有的特別是用有機過氧化合物的那個事業單位我們在去年年底做做出查複查做檢查如果有要提供可以處分的案件來執行那針對這種列管的高危險的事業單位其實我們建設民營齁董事長是台大化工系他明明知道那種東西他那麼可怕的齁
transcript.whisperx[171].start 5706.722
transcript.whisperx[171].end 5724.402
transcript.whisperx[171].text 隨時會爆炸的他都這樣幹了那其他都富盛齊坤大田齁大田齁糟糕的齁巨民民安這都互相交叉這些都這些這些場會會做得好我不相信啦所以齁我現在是要求部長跟署長你那天強力的稽查
transcript.whisperx[172].start 5726.204
transcript.whisperx[172].end 5753.242
transcript.whisperx[172].text 平東關這都掃一百個 這個化工廠都掃一次screen一次 高雄人家好像有做了 平東沒有做 我們縣政府有沒有這個能力我不知道 但是我對你主要是 我還有信心的阿部長 這很重要的 所以都去查一遍 所有平東關有的化工廠都去查一遍 尤其是這個做這麼高危險高爆炸的這種東西 絕對絕對 人命關天阿
transcript.whisperx[173].start 5756.584
transcript.whisperx[173].end 5758.346
transcript.whisperx[173].text 謝謝委員提醒我們會做專案檢查
transcript.whisperx[174].start 5787.701
transcript.whisperx[174].end 5794.763
transcript.whisperx[174].text 請許部長都委員好
transcript.whisperx[175].start 5807.928
transcript.whisperx[175].end 5833.859
transcript.whisperx[175].text 部長本席也是來自我們桃園的立委因為我們桃園現在是一個移工的城市全台灣我們外籍移工裡面有六分之一的都選擇在桃園所以我們現在桃園大概外籍移工就超過11萬桃園也是一個移民的城市目前桃園針對我們外配的比例在去年
transcript.whisperx[176].start 5834.939
transcript.whisperx[176].end 5861.876
transcript.whisperx[176].text 這個比例已經達到我們超越新北已經達到第一所以這一陣子收到很多越南印尼很多我們外籍新住民群體針對他們相關就業跟職業訓練的部分有提出一些問題那剛好今天來請教一下部長跟我們署長請問一下那個部長大概知道我們去年112年我們新住民人數大概有多少
transcript.whisperx[177].start 5863.231
transcript.whisperx[177].end 5867.253
transcript.whisperx[177].text 去年新住民的人數對沒關係這個沒關係大概跟這個部長講我們經過我們的70萬
transcript.whisperx[178].start 5875.02
transcript.whisperx[178].end 5892.499
transcript.whisperx[178].text 他是總共總共我們新住民的人數喔內政部統計喔是59萬多啦那所以他在去年的部分針對新住民喔已經超越了我們的原住民那加上如果新熱帶喔已經超過百萬人
transcript.whisperx[179].start 5893.3
transcript.whisperx[179].end 5919.362
transcript.whisperx[179].text 所以有人說去年112年可以說是新住民元年表示現在新住民在我們台灣的人口數是非常非常的多那我想針對我們這59萬多的新住民朋友請問一下我們勞動部跟勞發署有沒有針對他們就業促進服務還有措施職業信念等等有沒有針對他們來提供這些的服務有
transcript.whisperx[180].start 5920.933
transcript.whisperx[180].end 5944.363
transcript.whisperx[180].text 我們有定一些計畫還有那個作業的要點還針對新住民的這個職業訓練啊就業媒合好等等都有提供相關的對那就是針對我們促進新住民我有看過我們有促進新住民作業補助作業要點好那當然也針對新住民也開了一些專班
transcript.whisperx[181].start 5945.603
transcript.whisperx[181].end 5970.769
transcript.whisperx[181].text 當然表示我們勞動部在這一方面還是有在努力可是我們今天要講的重點說當然我們原住民的部分當然我們也需要照顧那現在新住民的部分人口數也這麼多那但是他的就業服務法裡面針對特定對象跟就業弱勢者這個母法裡面並沒有對他有特別的照顧所以我想說
transcript.whisperx[182].start 5972.504
transcript.whisperx[182].end 5985.117
transcript.whisperx[182].text 這一部分我們599萬多裡面因為這裡面我們發現有一些缺失59萬多裡面我們大概有14萬多超過20%的部分是我們這個要點沒有辦法照顧到的
transcript.whisperx[183].start 5990.441
transcript.whisperx[183].end 6005.009
transcript.whisperx[183].text 那就是說我們這些外配啊當他規劃成為我們中華民國國民之後他這些你們公佈的這些作業的要點就不能照顧到他
transcript.whisperx[184].start 6005.709
transcript.whisperx[184].end 6028.139
transcript.whisperx[184].text 那這裡面我們目前大概有21萬多的外配就是印尼馬來西亞菲律賓越南等等這些外配他有20萬人但是他規劃之後就這些要點就沒有辦法照顧他這個比例非常高大概有七成所以想說針對我們這部分
transcript.whisperx[185].start 6030.82
transcript.whisperx[185].end 6057.516
transcript.whisperx[185].text 是不是我們有注意到這一部分因為有很多的他們反映結果規劃以後應該福利更好結果他規劃以後反而這些沒有照顧到他像我們很多的新住民的專班職業訓練津貼等等所以變成他們到時間到以後他可以領身份證他反而要考慮了所以我不知道說我們勞動部針對這一部分有沒有注意到
transcript.whisperx[186].start 6058.196
transcript.whisperx[186].end 6084.137
transcript.whisperx[186].text 我這個部分來做一個回答其實跟委員報告這個我們的新住民他規劃以後他就是我們的國人他所有的這些就業就適用我們就業服務法相關的權益都是依照就業服務法所以是ok的沒有問題我們現在就業服務法是針對國人因為新住民不適用我們才另外訂一個新住民的補助所以剛好因為這我們也有研議到
transcript.whisperx[187].start 6084.898
transcript.whisperx[187].end 6108.874
transcript.whisperx[187].text 因為新住民其他加入勞保農保的比例其實非常低大概只有五成那所以這個新住民他到時候加入這個就業保險法的比例我們絕對不是很樂觀而且他這裡面有四分之一的像自營作業無酬家屬的工作者還有雇主的身份這些是完全照顧不到的
transcript.whisperx[188].start 6109.474
transcript.whisperx[188].end 6127.736
transcript.whisperx[188].text 瓜哥委員因為他規劃以後他就是本國人了所以他就所有的他就比如說他如果受雇勞工他就是勞救保他的雇主就要幫他投保他如果是自營作業者或無一定雇主那他可以加入職業工會我們今天的重點就是說
transcript.whisperx[189].start 6128.797
transcript.whisperx[189].end 6144.467
transcript.whisperx[189].text 就是因為他們有提出就是說他規劃以後其實他的各方面的照顧福利反而是低的所以所以你們去研議一下他說可以領身份證的時候反而要考慮所以我覺得這也很奇怪再來講規劃成為國民應該是好的
transcript.whisperx[190].start 6147.229
transcript.whisperx[190].end 6164.309
transcript.whisperx[190].text 結果他認為說可以領身份證反而規劃以後各項福利是差的所以他可以領身份證反而考慮不要領所以我覺得說就像我們蔡英文總統這個新南向政策希望我們這新住民融入我們的台灣的社會那今天有這個要點
transcript.whisperx[191].start 6165.81
transcript.whisperx[191].end 6187.744
transcript.whisperx[191].text 反而針對這些規劃以後他們覺得反而成為國民以後各項的福利補助反而減少所以我就希望我們勞動部針對這一部分你們可能要去研議一下可能這個我覺得有一些可能有疏漏所以今天我們會提案修正促進新住民就業補助作業要點
transcript.whisperx[192].start 6188.704
transcript.whisperx[192].end 6217.129
transcript.whisperx[192].text 需要放寬適用規劃的外國人還有要求勞動部要進行年度新住民就業狀況的檢查因為我們針對這個原住民的部分就業調查我們每一季做一次可是針對新住民我們是五年做一次所以我覺得這五年做一次可能針對整體新住民現在人口這麼眾多五年做一次可能沒有辦法確實的掌握他們的狀況
transcript.whisperx[193].start 6218.549
transcript.whisperx[193].end 6233.299
transcript.whisperx[193].text 還有我們原住民現在有原住民基本法可是新住民現在只有作業要點還有救福法的服務對象針對這些部分我們希望來研議一下針對這部分我們注意一下看是不是有機會來加強還有我請問一下我們部長我們當初有講2028我們勞保說我們這個會基金會破產
transcript.whisperx[194].start 6248.164
transcript.whisperx[194].end 6263.991
transcript.whisperx[194].text 那當初我記得2020年我們部長也有講當然上來你就希望來做那個勞保的年改那可是當初你說上來的時候要做這個年改可是這4年過去我想請問一下你的改革方案在哪裡
transcript.whisperx[195].start 6264.865
transcript.whisperx[195].end 6280.211
transcript.whisperx[195].text 報告委員其實那個因為勞保年改的部分會牽涉到千萬勞工的權益還有也涉及到60萬的投保單位所以這個部分其實各方的意見都不同因為我們有一些調整的方向
transcript.whisperx[196].start 6282.793
transcript.whisperx[196].end 6300.609
transcript.whisperx[196].text 因為我們現在擔心啊你說2028會破產啊我們是那個110年做的精算報告今年還會再做一次啦我們每三年做一次這是給政府一個參考說推估我們的基金用慶的時間點但是我跟委員報告就是說我們這幾年當然要推這個我想勞保財務的問題我們非常重視啦只是說
transcript.whisperx[197].start 6308.416
transcript.whisperx[197].end 6330.858
transcript.whisperx[197].text 我們就是有共識的先做因為我們也相信我們部長講所以很多的勞工當然也擔心2028這個會破產的問題那當然2020我們部長上任的時候也信誓旦旦說不惜丟掉無紗帽也要來做這個年改然後你在9月的時候也說要求要在年底
transcript.whisperx[198].start 6331.678
transcript.whisperx[198].end 6359.352
transcript.whisperx[198].text 勞動部要提出這個草案這個當初那個部長都有接受採訪都有說出這些可是我們發現4年過去真的還是沒有看到這改革方案那眼看著2028就要到了而且現在部長我也不知道說520部長的去留所以我現在很擔心剩下大概4年的時間我們這個勞保年改的問題我們希望能夠好好處理不要讓這些我們勞工的權益來受損
transcript.whisperx[199].start 6359.932
transcript.whisperx[199].end 6379.389
transcript.whisperx[199].text 報告委員這個方針勞動部一定會持續來努力我們現在先首要是先把勞保基金的財務讓他能夠穩定然後其他的面向我們會持續跟勞資團體各界來溝通也聽取大家的意見有關於說要怎麼來改革或者說要怎麼來推動
transcript.whisperx[200].start 6380.49
transcript.whisperx[200].end 6403.869
transcript.whisperx[200].text 這個我們有一個全盤的規劃這個不會我們一定會努力來做我們希望這個勞工這個福利權益的部分希望勞動部能夠好好的來重視好謝謝好謝謝圖全級委員那在這邊做一個宣告等一下在楊耀委員質詢結束休息10分鐘現在請王振旭委員發言
transcript.whisperx[201].start 6412.337
transcript.whisperx[201].end 6417.641
transcript.whisperx[201].text 謝謝主席有請許部長有請周署長請部長請周署長王委員好部長好署長好
transcript.whisperx[202].start 6423.522
transcript.whisperx[202].end 6446.169
transcript.whisperx[202].text 關於這個移工醫療權益的問題我們上週在質詢裡面也跟部長有討論過就是當時編輯就建議說必須要串聯跨部會的資源來進行有關於這些移工在各方面權益的這個維護那其實我們也了解資源不是沒有只是沒有妥善的整合
transcript.whisperx[203].start 6446.949
transcript.whisperx[203].end 6473.679
transcript.whisperx[203].text 那很多政策其實都已經行之多年包括像我們在三四的時候有提到針對國內事實上有4家以上的這個友善醫院針對於我們這些移工做相關的這個醫療資源的處理那這部分我們期待還能夠持續的加強那今天部長的報告裡面其實也有討論到未來怎麼去加強各方面的這些勞動人力還有移工
transcript.whisperx[204].start 6474.279
transcript.whisperx[204].end 6476.041
transcript.whisperx[204].text 那不知道未來在這方面部長有哪一些的規劃
transcript.whisperx[205].start 6493.458
transcript.whisperx[205].end 6507.148
transcript.whisperx[205].text 報告委員我先說明新南向的健康服務中心我們後來去了解他是針對國人的部分沒有包括移工而且他的項目是比較少然後有關於移工欠費的問題
transcript.whisperx[206].start 6510.931
transcript.whisperx[206].end 6528.866
transcript.whisperx[206].text 是那這個部分也在行政院也召開過跨部會的會議那我們4月對4月還在開第二次會議我那天有看到公文那就是說上一次的會議是在去年11月21開的那時候整個就是包括專家學者各部會
transcript.whisperx[207].start 6529.706
transcript.whisperx[207].end 6553.686
transcript.whisperx[207].text 大家看法是認為這個是屬於個人債務必須要要求來一個移工來源國他提供或者來建立相關的處理機制那這個部分我們會來跟來源國透過雙邊的會議來做要求那另外就是說我們目前因為大部分的來源國都比較消極處理這個問題那我們未來會規劃
transcript.whisperx[208].start 6557.649
transcript.whisperx[208].end 6557.889
transcript.whisperx[208].text 在上個禮拜
transcript.whisperx[209].start 6580.979
transcript.whisperx[209].end 6604.365
transcript.whisperx[209].text 那個時候有提到針對外國的仲介公司希望能夠針對於這些失聯移工的就醫的待葬看有沒有辦法克責那我們今天從貴部的業務報告裡面看到就是會對於這些外國的仲介會進行負擔遣返及縮容等連帶責任
transcript.whisperx[210].start 6605.805
transcript.whisperx[210].end 6625.381
transcript.whisperx[210].text 可是沒有看到在這方面能不能夠將有關的一些醫療或者是就醫過程當中的代帳也能夠做適當的處理那這部分可不可以麻煩部長能夠把相關的字眼都可以納進來好謝謝
transcript.whisperx[211].start 6628.644
transcript.whisperx[211].end 6648.161
transcript.whisperx[211].text 那再過來就是有關於這個盤點我們職業安全相關的一些如何能夠保障勞工的健康權那其實本席十分關切目前職業安全的相關規範希望在所有的勞工在進行他們的工作同時都能夠兼顧到安全跟健康
transcript.whisperx[212].start 6648.881
transcript.whisperx[212].end 6667.489
transcript.whisperx[212].text 得到應有的保障那其實我們也知道行政院在2018年就已經完成制定了這個18項的臺灣永續發展目標其中有3項包括目標3目標8目標10都跟我們的勞動勞工有很密切的關係那
transcript.whisperx[213].start 6669.95
transcript.whisperx[213].end 6692.788
transcript.whisperx[213].text 可是呢從這個過去兩年來我們看到的相關的規範除了除了大型的這些上市商會公司有比較完整的這些永續報告書以外其他的部分我們希望能夠繼續進進不過我們也看到在目前1800家左右的這些商會公司裡面有提出永續報告書的
transcript.whisperx[214].start 6694.349
transcript.whisperx[214].end 6707.931
transcript.whisperx[214].text 好像只有三分之一那這部分未來要如何來加強或者是有沒有更好的方式來讓所有的上位公司都能夠提出永續報告書如何去監測
transcript.whisperx[215].start 6709.025
transcript.whisperx[215].end 6736.055
transcript.whisperx[215].text 委員這部分我請署長來說明好謝謝謝謝委員那個有關永續的17個指標或者國家第18個指標其實我們勞動部認為說每個指標都跟我們工作者有關係所以我們勞動部跟國發會針對永續部分我們安全健康的列為我們往前推展的一個方向那至於委員關鍵是我們跟上市公司的那個報告書其實金管會針對一定規模以上的公司要寫永續報告書但報告書它的那個框架架構有關
transcript.whisperx[216].start 6736.915
transcript.whisperx[216].end 6750.617
transcript.whisperx[216].text 老公安全健康怎麼寫我們其實暫時有定一個指南供給世界單位做參考同時我每年會針對這有趣報告書有關安全安全揭露狀況好不好我們可以做神秘科的調查跟抽樣來做一些評比
transcript.whisperx[217].start 6751.263
transcript.whisperx[217].end 6775.26
transcript.whisperx[217].text 所以謝謝委員提醒其實大企業這對安全健康那雲林小企業是整個體系在展開了我們會透過永續的精神讓大企業帶小企業把勞工健康問題往下扎根謝謝委員提醒謝謝好那我們可以看下一個畫面知道說其實這個GRI403他是指標那這個指標裡面包括第三項職業健康服務
transcript.whisperx[218].start 6775.9
transcript.whisperx[218].end 6802.825
transcript.whisperx[218].text 有沒有進行相關的這些健康檢查那如何能夠讓工作者健康促進可以持續的讓這些健康工作的人得到健康的保護還有職業傷害我們可以看到不同的職類其實他接落的情形都有待加強所以剛剛署長有提到我們期待應該是各方面的職類都應該努力的來加強這部分
transcript.whisperx[219].start 6803.305
transcript.whisperx[219].end 6813.158
transcript.whisperx[219].text 非常謝謝委員 這個報告當然是我們勞動部責任署做極限調查的報告那我們發現說一年比年有稍微進步但是我們認為說有些產業它其實是比較弱的所以我們會針對我們這兩年的
transcript.whisperx[220].start 6816.599
transcript.whisperx[220].end 6837.229
transcript.whisperx[220].text 在做往後的展開特別是我們跟金管會做合作因為有些報告書的一些規範的要求是金管會為主但是我們跟他合作的時候GI403我們勞動部也出個中英文的對照指引這個也是我們後會會給委員做參考其實我們引領企業把揭露部分特別是安全健康做比較好的說明謝謝委員
transcript.whisperx[221].start 6838.51
transcript.whisperx[221].end 6866.951
transcript.whisperx[221].text 好謝謝那再過來我們可以看一下其實企業辦理勞工這個健康檢查剛剛提到是第三項的部分可是我們看到針對一些特殊的檢查健康檢查還是有蠻大的落差依照貴屬的推估目前將近有500家事實上是沒有執行相關這個勞工檢查那這些黑數是我們未來有什麼方
transcript.whisperx[222].start 6868.112
transcript.whisperx[222].end 6888.767
transcript.whisperx[222].text 法或者是對策來盡量減少這些黑數謝謝委員提醒因為我們現在按照這個世界上通報跟相關系統的嫁接我們現在全國大概6600家世界都要做特別危害健康作為檢查一般勞工是做一般健康檢查但是6600家的部分剛才委員有提醒就是我們從系統去嫁接他有沒有
transcript.whisperx[223].start 6889.557
transcript.whisperx[223].end 6906.998
transcript.whisperx[223].text 做特殊健檢之外我們後面的監督檢查會把一些高風險的拉出來另外跟委員報告我們其實去年開始做另外一個是CMR的CMR化學物質使用的一個世界單位專案檢查就是致癌致高致致毒毒害致生殖危害的這個
transcript.whisperx[224].start 6907.618
transcript.whisperx[224].end 6935.193
transcript.whisperx[224].text 我們另外500加我們做後面的追蹤檢查我們希望使用西安馬物質的事業單位他的健康風險能夠被我們做比較好的watch是 介委員好那主席我可以多2分鐘是因為我們比較擔心的是規模比較小的而且他們對於這種特殊健康檢查事實上需求是更高的所以如果能夠透過一些方法比如說從公共工程的標案啊國營事業開始做起
transcript.whisperx[225].start 6936.033
transcript.whisperx[225].end 6963.968
transcript.whisperx[225].text 除了大型的這些檢查以外那針對於臺電中有對於相關承包商的監督針對下層的這個監督可以更落實的話對於我們從事這種很辛苦的勞動人員應該可以讓他的特殊健康檢查可以得到更好的保障是那再過來就是有關於在做這個健康檢查的當中我們也了解有去
transcript.whisperx[226].start 6964.929
transcript.whisperx[226].end 6987.081
transcript.whisperx[226].text 看執行這些健康檢查的醫療院所是不是在他都能夠有效的執行相關的內容那我們可以看到的就是根據去了解這些醫療機構發現他們得到的相對分數是低的很多是C跟D的等級那C跟D的等級意思就是我們去了解發現相關的
transcript.whisperx[227].start 6989.562
transcript.whisperx[227].end 7015.752
transcript.whisperx[227].text 人員其實都非常的優秀可是呢他的一些軟硬體的設施不是不足或就是有相關的缺失那這部分如何能夠讓這些從事的健康檢查醫療機構在平昏如果相對低的時候有哪一些改善的方法如何能夠把相關的這些資源可以引進來不知道未來有沒有特別的規劃先有人關係
transcript.whisperx[228].start 7017.608
transcript.whisperx[228].end 7033.674
transcript.whisperx[228].text 老公見到檢查的醫療機構他應該符合標準安全的需求才讓他執行所以我們有平和機制有所以看到委員秀的是我們平和的成績那我們現在有新的機制就是如果連續三年不好我們就把他要下架因為我們要擇優太烈所以有關這樣子的那個
transcript.whisperx[229].start 7034.761
transcript.whisperx[229].end 7035.322
transcript.whisperx[229].text 接下來請楊耀委員
transcript.whisperx[230].start 7069.381
transcript.whisperx[230].end 7096.952
transcript.whisperx[230].text 謝謝主席主席請一下許部長請許部長兩位好部長好部長我看部長我看今天的業務報告齁就有關年金改革的準備的部分部裡面這邊還是一直停留在收集意見
transcript.whisperx[231].start 7098.615
transcript.whisperx[231].end 7125.251
transcript.whisperx[231].text 對不對我看你們的給我報告收集意見跟溝通會不會會不會收集意見跟溝通的時間太長了部長不是我不是不是不是我我我知道這是一項很很嚴峻的工程我也不是想為難你可是可是我覺得好像每每一次
transcript.whisperx[232].start 7126.653
transcript.whisperx[232].end 7151.193
transcript.whisperx[232].text 每一次的業務報告有關年改的部分大概一直都是停留在收集意見跟評估那這樣子到底年改革什麼時候可以啟動什麼時候可以落實讓讓讓廣大的勞工可以得到安心到底什麼時候
transcript.whisperx[233].start 7152.472
transcript.whisperx[233].end 7165.921
transcript.whisperx[233].text 委員這個期程部分我們會來通盤的規劃只是說因為不是 現在部長我打岔一下部長我打岔一下就是說你假如說說今天來議務報告已經有期程
transcript.whisperx[234].start 7167.185
transcript.whisperx[234].end 7189.452
transcript.whisperx[234].text 那我可能還可以接受可是這6年來我看部長也已經認滿6年了這個是一個非常長壽的部長可是對於跟勞工這麼息息相關影響這麼重大的一個政策一直停留在
transcript.whisperx[235].start 7191.272
transcript.whisperx[235].end 7207.083
transcript.whisperx[235].text 在準備跟收集意見打到共識這個階段本席真的沒有辦法接受謝謝委員因為這部分的確是不容易因為勞工的人口數實在是太多
transcript.whisperx[236].start 7210.845
transcript.whisperx[236].end 7232.322
transcript.whisperx[236].text 每個產業勞工職業勞工的這個他們的意見都不同關心的點都不同所以這個部分我也認為說這個其實應該要更我曾經在委員會跟部長討論過我覺得任何一項改革都不可能有共識都不可能有共識那我也知道
transcript.whisperx[237].start 7235.689
transcript.whisperx[237].end 7261.845
transcript.whisperx[237].text 勞工的年金改革為什麼困難就是因為他原本的的可以領到的給付就少那廣大的勞工的受薪階級也沒有因為台灣的經濟成長他的薪資等比例的增加所以要增加保費也有一定的阻力那要延後退
transcript.whisperx[238].start 7265.27
transcript.whisperx[238].end 7287.783
transcript.whisperx[238].text 可能會引發很大的風波所以我知道困難在哪裡可是也正因為困難所以才選民給民進黨機會就是要民進黨面對困難我還記得我們在從事軍工校年改的時候
transcript.whisperx[239].start 7289.505
transcript.whisperx[239].end 7306.104
transcript.whisperx[239].text 整個民進黨黨團大概受影響最大的就是我因為我澎湖的軍工校比例太高了可是我還是帶著崗盔挺過了年改我也已經又當選兩屆了
transcript.whisperx[240].start 7308.53
transcript.whisperx[240].end 7330.856
transcript.whisperx[240].text 就是說應該像蔡英文總統講的就是應該要改革的就是必須要改革必須要想到想到想到想到欸一套一套方案出來讓退休的不恐懼讓讓正在正在繳保費的洗男這個是我們的責任
transcript.whisperx[241].start 7331.926
transcript.whisperx[241].end 7359.144
transcript.whisperx[241].text 那我看這幾年就是提撥成為改革唯一的選項那這個本席也不反對甚至於我也已經提案把政府負擔最終的責任入法為什麼我這麼重視這件事情就是我講的這必須要讓勞動者有一個安定的心情
transcript.whisperx[242].start 7360.981
transcript.whisperx[242].end 7372.615
transcript.whisperx[242].text 欸讓他知道知道任何人執政都不會放棄這一千多萬的的老公朋友這一千多萬對台灣經濟
transcript.whisperx[243].start 7376.295
transcript.whisperx[243].end 7398.346
transcript.whisperx[243].text 有卓著貢獻的勞工我覺得我們必須要去面對現在就是這樣子就我剛才講的我知道改革的困難為什麼呢因為不要說減少給付就以目前的給付來看
transcript.whisperx[244].start 7399.946
transcript.whisperx[244].end 7428.177
transcript.whisperx[244].text 我們目前在請領勞工給付的人數大概有174萬平均每個月領到的是一萬八千多一萬八千多可是最低台灣的最低生活費以台北市來講就已經高達一萬九千多其台北市以外的地方平均值
transcript.whisperx[245].start 7429.451
transcript.whisperx[245].end 7446.104
transcript.whisperx[245].text 也已經將近到達一萬五那他現在領這樣子已經快要快要未達在台北市已經未達未達最低生活費的標準了現在萬一再減少幾副怎麼辦
transcript.whisperx[246].start 7448.203
transcript.whisperx[246].end 7476.236
transcript.whisperx[246].text 對,跟我也報告,但是我們其實臺灣的產業勞工來看他其實他退休包括兩個,一個就勞保另外一個就勞退,這兩個加起來那當然還有一些健保啦長照,那個是照顧我們的退休的人員健保跟長照是另外一回事啦我們就聚焦在勞工的部分就勞保跟勞退可是呢勞退的比例呢就是太低了
transcript.whisperx[247].start 7477.216
transcript.whisperx[247].end 7502.47
transcript.whisperx[247].text 字體的部分太低了字體比較低但是固體喔固體拿到我記得700多萬喔大概大概是這樣子啦齁前體前體體角數大概在106年的時候大概是14%多啦對對對那現在現在就是到字體的
transcript.whisperx[248].start 7504.861
transcript.whisperx[248].end 7527.913
transcript.whisperx[248].text 我們到去年年底是14.17%人數是106萬所以就是像部長講的沒有錯勞工的退休的保障我們的設計是架構在勞保跟勞退可是問題是勞退本身有一個現象就這14點幾%
transcript.whisperx[249].start 7531.371
transcript.whisperx[249].end 7556.688
transcript.whisperx[249].text 你仔細去看薪資所得越高的越願意自提配合自提的部分那越低的呢因為他的所得本來就低所以他要再提出6%他可能有他的困難度還有一個固體6%固體6%是僱主一定要提撥的對我知道那6%就是
transcript.whisperx[250].start 7558.831
transcript.whisperx[250].end 7560.998
transcript.whisperx[250].text 響鐘
transcript.whisperx[251].start 7561.636
transcript.whisperx[251].end 7588.729
transcript.whisperx[251].text 那6%呢是大家都有我現在講的是6加6特別是以薪資低的勞工來看6加6才足以保障他的退休生活那因為他假如說本來就低薪他可以領的勞保給付本來就低
transcript.whisperx[252].start 7590.051
transcript.whisperx[252].end 7603.167
transcript.whisperx[252].text 然後呢他又因為職涯的過程生活的所需教養子女孝敬父母所以他可能要自提這6%對他來講就馬上面臨生活的困頓
transcript.whisperx[253].start 7610.543
transcript.whisperx[253].end 7632.103
transcript.whisperx[253].text 部長你懂我的意思嗎?我知道我知道不過當然啦如果是低薪的齁可能多數都是低薪的低薪的字題很少啦對我們現在大概有統計啦齁大概平均啦齁報告委員平均我們那個月投保薪資大概就是平均大概3萬7啦齁如果以3萬7來看喔他的勞保
transcript.whisperx[254].start 7633.602
transcript.whisperx[254].end 7646.519
transcript.whisperx[254].text 應照按照現在限制他大概是領1萬7左右然後再如果他的再加上勞退就是固體只算固體不算自體啦齁大概1萬所以這個加起來勞保加勞退大概有27700
transcript.whisperx[255].start 7648.875
transcript.whisperx[255].end 7673.907
transcript.whisperx[255].text 就是像一個退休勞工以平均的月頭保薪資來看如果是37000平均大概我們抓大概37000他這樣領起來有27000多對啊這種平均值就是這種平均值就是比較看不到看不到真正弱勢的啦保障弱勢呢是民進黨邁向執政最重要的一個一個一個
transcript.whisperx[256].start 7675.007
transcript.whisperx[256].end 7675.027
transcript.whisperx[256].text 對對對因為
transcript.whisperx[257].start 7701.347
transcript.whisperx[257].end 7712.584
transcript.whisperx[257].text 我也知道很困難可是我常說不困難的事情怎麼輪得到我們做呢那不然我最後問一個問題就是
transcript.whisperx[258].start 7715.882
transcript.whisperx[258].end 7734.21
transcript.whisperx[258].text 本席已經提出來政府擔負最終的支付責任的保證那這樣子的提案 勞動部這邊的立場會支持嗎?我們支持好 謝謝部長 謝謝主席謝謝楊耀委員 我們先來休息10分鐘
transcript.whisperx[259].start 7761.647
transcript.whisperx[259].end 7762.127
transcript.whisperx[259].text 委員會主席
transcript.whisperx[260].start 8405.333
transcript.whisperx[260].end 8412.577
transcript.whisperx[260].text 好接下來請王玉明委員好謝謝主席我們請這個勞動部部長請許部長王委員好部長好部長你記不記得過去你曾經說過就是即使你摘了烏紗帽也要進行年金改革勞保年金改革你有沒有說過這句話這句話不是我說的是在訪問的時候那個那個
transcript.whisperx[261].start 8434.91
transcript.whisperx[261].end 8436.351
transcript.whisperx[261].text 關羽老寶負債13兆即將在2028年破產你到底想改還是不想改
transcript.whisperx[262].start 8451.52
transcript.whisperx[262].end 8454.583
transcript.whisperx[262].text 有沒有改革的計畫到目前為止本席看到就是我們的這一些老年給付金額過去10年你看這個圖我們從102年到這個111年他其實是暴增了兩倍
transcript.whisperx[263].start 8468.136
transcript.whisperx[263].end 8492.097
transcript.whisperx[263].text 那這個所有的這個精算報告都已經直指2028年其實就要年金就要破產但是到目前為止本期都沒有看到到底我們主責的勞動部你的年金改革的計畫到底在哪裡喔過去蔡總統也曾經說要軍工教勞一起改
transcript.whisperx[264].start 8492.977
transcript.whisperx[264].end 8520.086
transcript.whisperx[264].text 結果軍公教年改已經完成了但是我們有關於勞保年金的改革到現在遲遲未上路遲遲未啟動本期想要救教部長這個問題到底是出在哪裡是你作為勞動部長你不敢去提方案不敢改還是有更上層告訴你說千萬不要動不要有任何的計畫
transcript.whisperx[265].start 8521.516
transcript.whisperx[265].end 8531.046
transcript.whisperx[265].text 到底是哪一個是你自己沒有改革計畫還是上面有交代說我們只要改軍公教就好勞保根本不用改這個問題我們一直在很審慎的在做一些研議
transcript.whisperx[266].start 8536.277
transcript.whisperx[266].end 8553.027
transcript.whisperx[266].text 有嗎有那報告委員因為主要幾個面向那委員應該也清楚因為整個財務要改其實勞保年改的目的他是在要解決財務的問題是那解決財務的問題當然這裡面就有幾個面向一定要去做討論我這麼說
transcript.whisperx[267].start 8555.188
transcript.whisperx[267].end 8576.207
transcript.whisperx[267].text 好那這個當然就是包括費率的調整的部分包括月平均薪資的採集年間包括年資給付率是不是要調整還有就是撥補因為不管怎麼樣這個撥補是一定要的因為說了面向它都是連動的我知道但是撥補可以解決整個勞保年金要破產的問題嗎撥補沒有辦法完全解決撥補是啊而且你現在撥補
transcript.whisperx[268].start 8579.85
transcript.whisperx[268].end 8606.651
transcript.whisperx[268].text 是幾百億欸又不是說一兩千億對報告委今年是到一千兩百億再加特約預算是一共一千三那我是跟委員報告就是說這個撥補其實對不能完全解決問題但是其實對我們基金的一個財務的穩定是有幫助那你這是短期的救急啊但是就廣大的一千萬的勞工來講短期的救急方案這是解決之道嗎這個蔡政府執政已經八年囉
transcript.whisperx[269].start 8610.634
transcript.whisperx[269].end 8627.666
transcript.whisperx[269].text 還有多少個勞工的8年可以拖延或者是等待那如果大家面對問題就只是這樣子歸縮起來然後呢不敢提任何方案我覺得這不是一個負責任的執政黨該有的作為吧我覺得報告委員這個問題當然一定要去面對處理
transcript.whisperx[270].start 8629.247
transcript.whisperx[270].end 8653.959
transcript.whisperx[270].text 什麼時候要面對就是說什麼時候要提方案我是幫廣大的勞工因為周遭都有勞工朋友說媒體都這樣子在報就是說2028年要破產那這些年輕的勞工就很擔心我必須真的還是要讓委員因為這個所謂的破產是基金的用完這個部分其實是整個財務他可能會面臨這個用慶的這個問題但是
transcript.whisperx[271].start 8657.24
transcript.whisperx[271].end 8672.172
transcript.whisperx[271].text 對於勞工的權益因為這是政府辦的保險政府一定會付給負的責任因為我很怕有時候一講破產這句話勞工要不了解他有時候我到時候是不是沒有錢可以領了是啊因為你的收支就是不平衡因為你現在負債已經13兆啦我必須這麼說還是要利用這個機會因為我一定要跟勞工朋友講說這個基金用盡並不代表你就領不到錢因為這是政府辦的保險
transcript.whisperx[272].start 8682.04
transcript.whisperx[272].end 8708.332
transcript.whisperx[272].text 政府一定會負幾負責任所以我說但是你一個保險呈現出來的負債這麼高勞工擔心也是合理啊勞工擔心當然他擔心他希望我們財務解決我們這個讓他能夠穩定然後他這個能夠永續但是因為你沒有解決方案啊方案我跟委員報告我們方案就沒有方案啊方案還在你劇當中啊因為方案委員部長你已經做幾年了七年了吧
transcript.whisperx[273].start 8709.292
transcript.whisperx[273].end 8709.812
transcript.whisperx[273].text 我們會在這樣穩定的財務基礎上
transcript.whisperx[274].start 8725.021
transcript.whisperx[274].end 8725.721
transcript.whisperx[274].text 我根本沒提出任何的關於如何解決勞保
transcript.whisperx[275].start 8740.686
transcript.whisperx[275].end 8751.208
transcript.whisperx[275].text 年金破產的問題沒有任何方案欸你們現在你們的官網你自己看你們的年金改革你們一直停滯在這個疫苗收集的階段因為目前沒有方案就是說因為還沒有一定的共識啦你根本會也沒有開啊怎麼會有共識你們根本不敢走出踏出那一步因為只要一開始行動你們就怕被檢討
transcript.whisperx[276].start 8767.851
transcript.whisperx[276].end 8787.281
transcript.whisperx[276].text 因為那個不是我參與但是在這年金改革委員會其實有討論到老跑的問題大概是幾個面向大家都知道啦只是說這個面向你到底要怎麼去做處理所以你現在到底是你不能改還是不敢改還是上面有交代說先不要動不是都不是我覺得我現在還是要
transcript.whisperx[277].start 8788.562
transcript.whisperx[277].end 8816.997
transcript.whisperx[277].text 持續我的意思說還是要勞資團體部長我們還是要你讓本席看到就沒有持續啦好啦這個問題我就是要讓部長知道說這是重中之重作為執政黨哪有那麼好當該扛的就是要扛該解決的要面對就是要面對嘛但是你們這樣子一直拖延一拖再拖其實很多勞工心裡的那個擔憂是真的因為這樣子沒有根本解決問題這是第一個齁第二個我要問你那個
transcript.whisperx[278].start 8817.777
transcript.whisperx[278].end 8839.979
transcript.whisperx[278].text 台印的MOU你們什麼時候會送行政院?送了沒?還沒報告委員因為我們2月26接到嘛那知道我們就是按照條約地鐵法的規定我們30天也就我3月26之前會送進去然後因為現在在他們在簽辦當中3月26會送到行政院對對那什麼時候會送立法院?4月初?
transcript.whisperx[279].start 8841.841
transcript.whisperx[279].end 8871.241
transcript.whisperx[279].text 就是行政院被查之後我們就會送那個立法院這裡好所以是大概4月初會送進來立法院嗎可能應該是4月就是你們沒有時間表嗎不是因為要等行政院被查啦他回文給我們說被查我們就會送那個立法院應該4月我跟差不多了這個本期上個禮拜我有接見很多的這個移工團體他們很關心這件事情
transcript.whisperx[280].start 8871.901
transcript.whisperx[280].end 8890.692
transcript.whisperx[280].text 第一個他們有反映到有關於台印要簽MOU這件事情他們希望要能達到G2G就是政府對政府而且希望這個是唯一方案因為他們已經看到現行的執聘中心這個相關的制度還有很多缺失你們也沒有改
transcript.whisperx[281].start 8891.112
transcript.whisperx[281].end 8918.886
transcript.whisperx[281].text 但是他們認為這個台印因為部長你有說會是從小規模開始那既然小規模就可以用一個新的做法來做這件事情部長你是不是可以承諾這些勞工團體會全力的來研議G2G的方案會會齁好你答應了齁好那另外一個呢就是這些勞工團體說最近我們跟印尼還要再次簽MOU你知道吧
transcript.whisperx[282].start 8920.92
transcript.whisperx[282].end 8939.597
transcript.whisperx[282].text 應該是1月屬的,境外遠洋漁工對,是關於遠洋漁工那連這樣子印尼的官方他還邀台灣的漁工團體透過視訊在簽MOU之前他要了解這些團體的想法我覺得印尼這樣的做法非常的進步
transcript.whisperx[283].start 8940.037
transcript.whisperx[283].end 8966.656
transcript.whisperx[283].text 就是他連我們臺灣的移工團體的意見都充分尊重然後再納入他的意見再來簽MOU但是反觀我們的做法我們是簽了MOU之後現在事後才要來開相關的會議再來收集意見而這些移工團體告訴我說你們之前什麼都沒有邀請他們而他們是最關心就是有關於這些這些外籍移工的問題為什麼你不邀他們呢
transcript.whisperx[284].start 8967.757
transcript.whisperx[284].end 8970.718
transcript.whisperx[284].text 國會報告因為其實我們歷來包括之前的5個來源國我記得到6個了其實還有馬來西亞過去我們都是都沒有徵詢團體的意見都沒有那你要改變做法部長你可以改變一個好的做法你要比前面更進步啊那我問你那後面的
transcript.whisperx[285].start 8987.426
transcript.whisperx[285].end 8991.889
transcript.whisperx[285].text 你將來要開的這一些會議算是本席有問過嗎你是不是可以承諾讓這一些比較有代表性的移工團體讓他們有機會進到你的會議小組裡面我覺得他們真的是真正關心移工相關權益的這一群人不要把他們排除在外
transcript.whisperx[286].start 9005.938
transcript.whisperx[286].end 9022.012
transcript.whisperx[286].text 讓他們的意見納進來才可以讓我們整個台印雙方未來的這一個MLU的內容是更完備或是未來的制度設計更兼顧到這一些移工的權益是不是可以承諾邀我們這一些代表性的移工團體可以進來你的委員會
transcript.whisperx[287].start 9026.455
transcript.whisperx[287].end 9046.785
transcript.whisperx[287].text 我希望今天部長的承諾要做到讓這些擴大讓這些公民團體的參與只有好處沒有壞處因為我們可以把各式各樣的情況設想得最周到然後讓這些外籍移工來到台灣之後不要有被剝削而是他的權益都可以得到最周延的保障達到雙贏的目標好不好好謝謝部長
transcript.whisperx[288].start 9051.541
transcript.whisperx[288].end 9055.005
transcript.whisperx[288].text 謝謝王委員接下來請李昆成委員謝謝主席來有請我們許部長請許部長
transcript.whisperx[289].start 9071.96
transcript.whisperx[289].end 9087.208
transcript.whisperx[289].text 立委員好部長好這個我過去在擔任市議員的時候然後也常常會介紹那些勞資爭議的陳情案件還蠻多的那時候就是勞工局會做處理那我這個就幾個這個
transcript.whisperx[290].start 9089.069
transcript.whisperx[290].end 9096.193
transcript.whisperx[290].text 案件的這個數字請教一下部長我們是109年勞動事件處理法實施之後然後這個勞資爭議案件的統計從109年到112年那這個109年是27000到112年是26000大概有稍微減少一點點但是其中受到這個
transcript.whisperx[291].start 9111.423
transcript.whisperx[291].end 9135.172
transcript.whisperx[291].text 送到地方法院受理的案件這4年來大概平均大概都1萬件左右那我看到這個司法院他們的這個新聞稿他上面寫說這個勞動的調解案或是訴訟案平均的這個終結的天數這個63.47天還有116.35天那也少於法定期間的90天跟180天那所以呢
transcript.whisperx[292].start 9136.992
transcript.whisperx[292].end 9160.88
transcript.whisperx[292].text 這個勞動事件調節成立率57%大概快六成那對勞方來講是相對是有利的那所以這個本席請教這個部長就統計來看勞資爭議的案件法院審理可以得到快速的處理但是呢而且對勞方是有利的但是勞資爭議的案件呢並沒有顯著的減少那部長你的看法是怎麼樣
transcript.whisperx[293].start 9164.178
transcript.whisperx[293].end 9186.723
transcript.whisperx[293].text 因為勞動事件法當初也是要讓這些讓勞工願意然後便於使用這個訴訟程序來解決爭端所以我覺得這個訴訟案件會增加這個其實就是說對勞犬保障來講並沒有說不好我也沒有說不好我就說這個勞資爭議案件也沒有減少
transcript.whisperx[294].start 9190.014
transcript.whisperx[294].end 9207.525
transcript.whisperx[294].text 那所以就表示說當然如何減少勞資爭議那這個要從他們譬如說爭議的原因然後去探討然後我的意思是說那其實我們一般都希望說能夠勞資能夠去協調就協調也不一定最後是上法院
transcript.whisperx[295].start 9209.186
transcript.whisperx[295].end 9225.675
transcript.whisperx[295].text 可是我也發現臺灣的資方寧願請律師上法院也不願意給勞工合法的勞動條件因為我看這一個地方受理的案件平均來講也都是一萬件左右其實也沒有減少
transcript.whisperx[296].start 9227.423
transcript.whisperx[296].end 9248.561
transcript.whisperx[296].text 因為這個當然就是有時候資方他的意願等等這個也沒有辦法因為其實我們在做這個調處的時候那其實比如說勞工局他們會去資方調閱相關的一些文件然後讓資方也覺得說勞工局有在重視這件事情但是他們最後
transcript.whisperx[297].start 9249.261
transcript.whisperx[297].end 9271.853
transcript.whisperx[297].text 大概平均下來都還是有大概接近三分之一吼他們還是最後還是上了法院吼案件也沒有減少啦吼我用意在這裡啦就是說欸如果有人是希望說能夠吼盡量不要對啊還是不然你你我們還是希望說站在老方的這個角度來講嘛所以報告委員我們其實也是行政跟司法的條件我們都還是維持雙軌啦
transcript.whisperx[298].start 9273.214
transcript.whisperx[298].end 9283.5
transcript.whisperx[298].text 好那其實在像剛剛您講的那個法院的調解大概57%我們大概勞動部這邊行政調解大概都一半以上我的意思是說齁這個還是站在勞方的立場齁就是能夠協調就協調這個不鼓勵齁
transcript.whisperx[299].start 9290.443
transcript.whisperx[299].end 9306.557
transcript.whisperx[299].text 這資方跟勞方打官司啦我是看那個數字齁大概沒有什麼顯著下講好我再問你一下齁我們在2004年開放家庭幫傭齁那家庭幫傭的這一個其實標準是很嚴格啦齁這個有三個條件齁就有三名以上
transcript.whisperx[300].start 9307.438
transcript.whisperx[300].end 9329.497
transcript.whisperx[300].text 那個年齡6歲以下的子女或是說4名以上齁年齡12歲以下的子女而且其中兩名是年齡6歲以下或是累積點數滿16點齁那當然你們有一個累積點數表啦齁那可是齁就目前來講我們都是少子化齁然後呢如果是這個有3個小孩齁除非齁你一次三胞胎啦不然齁一次一胎齁跨了6年齁
transcript.whisperx[301].start 9330.878
transcript.whisperx[301].end 9346.895
transcript.whisperx[301].text 這個總是就是不符合資格因為你可能到第三胎齁這個你的這個長這個這是老大齁有可能就是超過了啦齁然後部長你應該知道齁其實現在從2021年開始齁我們已經連續37個月齁生不如死你知道生不如死是什麼意思嗎
transcript.whisperx[302].start 9350.195
transcript.whisperx[302].end 9376.787
transcript.whisperx[302].text 死亡比出生多所以說我本席就是有接到一個案例就是說他們在這個申請的時候那其實是符合資格的那可是呢他因為這一個幫養就是在照顧小孩方面出了一些問題那所以他必須就是要換掉但是當他換掉的時候當初申請的時候是符合資格但是要換的時候老大已經超過6歲了就不符合資格了
transcript.whisperx[303].start 9377.447
transcript.whisperx[303].end 9405.326
transcript.whisperx[303].text 那其實我有請你們的這個勞動力發展所來做過這一個說明然後他們也有給予協助但是我個人是認為就是說我們對家庭幫傭的這一個制度在現在少子化的情況之下這其實是有點限制是有點嚴格剛剛三個條件我是想請這個勞動部回去檢討一下就是說你們資格條件能不能放寬因為現在是少子化的情況那第二個就是說
transcript.whisperx[304].start 9406.708
transcript.whisperx[304].end 9417.519
transcript.whisperx[304].text 這個有關家庭看護的這部分他其實就比幫用都還要再寬鬆一點比如說那個家庭看護他有這個地補的制度他不用重新申請然後甚至的也縮短了這個
transcript.whisperx[305].start 9418.251
transcript.whisperx[305].end 9418.271
transcript.whisperx[305].text 部長.
transcript.whisperx[306].start 9446.135
transcript.whisperx[306].end 9473.686
transcript.whisperx[306].text 包括這個我們來檢討啦但是因為這個部分其實也有不同的團體有不同我知道有不同的團體啦所以我們這部分會再來做一些因為條件的確是嚴格的一點我們現在少死化情況那麼嚴重我們要鼓勵多生鼓勵多生我們也做了很多的這一些托育政策那有關這個齁這個有關家庭包容這部分本席是認為是可以再放鬆一點啦不要給家庭造成太大的壓力啦好不好
transcript.whisperx[307].start 9474.726
transcript.whisperx[307].end 9488.635
transcript.whisperx[307].text 當然有不同團體有不同意見我們也是有借到相關的陳情好不好來做個橫評一下再稍微再調整一下好謝謝主席謝謝李坤澄委員接下來請林淑芬委員
transcript.whisperx[308].start 9502.642
transcript.whisperx[308].end 9506.572
transcript.whisperx[308].text 好謝謝主席喔是不是請我們這個許部長請許部長
transcript.whisperx[309].start 9511.021
transcript.whisperx[309].end 9537.887
transcript.whisperx[309].text 林委員好部長好我們知道這個消除婦女歧視一切形式的這個歧視公約C鬥公約我們的國家報告是4年要報告一次嘛對不對然後這4年裡面我們最近的一次報告是111年的第4次國家報告會議結論在這個性平意見上有關的就有一個叫家庭育兒和工作的平衡他關切的重點是什麼你知道嗎
transcript.whisperx[310].start 9540.711
transcript.whisperx[310].end 9555.336
transcript.whisperx[310].text 就是讓消除婦女所有一切的歧視CEDAW公約我們的國家報告跟你們的業務有關的是什麼應該就是能夠在育兒上更有更友善的措施
transcript.whisperx[311].start 9557.373
transcript.whisperx[311].end 9570.87
transcript.whisperx[311].text 我先來講他為了提升婦女人權和促進性別平等的重要成果他公開發表了86點的結論性意見還有建議那跟你們最直接相關第49點和第50點是這樣說的
transcript.whisperx[312].start 9574.514
transcript.whisperx[312].end 9593.395
transcript.whisperx[312].text 第49說台灣已經列為全球最低出生率的國家之一國際審查委員會發現造成這個現象的關鍵因素是非常薄弱零散且模糊的產價和育嬰制度儘管台灣的育嬰制度最近有一些彈性
transcript.whisperx[313].start 9594.016
transcript.whisperx[313].end 9601.521
transcript.whisperx[313].text 但他仍然很僵化所以這個國際審查委員會他關切育嬰價制度我們台灣現在仰賴主要是仰賴雇主的貢獻那第50點當然就講到說這個國際委員會建議政府研究並參考國際經驗改善育嬰價制度以設計一個永續和彈性的制度為目標讓所有利益相關者一起分擔費用以增進國家利益
transcript.whisperx[314].start 9624.756
transcript.whisperx[314].end 9637.783
transcript.whisperx[314].text 所以他一直在建議說改善育嬰假制度改善育嬰假制度你要我們都知道說針對這個國家報告我們要採取行動方針要訂出績效指標嘛對不對你知道嗎?
transcript.whisperx[315].start 9637.783
transcript.whisperx[315].end 9637.823
transcript.whisperx[315].text 你們訂什麼?
transcript.whisperx[316].start 9637.823
transcript.whisperx[316].end 9638.023
transcript.whisperx[316].text 你們知道嗎?
transcript.whisperx[317].start 9638.023
transcript.whisperx[317].end 9639.104
transcript.whisperx[317].text 你們的績效指標還是你們的行動方針是什麼?
transcript.whisperx[318].start 9650.53
transcript.whisperx[318].end 9661.664
transcript.whisperx[318].text 報告委員因為這個部分我們勞動部還是在持續在研議當中因為這個其實委員我知道你沒有你如果不知道你業務單位知不知道
transcript.whisperx[319].start 9664.115
transcript.whisperx[319].end 9685.026
transcript.whisperx[319].text 這個部分的話就是我們持續的會有一些更...我在問你們的績效指標是什麼行動方針111年到現在勒4年一次115年你們就要針對你們採取了什麼行動有了什麼關鍵的績效指標你們要回復出來勒你們要做報告勒部長不知道業務單位也不知道
transcript.whisperx[320].start 9687.608
transcript.whisperx[320].end 9690.871
transcript.whisperx[320].text 我跟你報告好了今年你們2月就公開了CIDO第4次國家報告的行動回應表112年的辦理情形你們的具體行動方針你們具體行動就是
transcript.whisperx[321].start 9705.982
transcript.whisperx[321].end 9723.121
transcript.whisperx[321].text 加強宣導職場平權概念關鍵的績效指標是一年要辦25場的宣導會讓勞工要了解自身權益、雇主要遵守法令你們的行動方針是辦宣導會然後呢
transcript.whisperx[322].start 9727.385
transcript.whisperx[322].end 9739.821
transcript.whisperx[322].text 計效指標是要達到25次一年半25次人家講說你的育嬰價要改善你說好我來宣導宣導平權那我一年半25次代表我績效達到了
transcript.whisperx[323].start 9741.858
transcript.whisperx[323].end 9769.311
transcript.whisperx[323].text 這樣子未免太便宜行事了吧保證這樣太簡單了這樣會不會就虛以為疑啊這樣子你們在115年你們要報告你們具體的推動成果難道你要跟國際審查委員會說我已經辦了一年我不是辦25場我辦26場的宣導要這樣子講嗎人家說你要改善你的育嬰假的制度
transcript.whisperx[324].start 9770.211
transcript.whisperx[324].end 9775.214
transcript.whisperx[324].text 要建立一個更有彈性的不僵化的你說我去宣導了 保證這樣會搞這個當然不夠不過我知道就是運將的部分我剛其實要表達是說我也責成我們的那個業務單位這個部分一定要去做一些研議規劃我們已經跟你建請多少年了
transcript.whisperx[325].start 9795.367
transcript.whisperx[325].end 9799.43
transcript.whisperx[325].text 我至少我們看過工地委然後這幾年至少這5年內我們也不斷都一直不斷的跟你講說我們有一個更好的更彈性的親子架的架構都跟你們講了但我今天要講說你們部裡面始終認為說阿我育嬰留子停薪有做就是了所以你們在這裡面大概檢視了兩個說我到底有沒有做第一個當然就是說
transcript.whisperx[326].start 9824.32
transcript.whisperx[326].end 9845.771
transcript.whisperx[326].text 這個申請育嬰留職停薪的勞工他有意願重返原工作崗位你們認為這個就是指標第二個你們也認為說顧子武願意提供原工作的這個意願比例也上升了你們就覺得他有意願再重返職場第二個顧子武也願意讓他返回原來的職位
transcript.whisperx[327].start 9849.313
transcript.whisperx[327].end 9864.129
transcript.whisperx[327].text 的意願也提高了反為原來的工作崗位你們認為這樣就叫達標了但是呢我們跟你講說事實上這個重返職場重返工作崗位這樣子就算是達標了嗎
transcript.whisperx[328].start 9866.741
transcript.whisperx[328].end 9889.698
transcript.whisperx[328].text 所以我們希望你是要對申請了育嬰流子停薪的勞工你還要進行長期的這個追蹤他的職業變化然後呢我們發現你們自己這個安慰所其實有一個一份長期的追蹤報告那安慰所裡面他研究發現申請育嬰流子停薪者相較於未勤領者
transcript.whisperx[329].start 9890.879
transcript.whisperx[329].end 9914.481
transcript.whisperx[329].text 有較高的離職率那也建議未來研究可以納入婚育離職者和未離職者的比較更深度的去檢驗育嬰留職停薪政策的成效但我們在這裡要強調這個我們不反對育嬰留職停薪但是透過你們安慰所這份研究我們更要證明提升勞參率
transcript.whisperx[330].start 9917.103
transcript.whisperx[330].end 9942.617
transcript.whisperx[330].text 維持女性的勞參率不要講提升啦維持生兒養小孩以前的勞參率維持它不是這個只有靠育嬰留子停薪不要每次談到說家庭跟工作生活要平衡你就說啊我們有育嬰留子停薪假提高了經濟性的補貼然後就叫我們要住嘴不是的
transcript.whisperx[331].start 9943.407
transcript.whisperx[331].end 9951.652
transcript.whisperx[331].text 第一個國家勞動力短缺你們動不動就說開放外籍移工開放外籍幫傭開放外籍勞工不只是那樣子我們的婦女勞參率從剛出社會我們的90%的勞動參與率下降到生小孩以後重返勞動到這個生完小孩10年以後勞參率剩40幾%
transcript.whisperx[332].start 9969.904
transcript.whisperx[332].end 9988.784
transcript.whisperx[332].text 台灣的婦女勞參率沒有辦法重返生小孩之前然後留住台灣的這一些專業的認真的女性的勞動者你們要拿出來不是只有育嬰留子停薪假為什麼要這麼講說你來看你們自己
transcript.whisperx[333].start 9990.346
transcript.whisperx[333].end 10007.464
transcript.whisperx[333].text 這個安慰所我們從這個育兒婦女就業歷程探討提升勞動參與率參與意願的可行性你們勞研所109年的報告你看2004年他做了204年這一批的他持續就業的這一群來看
transcript.whisperx[334].start 10008.605
transcript.whisperx[334].end 10012.009
transcript.whisperx[334].text 他養小孩養到最後一年剩下45%
transcript.whisperx[335].start 10023.385
transcript.whisperx[335].end 10040.995
transcript.whisperx[335].text 那我們也知道養小孩的第一年還是很多人會留在職場但是呢他要面臨幾個階段第一個階段大幅下降的就是小孩在這個第三年大概送托兒所了送托兒所就經常發生
transcript.whisperx[336].start 10043.072
transcript.whisperx[336].end 10047.938
transcript.whisperx[336].text 容易生病感冒藏病毒婦女要帶回家自己顧顧天顧7天總來總去就這個大幅滑落-8.9
transcript.whisperx[337].start 10054.315
transcript.whisperx[337].end 10074.587
transcript.whisperx[337].text 在第6年要念小學了他反而滑落了5-3.4小學孩子家長的這個陪伴然後關心他的教育發生問題了然後跟學校老師要溝通所以他還需要的時間要很談判也要很多但是呢
transcript.whisperx[338].start 10075.467
transcript.whisperx[338].end 10090.716
transcript.whisperx[338].text 大部分的不友善的狀況沒有配套的狀況他還是選擇離職追蹤到最後一年第12年之後呢剩下45.5所以你看得出來婦女的勞動參與率一去不復繁
transcript.whisperx[339].start 10092.54
transcript.whisperx[339].end 10094.162
transcript.whisperx[339].text 在這種狀況裡面很多臨時狀況但是我們看到負育兒的女性一旦退出職場以後就沒有再重返職場這個才是國家勞動力
transcript.whisperx[340].start 10107.617
transcript.whisperx[340].end 10111.301
transcript.whisperx[340].text 最大的隱憂而你們當然想說不要緊啦外籍移工啦外籍幫傭婦女要二度就業大概重返什麼的門檻最低你知道嗎也有部分的婦女她會去做這個倒載
transcript.whisperx[341].start 10124.537
transcript.whisperx[341].end 10147.102
transcript.whisperx[341].text 倒載保姆居家清潔。結果打算來開放外籍幫佣,他們再繼續死掉嗎?所以我現在看接下來那6歲以前婦女都選擇直接離開職場但是年齡比較大的時候可以上學以後他就會開始採取兼職那我們現在看高所得跟低所得來看
transcript.whisperx[342].start 10148.015
transcript.whisperx[342].end 10154.48
transcript.whisperx[342].text 高低所得不管你大家覺得你所得這麼高的婦女你大概不會離開職場吧薪水這麼高這麼好你就去請外傭來幫傭幫忙帶小孩就好了帶小孩有人幫你帶小孩煮飯清潔打掃這麼高薪你不會離開職場吧事實上不然啊事實上不然你看
transcript.whisperx[343].start 10172.449
transcript.whisperx[343].end 10188.021
transcript.whisperx[343].text 高所得者生完小孩要第一年他有82.8%到那個第12年剩下47.1%這樣下降了多少你看低所得的人76.6然後追蹤到最後一年43.0一樣大幅滑落你不要以為很有成就感所得很高的婦女他就願意他就願意繼續留在職場
transcript.whisperx[344].start 10200.998
transcript.whisperx[344].end 10206.732
transcript.whisperx[344].text 其實他還是有很多的這個需求所以今天在這裡我們今天要跟大家講說
transcript.whisperx[345].start 10210.155
transcript.whisperx[345].end 10235.482
transcript.whisperx[345].text 這個獄嬰劉子庭新者他即便申請那也只是前0到3歲0到3歲0到3歲以後呢0到3歲以後他還是繼續有這個就業的這個需求但是呢他還是有薪資所得的需求但是呢還會再重返就業的他持續就業比
transcript.whisperx[346].start 10236.789
transcript.whisperx[346].end 10256.735
transcript.whisperx[346].text 有申請過應留職停薪的持續就業的跟一般整體不管有沒有的平均數來比他還是比較低啊那我們今天講說其實很多人是需要經濟經濟因素他是不能夠沒有收入而他必須要有收入然後還必須要兼顧育兒所以這種狀況裡面呢
transcript.whisperx[347].start 10260.874
transcript.whisperx[347].end 10275.527
transcript.whisperx[347].text 我們看到說我們一直在跟你溝通喔引導育兒女性重返職場不只是這個育嬰留子停薪假也不只是只有這個顧小孩的外傭顧小孩你看到六歲六歲之後他還是繼續在滑落
transcript.whisperx[348].start 10279.451
transcript.whisperx[348].end 10298.328
transcript.whisperx[348].text 他不是6歲以後就不用再陪著這個小孩所以我們也希望說著眼於避免育兒的女性退出職場有心彈性的親職假他很重要他的彈性在於說如果我們育兒留職停薪假是兩個月嘛60天嘛
transcript.whisperx[349].start 10300.049
transcript.whisperx[349].end 10322.489
transcript.whisperx[349].text 那你讓他開放到一天一半天一小時為這個方案然後呢新資補貼這個當然原來就是舊保繼續付也沒有叫雇主付然後對雇主來講也很有善啊我的這個生育的婦女不是一次請兩個月也不是一次請半個一個月
transcript.whisperx[350].start 10323.69
transcript.whisperx[350].end 10343.014
transcript.whisperx[350].text 然後呢他也不用說半年裡面分兩次請對僱主來講他是可能以天為單位他比較好搭配他不用再去請一個人來這個替補這個人力然後總共的天數就是啊抱歉就是總共的天數就是6個月啦我剛剛講錯了是6個月所以不是兩個月是我剛剛一直講錯了6個月
transcript.whisperx[351].start 10346.795
transcript.whisperx[351].end 10352.078
transcript.whisperx[351].text 這6個月裡面你讓他慢慢的彈性的去那你讓僱主說一次請3個月或是一次請6個月對僱主的衝擊比這個彈性還更大對不對部長
transcript.whisperx[352].start 10358.954
transcript.whisperx[352].end 10375.913
transcript.whisperx[352].text 一天六天還一次一天六天再一次對僱主衝擊比較大就是說主要是他人力的運用還有替代的這個會不會不好找人因為本來想說那種零碎化可能比較難找人但沒關係我這麼不是啦
transcript.whisperx[353].start 10376.434
transcript.whisperx[353].end 10396.946
transcript.whisperx[353].text 六個月僱主還要找一個人來替補他嘛三個月也要但六天跟一天他比較好找人找替報告你就是有些輪班的公司啊他如果是一小時或兩小時那個對他會比較困難因為他沒有辦法去找這種一小時的人力來
transcript.whisperx[354].start 10397.947
transcript.whisperx[354].end 10419.366
transcript.whisperx[354].text 那你這樣子講話你這個鼓勵婦女在就業計畫裏面你講到說獎勵雇主提供有照顧需求女性勞工調整或縮短工作時數你這個方案你就不用做啊叫你講的你們提供了雇主對有照顧家庭需求的婦女提供工時調整或部分工時調整每一個職缺每個月發給3000元最長12個月最高獎勵36000元然後你們這個方案
transcript.whisperx[355].start 10425.091
transcript.whisperx[355].end 10430.695
transcript.whisperx[355].text 要做到113年2月29號截止你們發了687個職缺去補助然後你們要透過獎率去引導雇主縮短工作時數育兒女性以薪資讓他們有彈性你還要給錢那你現在又說這個對排班的公司來講是很困難的你的這個政策跟你剛剛所講的是矛盾的
transcript.whisperx[356].start 10450.719
transcript.whisperx[356].end 10457.763
transcript.whisperx[356].text 林委員是因為時間的關係等下還要處理臨時提案我趕快做一個結束好了
transcript.whisperx[357].start 10459.508
transcript.whisperx[357].end 10483.6
transcript.whisperx[357].text 首先你這個東西就認為說應該要彈性化而且你要獎勵你還發給雇主最高一年三萬六的獎勵你的是說提供雇主有照顧需求的女性有照顧需求照顧小孩需求的女性調整或縮短工作時數勒那個林委員是不是等一下請勞動部這邊
transcript.whisperx[358].start 10491.394
transcript.whisperx[358].end 10503.76
transcript.whisperx[358].text 我們要的是這個有心的這個彈性親子嫁啦因為事實上呢彈性親子嫁才能留住這個女性的勞動率啦
transcript.whisperx[359].start 10504.5
transcript.whisperx[359].end 10531.698
transcript.whisperx[359].text 那不能夠沒有工作沒有收入可是又要照顧小孩我們需要友善一點也不是只有到6歲為止甚至整個小學階段都還是很多問題小學階段一放一放那個長病毒一放都7天啊這題我有在處理我請業務單位去跟你們報告啦我們可能有會你試辦計畫啦我剛剛在跟你講說不是每個行業都有辦法這樣子做但是我們先對先就可以做的行業先來試辦看看啦我請業務單位去給你們
transcript.whisperx[360].start 10533.579
transcript.whisperx[360].end 10560.784
transcript.whisperx[360].text 以前不是每個行業都可以一例一休我們也是先訂了啊 對不對是不是請那個勞動部等一下會議對啦我知道啦但是我跟你講說育兒的需求要到完整來講像小學階段要到12歲談性話其實要很久我剛剛講藏病毒就是7天他整個小學階段通通都要那也不是只有照顧
transcript.whisperx[361].start 10562.044
transcript.whisperx[361].end 10575.447
transcript.whisperx[361].text 這個小孩到6歲而已不是只有這樣子而已請勞動部等一下會後再跟林委員說明那我在這邊做一個宣告等一下在05月請委員質詢結束處理臨時提案那現在請楊瓊英委員謝謝主席本席想邀請部長
transcript.whisperx[362].start 10602.521
transcript.whisperx[362].end 10617.658
transcript.whisperx[362].text 最近一次的勞保精算報告有指出你說若不啟動年金改革勞保基金將要在2028年破產那當年度缺口會來到1267億元
transcript.whisperx[363].start 10621.082
transcript.whisperx[363].end 10639.481
transcript.whisperx[363].text 那也成為賴清德總統任期內可以預估的看到的第一個大課題那部長你也曾經在2020年說老保年改掉了烏紗帽你都要做那現在你仍舊是部長
transcript.whisperx[364].start 10642.843
transcript.whisperx[364].end 10665.134
transcript.whisperx[364].text 但是勞保基金每一年依舊在增加數千元的精算負債精算負債所以因此我要說因為政府我們很關心絕對不能倒政府也告訴我們只要政府不倒勞保不會倒
transcript.whisperx[365].start 10665.814
transcript.whisperx[365].end 10689.1
transcript.whisperx[365].text 就是這樣子但是又隨時放出一個聲音又出來又賠了多少怎麼樣會怎麼樣那似乎對於我們的這個勞工朋友非常的不公平所以呢本期要來請教部長你現在勞保修正的條例你會提出嗎請說說明
transcript.whisperx[366].start 10691.665
transcript.whisperx[366].end 10703.392
transcript.whisperx[366].text 報告委員目前那個方案吼就是草案吼還沒有還沒有啦吼對還是還沒有來繼續本事要請教那如果你連提的方案都沒有
transcript.whisperx[367].start 10705.051
transcript.whisperx[367].end 10731.386
transcript.whisperx[367].text 那就擺爛的阿那本期要請教喔2028年勞保破產那如果你現在沒有方案協助喔比如說像台電需要倒我們趕快請行政院來支援因為不能漲價民生店漲了那物價又要漲了那是更大的洞所以行政院也支援那在這樣子的情況之下沒關係我們好好來討論喔
transcript.whisperx[368].start 10733.464
transcript.whisperx[368].end 10740.451
transcript.whisperx[368].text 那就是說我們政府當然要撥補給我們要努力這一塊那在這樣的情況之下
transcript.whisperx[369].start 10741.926
transcript.whisperx[369].end 10771.372
transcript.whisperx[369].text 你可以保證政府每一年可以來撥補這個基金讓勞保不破產嗎因為本期要跟你討論的是應該要去努力行政院你如果每一年撥補的預算是1500億那就不會有這個問題那你總是你的條例未出以前那你要保證我們的勞保基金不會倒啊這才是部長你應該要做的啊
transcript.whisperx[370].start 10772.312
transcript.whisperx[370].end 10780.875
transcript.whisperx[370].text 請說明根本報告號其實再次計算報告是110年那在109年的時候我們基金餘額是7625億那到現在為止我的基金餘額到1月是9088億我記得這幾年透過撥補透過我們的投資老闆基金投資運用其實我們的這個基金的
transcript.whisperx[371].start 10797.689
transcript.whisperx[371].end 10816.24
transcript.whisperx[371].text 財務是有增加增加1463億那我是跟委員報告說這種波幅也好投資運用也好這個都是讓我們財務能夠穩定那波幅的部分我們也持續先暫停你的回答因為每一次告訴我們就是這個方向
transcript.whisperx[372].start 10816.88
transcript.whisperx[372].end 10840.976
transcript.whisperx[372].text 但是每一次一小段時間就會告訴我們我們如果不怎麼樣呢那我們就會這個勞保金捐就會倒這個聲音在民眾的身上已經很痛苦了會倒會破產這都是媒體的報導我一向我們都是講說這是政府辦的社會保險勞工安心政府一定會負最後幾個責任這是媒體說的
transcript.whisperx[373].start 10842.957
transcript.whisperx[373].end 10854.926
transcript.whisperx[373].text 但是人家有這樣的疑慮你就要去提出方案不管任何方案因為在你的立場就是要保證他真的不能倒嘛我們勞工才會安心啊當然這是你的工作所以來本期的立法會勞退薪資2005年實行到現在幾年了
transcript.whisperx[374].start 10870.836
transcript.whisperx[374].end 10898.415
transcript.whisperx[374].text 啊?勞退新制到現在幾年啊?201818年18年了嘛吼那我們法定的這個雇主是6%嘛吼那其中還有一個也就是2003年的這個勞退自體率我們統計了你有新的政策你就要去看他的結果那這一個統計出來是2003年那個勞退自體的部分是14%
transcript.whisperx[375].start 10900.476
transcript.whisperx[375].end 10923.695
transcript.whisperx[375].text 那顯示還有大概740萬勞工裡頭有600萬那麼86%他希望扣我自己啦我不要自體那到底為什麼呢因為自體就是尊重在個人的意願當然啊那他不願意提可能是說他表示你的政策人就是怕你會倒啊所以人家不要自體啊 對不對每一次都告訴我們絕對不會倒然後一段時間又告訴我們有可能會倒自體不會倒啦
transcript.whisperx[376].start 10929.7
transcript.whisperx[376].end 10933.461
transcript.whisperx[376].text 當然啊!當然啊!那可是人家不要自體啊!對啊!個人帳戶不會倒啊!但是為什麼你的執行率是如此?本席要跟你討論的就是說當你提出一個政策之後那為什麼你的執行率不高?
transcript.whisperx[377].start 10954.969
transcript.whisperx[377].end 10967.146
transcript.whisperx[377].text 你聽我說具體不高有的是勞工他自己可以去投資應用他可以到自由金融市場去投資應用也有人因為他的經濟負擔他認為他沒有辦法有餘裕再去製體
transcript.whisperx[378].start 10969.91
transcript.whisperx[378].end 10969.95
transcript.whisperx[378].text 當然啊!
transcript.whisperx[379].start 10990.959
transcript.whisperx[379].end 11004.604
transcript.whisperx[379].text 我會努力來讓字體,因為這個等於說鼓勵勞工出去你要去努力嘛,而不是原因,當然人家不信任你,人家當然不要啊有我原因啦,我會介紹給你聽啦,但是KPI要提高,我會再拍片要努力,好那你把你的方案,你可能提高的
transcript.whisperx[380].start 11012.927
transcript.whisperx[380].end 11030.564
transcript.whisperx[380].text 那個效能的方案你提出來好不好最後一個議題我給他一個功課就好三八婦女節剛過那麼我們針對於女性面臨勞動薪資的部分同工不同酬那麼我們也看到101年的參與率首次破了五成
transcript.whisperx[381].start 11031.184
transcript.whisperx[381].end 11049.721
transcript.whisperx[381].text 那麼提升到51點七三%但是我們也有很多的學者也警示我們在職場的方面對於女性呢他是不夠友善也缺乏彈性所以部長我給你一個功課我要拜託你影響女性參動力的一個參與率呢他的
transcript.whisperx[382].start 11050.842
transcript.whisperx[382].end 11079.236
transcript.whisperx[382].text 這個重要因素他沒有辦法提高到底是什麼因為你們為期定期的三年的婦女在就業計劃裡頭你有鼓勵你有鼓勵因為婚姻因素退出的希望能夠重返這個職場所以我要你一個資料也就是我們看到的是這樣子的但是是不夠友善的那你要怎麼樣如何幫助兩線金權怎麼樣協助女性在勞動市場方面她可以更安心
transcript.whisperx[383].start 11079.676
transcript.whisperx[383].end 11102.242
transcript.whisperx[383].text 他很願意更走出來你帶他去協助嘛好不好你把方案給我好不好你把方案給本席謝謝因為等一下要處理臨時提案所以不好意思那跟證宣告我們等一下在李燕秀委員質詢結束處理臨時提案好那接下來請林月琴委員
transcript.whisperx[384].start 11113.656
transcript.whisperx[384].end 11116.057
transcript.whisperx[384].text 有請我們的部長請部長我來自民間一直在從事兒少工作那過去也在那個到現在也是還是台少盟的理事長那過去我們有一個
transcript.whisperx[385].start 11134.449
transcript.whisperx[385].end 11155.72
transcript.whisperx[385].text 調查就是根據我們的調查裡邊大概發現18歲以下進修部的學生他會去工作主要的原因在經濟匱乏包括要負擔自己的生活費賺自己的零用錢跟分擔家計那不是因為貪玩或是而要去就業是因為經濟壓力而要去就業
transcript.whisperx[386].start 11156.704
transcript.whisperx[386].end 11178.357
transcript.whisperx[386].text 所以那有93的比例在16歲已經有了第一份工作而且是初次求職者可是呢只有的薪資是符合基本工資那是不知道勞動條件規定的也不知道有納保有勞保然後常遇到不當對待勞動條件普遍惡劣
transcript.whisperx[387].start 11182.701
transcript.whisperx[387].end 11208.489
transcript.whisperx[387].text 是10%曾在工作當中受傷10.7%曾受傷送醫12%曾在深夜照理講10點後他不應該是上班曾在深夜或凌晨工作職業安全真的是看慮所以想問在這麼劣質的環境當中他自己都沒有辦法察覺說他原來的工作環境薪酬不夠沒達到基本工資又沒有勞健保那
transcript.whisperx[388].start 11209.79
transcript.whisperx[388].end 11228.308
transcript.whisperx[388].text 受傷之後又求助無門所以想問部長這邊目前勞動部如何對這些青少年做勞動教育還有你的管道是什麼一年有多少人受惠談的事實上是勞動條件嗎職業安全嗎社會保險跟救濟管道是什麼那再來
transcript.whisperx[389].start 11229.609
transcript.whisperx[389].end 11250.471
transcript.whisperx[389].text 勞動部的1995的申訴管道有沒有接線去年2023年因為我們2022年在國際委員來審查CRC的時候就提起說申訴制度那去年各部會都要回應這個申訴制度的時候我那時候在民間也提出來說而勞動部你有沒有針對於青少年服務
transcript.whisperx[390].start 11251.272
transcript.whisperx[390].end 11274.028
transcript.whisperx[390].text 的這個專線來接否則青少年有時候在問話方式跟一般有時候政府部門的回答轉線轉的他們事實上是沒辦法去理解甚至轉線當中他也不知道說這些轉線的人在跟他對應那一樣的你有沒有督導各縣市勞工局勞動局這邊有沒有適切的申訴管道這個在
transcript.whisperx[391].start 11275.169
transcript.whisperx[391].end 11277.269
transcript.whisperx[391].text 新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞新聞
transcript.whisperx[392].start 11306.503
transcript.whisperx[392].end 11327.298
transcript.whisperx[392].text 我先講宣導的方式就是我們多元然後包括我記得剛剛有個資訊部長多元應該要去切中當要求職的人否則的話否則為什麼我們調查這麼多青少年事實上是受騙的甚至他被不當對待的時候他求助包括也辦那個宣導會我記得112你剛剛有個資料辦了好幾場
transcript.whisperx[393].start 11331.568
transcript.whisperx[393].end 11345.847
transcript.whisperx[393].text 對我知道我要講的先分層次啦第一個我們多元管道宣導另外我們到校園從國小國中高中到大學我們也有做各種不同的
transcript.whisperx[394].start 11346.408
transcript.whisperx[394].end 11347.629
transcript.whisperx[394].text 喔喔喔喔喔喔喔喔喔喔喔喔喔喔喔喔喔
transcript.whisperx[395].start 11363.254
transcript.whisperx[395].end 11388.937
transcript.whisperx[395].text 我們都會有專案的勞調檢查就是會針對因為寒暑假都是這些經濟弱勢學生打工比較多所以我們會去做這些檢查部長在的時候是不是把這些相關事上是提供給我這邊那因為有時候宣導也要去檢討到底效能怎樣否則的話現在持續還是有這些問題發生我們會用年輕人比較
transcript.whisperx[396].start 11389.838
transcript.whisperx[396].end 11405.791
transcript.whisperx[396].text 接觸接觸的方式要關心我們的年輕人因為這一群事實上是為了家計而進入到勞動市場的人而不能默示他們可能是會雪上加霜如果少年持續在這種狀況底下他負擔家計的時候他如果又受傷
transcript.whisperx[397].start 11406.724
transcript.whisperx[397].end 11420.58
transcript.whisperx[397].text 那現在當然我們覺得只在這邊你們會去做處理可是沒有拿到最低基本工資我覺得這有點不太妥是這個不行這個有多重那就麻煩部長那接下來就看到那個非勞動人口我認為應該要積極就業來作為你
transcript.whisperx[398].start 11423.243
transcript.whisperx[398].end 11451.805
transcript.whisperx[398].text 的所謂的促進對象為什麼這樣講就我們現在主動發現問題不是透過數字來引力問題喔因為你如果是就業率如果不扣除我們的非勞動力人口的時候這數據是有相差的喔因為我覺得勞動部主業透過這種勞動統計來了解國人勞動狀況OK可是國人最關心的就是就業率跟失業率可是當你把這個非勞動人力排除之後呢的確看起來數字很漂亮
transcript.whisperx[399].start 11452.005
transcript.whisperx[399].end 11468.899
transcript.whisperx[399].text 議員議員
transcript.whisperx[400].start 11469.059
transcript.whisperx[400].end 11498.26
transcript.whisperx[400].text 接下來就來看這個15歲到24歲齁不過在這邊也請勞動部要知道齁中錯事實上是國民義務教育齁才叫中錯你們的新聞稿都一直在講中錯中離是講國中生非義務教育的我們比較要關心的是這15歲到24歲不過國中生以下如果去就業的話那童工又是另外一個問題齁可是你們的新聞稿先以後要記得要更正不可以講中錯應該是中離生那中離生這一塊是不是
transcript.whisperx[401].start 11499.124
transcript.whisperx[401].end 11499.589
transcript.whisperx[401].text 而針對於
transcript.whisperx[402].start 11501.9
transcript.whisperx[402].end 11528.777
transcript.whisperx[402].text 他們目前的狀態在就業的時候有沒有因為你們已經是在111年12月19號就公布弱勢青少年的慈愛準備計畫那我現在想問現在成效如何那做的狀況而且如何定義弱勢是家庭總收入還有我覺得去年不錯的是勞動部已經提出少年就業計畫可是我現在在你們官網上找不到這個是一個不錯的
transcript.whisperx[403].start 11529.838
transcript.whisperx[403].end 11545.759
transcript.whisperx[403].text
transcript.whisperx[404].start 11545.999
transcript.whisperx[404].end 11566.574
transcript.whisperx[404].text 否則的話這幾年來一直以來都是我們民間在募款在做逆風少年逆風少年讓青少年就業我們是去輔導他那怎麼會是那我覺得去年勞動部已經沒有置身事外認為你們不是局外人要來做這些事情的時候很好啊可是至今到現在我還是在網站上找不到那團體更是找不到
transcript.whisperx[405].start 11567.114
transcript.whisperx[405].end 11584.342
transcript.whisperx[405].text 一件事我們木款給團體來申請可是現在變成是你政府要承擔很好可是我到現在還是沒有看到那另外一群我們更擔心的是現在我們收到一些訊息55歲被很多我們的市場機制裡邊去淘汰掉了強迫被
transcript.whisperx[406].start 11585.262
transcript.whisperx[406].end 11585.282
transcript.whisperx[406].text 謝謝部長謝謝
transcript.whisperx[407].start 11618.639
transcript.whisperx[407].end 11621.282
transcript.whisperx[407].text 謝謝林月晴委員接下來請伍麗華委員謝謝主席有請部長請許部長部長好如您所知道的其實從今年的1月起
transcript.whisperx[408].start 11644.965
transcript.whisperx[408].end 11667.019
transcript.whisperx[408].text 農業部的這個老年老農津貼他又調高了那也就是說從過去91年4000其實來到今年可以領到8080那這個是在農保條例裡面呢就是有特別在第5條有談到除了農會的會員之外
transcript.whisperx[409].start 11668.52
transcript.whisperx[409].end 11690.247
transcript.whisperx[409].text 只要年滿15歲以上沒有去領取相關的各種社會保險老年給付都可以來參加農保那以我們原住民來講我們最喜歡的就是農保那哪一些相關的保險呢像公保沒有勞保沒有軍保或者是沒有國民年金
transcript.whisperx[410].start 11691.147
transcript.whisperx[410].end 11716.483
transcript.whisperx[410].text 那我這邊會問這個問題部長是因為有一個案例那後來發現這樣的人很多還真不少以這個老人家為例他是民國31年出生在他41歲的時候那個時候經濟起飛很多的原住民呢都到都會區去工作那他呢是去做吃的參加了廚師工會
transcript.whisperx[411].start 11717.884
transcript.whisperx[411].end 11735.424
transcript.whisperx[411].text 那後來年紀大了他就要回家鄉那個時候工會呢就跟他說你可以結親老寶領取一次性的老年給付他也很高興那領了回去之後呢一直到現在他已經82歲了他一直都在務農
transcript.whisperx[412].start 11736.325
transcript.whisperx[412].end 11736.345
transcript.whisperx[412].text 獲得獎項獎項
transcript.whisperx[413].start 11756.545
transcript.whisperx[413].end 11784.431
transcript.whisperx[413].text 台灣原住民族經濟狀況調查這是112年去年6月底的一個資料你可以看到我們原住民從事農林漁牧業的是占最高當然跟從事營建工程的也很多不相上下另外他也提到我們負責主要的維持家計生計的是60歲以上
transcript.whisperx[414].start 11785.111
transcript.whisperx[414].end 11806.061
transcript.whisperx[414].text 也就是說對原住民族群來講我們到60歲以後其實都還需要繼續工作繼續來承擔家裡的主要生計所以我想要請教一下部長您聽到這樣的一個案例而且還真不少我講的是老人家你覺得他該不該領取老農津貼他沒有任何的社會保險他誤農他誤農
transcript.whisperx[415].start 11813.577
transcript.whisperx[415].end 11821.44
transcript.whisperx[415].text 沒有沒有這樣的長者還真不少他就是那個時候離開工廠對他領完了因為如果按照我們現在法令的規定是他有領過老年給付的話他就
transcript.whisperx[416].start 11835.089
transcript.whisperx[416].end 11835.729
transcript.whisperx[416].text 委員這個是老農津貼的問題
transcript.whisperx[417].start 11852.594
transcript.whisperx[417].end 11867.787
transcript.whisperx[417].text 是是我沒有關係我現在就是要來問您以他當時的投保薪資去算的話他是做了15年所以他當年是一次領了23萬多那他這個當事人呢他是
transcript.whisperx[418].start 11868.167
transcript.whisperx[418].end 11881.016
transcript.whisperx[418].text 後來呢我們去看一下吼他當時是56歲退嘛吼所以呢他目前的狀況如果他可以去領老農津貼他大概還沒有到4年就已經超過他當時的23萬
transcript.whisperx[419].start 11883.718
transcript.whisperx[419].end 11903.78
transcript.whisperx[419].text 如果以他現在他82歲吼他已經可以領將近一百五十萬如果以我們原住民的平均餘命我們目前平均餘命吼是七十八歲他也可以領到一百一十二萬多好那現在我們來看一下因為我們的農保條例告訴他我們如果要去請領
transcript.whisperx[420].start 11905.361
transcript.whisperx[420].end 11932.635
transcript.whisperx[420].text 農今天他其實所有的條件都符合他唯一的一個條件不符合就是說要持續加保他曾經參加過農保那他回來之後他也是繼續務農但是他有一個條件不符合就是要持續加保所以呢他也跑去農會一直要加保可是農會呢告訴他說這邊有寫他說他已領取老年給付他說請於條例修正後再參加農保
transcript.whisperx[421].start 11934.136
transcript.whisperx[421].end 11941.962
transcript.whisperx[421].text 所以部長您就知道為什麼我要來請教您吼那部長我去年10月呢其實也曾經到農業部問過我們的農業部部長現在我是同樣的問題我要請教你為什麼您聽聽看農業部長當時是這麼說他說對
transcript.whisperx[422].start 11951.348
transcript.whisperx[422].end 11968.918
transcript.whisperx[422].text 他本身在現在相關的規定上面是無法適用的我們會後去看這個部分是否真正的具有公平性如果是有公平性我們會解釋如果是屬於被遺漏的一群相對的就是該用什麼樣的規定去處理如果是農業部的相關規定農業部會炒你這個是當時農業部長所以您也同意嗎因為他說
transcript.whisperx[423].start 11977.463
transcript.whisperx[423].end 12004.135
transcript.whisperx[423].text 只要勞動部:後來他們研擬的相關辦法是說只要勞動部願意繳回當時的老年給付就可以那我就要請教部長您的意見如何報告委員這個是我們法定的規定我沒有辦法來說支不支持因為現在法定規定就是你領了之後合覆了以後就不能變更啊所以沒有說所謂我可以再收回然後他再另外去
transcript.whisperx[424].start 12004.855
transcript.whisperx[424].end 12006.035
transcript.whisperx[424].text 不是部長農業部那個地方因為他有他的農保條例
transcript.whisperx[425].start 12021.926
transcript.whisperx[425].end 12041.719
transcript.whisperx[425].text 那現在我再翻回那個農保條例我再念給您聽一次他在農保條例第5條第二款非前向農會會員年滿15歲以上從事農業工作之農民未領取相關社會保險老年給付者得參加本保險嗎
transcript.whisperx[426].start 12043.612
transcript.whisperx[426].end 12071.139
transcript.whisperx[426].text 那現在我們農會他就是因為根據這個農保條例他就是覺得說他告訴他說這個可能要等修法之後你才可以回來參加農保嗎那現在農業部他也覺得他們是被漏接的一群嗎也願意來研擬就他們研擬呢他們提供的是說如果我們勞動部這邊針對我們的這個一次性老年給付如果他願意
transcript.whisperx[427].start 12072.259
transcript.whisperx[427].end 12081.614
transcript.whisperx[427].text 叫回去你們可不可以讓這樣的長者這個沒有辦法用韓式來解決這個是法令的明文規定那您認為要怎麼修
transcript.whisperx[428].start 12084.494
transcript.whisperx[428].end 12090.156
transcript.whisperx[428].text 我希望您會同農業部能夠一起去共商然後呢去延長可行的方案然後讓老保投保年資或老年
transcript.whisperx[429].start 12113.764
transcript.whisperx[429].end 12113.784
transcript.whisperx[429].text 好﹖
transcript.whisperx[430].start 12139.213
transcript.whisperx[430].end 12163.588
transcript.whisperx[430].text 這個是法令的規範沒關係啦委員會跟農業部來因為他們的確是被漏接的一群而且我希望去算一下其實這樣的人不多因為有的像年輕的他其實可以去國民年金那邊但是像這樣的長者是沒有辦法因為他已經過了年紀好不好是不是請勞動部會後再跟委員再跟委員這邊來說明好謝謝部長謝謝主席謝謝
transcript.whisperx[431].start 12168.306
transcript.whisperx[431].end 12178.898
transcript.whisperx[431].text 謝謝吳麗華委員接下來請李燕秀委員感謝教委請部長請許部長
transcript.whisperx[432].start 12183.237
transcript.whisperx[432].end 12198.49
transcript.whisperx[432].text 部長在上一次的我們勞動部的工作報告當中我提出來我們失業率整體是降低的我看到你的工作報告內容確實沒有錯但是包括我們15歲到29歲失業率其實在金融海嘯之後我們也創了新低
transcript.whisperx[433].start 12202.794
transcript.whisperx[433].end 12230.043
transcript.whisperx[433].text 這些其實都是事實沒有錯但是我覺得勞動部還有一個更關鍵的數據跟報告沒有呈現在上一次的我們勞動部工作報告當中就是我們非典型的就業人口在過去4年來創了新高達到80.6萬人這一塊數據其實佔整體勞動力的比例未來部長你覺得非典型就業人口在未來會增加還是會減少
transcript.whisperx[434].start 12230.723
transcript.whisperx[434].end 12247.439
transcript.whisperx[434].text 你預估你感覺到我覺得現在的現在年輕人啊都對工作自由的這個那個選擇會是他的決定工作的之類的很重要的考量的因素啦那所以未來有可能會增加我是覺得對
transcript.whisperx[435].start 12248.44
transcript.whisperx[435].end 12263.117
transcript.whisperx[435].text 對你跟我的看法一樣我們看韓國我們看日本非典型的就業人口應該是往上在走的趨勢因為很多年現在就他希望有彈性工時要更靈活這個就是未來當然非典型有不同的不同的就業
transcript.whisperx[436].start 12263.257
transcript.whisperx[436].end 12263.597
transcript.whisperx[436].text 獲得的挑戰
transcript.whisperx[437].start 12288.314
transcript.whisperx[437].end 12305.541
transcript.whisperx[437].text 部長你同不同意包括像之前我們常常在開會討論包括UberEat跟Foodpanda他們常常我自己在基層走的時候我常常聽到外送人在跟我講說他們常常被片面的去調降外送獎金
transcript.whisperx[438].start 12306.061
transcript.whisperx[438].end 12328.127
transcript.whisperx[438].text 就突然一個公告就是說這個月要調價或者是增加外送的里程數這個是不是叫做片面的修改這個勞動條件這個算嗎你同意嗎我們這邊勞資糾紛接受到這樣的資訊跟曾經的建樹多不多報告委員這個部分一發現有這個問題馬上就要透過我們一個對話平台
transcript.whisperx[439].start 12330.828
transcript.whisperx[439].end 12350.126
transcript.whisperx[439].text 我們這幾年就有建立那個我們的外送業者跟那個這些外送工會的一個對話平台針對相關的爭議包括像說多碼對不對重點是多碼對所以我更認為在非典型的就業的模式上我覺得我們應該要有更多的
transcript.whisperx[440].start 12351.144
transcript.whisperx[440].end 12362.065
transcript.whisperx[440].text 法規也好來去保障勞工相關的權益你同嗎所以我們以前一直在說派遣法要怎麼修那你們的看法到底如何
transcript.whisperx[441].start 12363.143
transcript.whisperx[441].end 12383.097
transcript.whisperx[441].text 之前那個因為外送跟派遣這個可能不太一樣派遣的部分我們那時候因為常常都是假承攬真僱傭對假承攬真僱傭這幾塊其實都是我們現在勞動部接下來面臨很大的挑戰跟問題我記得我們剛上任我們一起努力做了一些法規上的調整
transcript.whisperx[442].start 12384.958
transcript.whisperx[442].end 12404.03
transcript.whisperx[442].text 那但是外送這一塊我是跟委員報告就是說的確這一塊不容易啦一直有人希望我們立專法的這個呼這個呼籲所以你到底做不可以做嗎這個我你你受到哪些你不能做的理由是什麼樣外界知道因為我在基層我都答應說我會把你們爭取權益是我覺得我不能讓你們你們的權益
transcript.whisperx[443].start 12404.81
transcript.whisperx[443].end 12404.83
transcript.whisperx[443].text 部長
transcript.whisperx[444].start 12428.747
transcript.whisperx[444].end 12450.978
transcript.whisperx[444].text 我知道,你說了這個都要回去做,但對外送員來說他可能這是他的第二份工作第三份工作因為薪資不夠嘛但是片面的去修正如何在他們這個勞僱的過程當中保障更大的權益更多的權益我們因應的方式到底是什麼我覺得要更具體否則
transcript.whisperx[445].start 12452.239
transcript.whisperx[445].end 12477.771
transcript.whisperx[445].text 我之前那個我之前當立委是4年前那個是我們4年前的修法但這幾年可能投入這些外送員的那個對那是派遣的部分派遣也好外送也好越來越多所以我覺得我們的法律是要越走越往前去進步去涵蓋照顧這些勞工的範圍要更多才對我們現在就是先透過對話的機制剛剛我講的那個平台他其實也有發揮到效果
transcript.whisperx[446].start 12481.293
transcript.whisperx[446].end 12497.822
transcript.whisperx[446].text 有對平台業者有達成約束的一個效果所以但是長期我們會去考量用怎麼樣的機制什麼機制因為這個機制我等很久部長我不是在考你因為現在外送人員越來越多派錢的人越來越多
transcript.whisperx[447].start 12498.562
transcript.whisperx[447].end 12524.291
transcript.whisperx[447].text 所以我們不能原地踏步四年前我覺得我們有做一些努力但是過去這四年我看到這一塊是很空的就是說我們沒有在法規裡面涵蓋照顧他們的權益要照顧的更多所以我在等待就是說既然未來非典型的就業人口我們也預估它是會越來越多的所以在法規我們的因應方式到底是什麼
transcript.whisperx[448].start 12525.256
transcript.whisperx[448].end 12530.082
transcript.whisperx[448].text 不管是派遣 非典裡面分很多 那我們的因應方式是什麼
transcript.whisperx[449].start 12531.079
transcript.whisperx[449].end 12555.774
transcript.whisperx[449].text 這個我未來齁 積極我不用大聲跟你講但你非常清楚這一塊年輕人非常重視這一塊他們也都在等年輕人為什麼這一次那麼多人不支持你們我邊走我邊在路上在敗票都天天看到他們在罵民進黨所以這一塊要做好因為投入這一塊市場很多都是年輕人部長我提醒你快走好不好好謝謝
transcript.whisperx[450].start 12561.101
transcript.whisperx[450].end 12586.19
transcript.whisperx[450].text 好謝謝李恩秀委員那我們現在處理臨時提案總共有3案請一併宣讀臨時提案第一案鑒於促進新住民就業補助作業要點第二條第三項第一款所指新住民排除了規劃取得國籍之外役外籍配偶導致超過14萬新住民因此喪失參加勞發署所開設新住民專班之資格
transcript.whisperx[451].start 12586.75
transcript.whisperx[451].end 12615.93
transcript.whisperx[451].text 故未能由勞動部全額補助其訓練費用.並獲發職業訓練生活津貼.原此建請勞動部於兩個月內研議修正.促進新住民就業補助作業要點.放寬第二條第三項第一款所指之新住民範圍.納入規劃取得國籍之外國人可行性.確保政府照顧新住民群體之美意得以落實提案人委員徒全吉聯署人委員盧憲一邱振軍第二案
transcript.whisperx[452].start 12616.75
transcript.whisperx[452].end 12644.25
transcript.whisperx[452].text 建於我國新住民已經成為臺灣社會重要的新興族裔為勞動部並為針對新住民進行就業調查原此建請勞動部於兩個月內研議針對新住民群體進行年度就業調查之可行性並報告立法院社會福利及衛生環境委員會確保政府照顧新住民群體之美意得以落實提案人委員徒全吉聯署人委員盧憲一邱振軍第三案
transcript.whisperx[453].start 12645.493
transcript.whisperx[453].end 12668.742
transcript.whisperx[453].text 一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第12條規定僅由家戶成員符合有三名以上之年零六歲以下子女或有四名以上之年零十二歲以下子女且其中二名為年零六歲以下條件之一且累計點數滿16點者使得申請招募或承接外國人
transcript.whisperx[454].start 12669.342
transcript.whisperx[454].end 12691.471
transcript.whisperx[454].text 上述規定不符合現今國內家庭多為小家庭或少子女之現狀為減緩臺灣家庭壓力原要求勞動部於3個月內研議放寬審查標準修正相關規定符合臺灣家庭現況所需之方案向立法院社會福利及衛生環境委員會提出書面報告提案人委員蘇清泉、邱振鈞、陳金輝宣讀完畢
transcript.whisperx[455].start 12696.611
transcript.whisperx[455].end 12704.88
transcript.whisperx[455].text 呃請問第一案行政單位有無意見第一案沒有意見沒有意見齁那委員OK啦齁好那呃照案通過
transcript.whisperx[456].start 12707.042
transcript.whisperx[456].end 12734.451
transcript.whisperx[456].text 那請問第二案行政單位或委員有意見報告委員會第二案的文字那也跟委員這邊做溝通是不是建議做部分修正那倒數第三行原來是並報告社會福利及推動委員會就是報告改成向並向社會福利及衛生環境委員會那後面加提出書面報告那後面文字沒有修正
transcript.whisperx[457].start 12735.722
transcript.whisperx[457].end 12737.224
transcript.whisperx[457].text 請問提案委員有沒有意見?無異議就遭案通過
transcript.whisperx[458].start 12760.152
transcript.whisperx[458].end 12784.079
transcript.whisperx[458].text 好那呃是不是請圖委員剛剛你們又後來又加了幾個文字第一案吼就照照修正文字通過好好好好那那個呃剛剛第一案就照文字修正通過好那第二案也是圖委員這邊剛就
transcript.whisperx[459].start 12786.643
transcript.whisperx[459].end 12807.312
transcript.whisperx[459].text 那也是照文字修正通過那接下來第三案第三案跟葛委員報告因為很多委員在關心因為邦庸的這個申請的資格的點數那因為過去這個議題因為社會確實有非常多不同意見那因為也擔心到對婦女的就業或是說對幼兒成長造成影響
transcript.whisperx[460].start 12808.372
transcript.whisperx[460].end 12836.643
transcript.whisperx[460].text 因為現在這個整個點數因為過去因為大概長期在執行之後可能跟設備現況因為可能有一些單親或雙親家庭因為有一些家庭照顧上的問題所以他確實有一些意見是說是這個點數比較做一些檢討那這個提案我們跟委員有溝通因為原來委員是說要把它降到一點那我們認為這一點可能會影響衝擊太大那也建議就是說可能要比較留一些後面的演繹的空間
transcript.whisperx[461].start 12837.623
transcript.whisperx[461].end 12854.577
transcript.whisperx[461].text 所以在這個文字上我們是建議就是是不是讓我們來跟社會各界就是來研議這個這個標準這個相關的標準然後符合社會的現況跟相關的一個現實的一個情形那請提案委員蘇清泉委員謝謝主席
transcript.whisperx[462].start 12861.162
transcript.whisperx[462].end 12888.23
transcript.whisperx[462].text 現在有人要生孩子 要叫人生四個孩子孩子要六個孩子 你要生四個孩子 什麼12個孩子 這個太糟糕了 存期委員自己三個小孩 他都沒有資格申請你要再叫人生 要再叫人上班 要再怎麼樣 這個是太糟糕的 所以一定要一定要你不要給我 顏議員你又走回頭路 不行耶 部長這樣不行喔
transcript.whisperx[463].start 12890.223
transcript.whisperx[463].end 12905.994
transcript.whisperx[463].text 所以這個留空間讓你們去演繹我沒有意見但是一定要放寬啦這個很重要很重要以上那那個第三案是不是有文字好書芬好書芬委員
transcript.whisperx[464].start 12913.357
transcript.whisperx[464].end 12940.714
transcript.whisperx[464].text 各位我們支持不管是育兒還是老人都要有人照顧當然我們講說這個開放家事服務工看護工到底是不是我們從看護老人開始看就知道外傭外籍移工不是解方否則老人在那裡現在每天在那裡吵架的很多那整個國家不管然後也沒有配套那像這個一個月你
transcript.whisperx[465].start 12941.494
transcript.whisperx[465].end 12944.536
transcript.whisperx[465].text 一兩萬塊的薪水事實上我們請過那個看護工都知道不是兩萬塊現在這個私底下成本你沒有到三萬是不行的可是如果你這個家庭看這個幫傭兩萬塊也不可能然後呢
transcript.whisperx[466].start 12957.023
transcript.whisperx[466].end 12972.735
transcript.whisperx[466].text 三萬塊你叫他要做家事要煮三餐然後還在一打二然後照顧兩個小孩還24小時週休零天可能週休零天給加班費就沒有了然後可能年休年休看看有沒有幾天我告訴你
transcript.whisperx[467].start 12973.035
transcript.whisperx[467].end 12996.42
transcript.whisperx[467].text 每一個照顧小孩的這個外籍幫傭可能最後都想要轉換僱主然後就每天跟你玩雞然後就說我要去廠工那裡我要去產業界產業界工時禮拜一到禮拜五即便是加班也有紙淨的時候不是無紙無淨不是一天24小時產業界的勞工加班薪水還比較高一個月零五萬六萬然後呢他可以週休至少一日
transcript.whisperx[468].start 12997.12
transcript.whisperx[468].end 13024.08
transcript.whisperx[468].text 一例一休也是至少一日然後他遇到這個該休的都有勞基法保障所以這種狀況裡面你要做家事然後又要無職無盡半夜小孩考答又起來過一天理系休息然後呢又要煮三餐然後一打二到時候這個額略的狀況也會出現啦然後領這麼少還要顧足完結要勞一直勞但我們不是在講這個而已我不是要講這個我
transcript.whisperx[469].start 13025.521
transcript.whisperx[469].end 13043.606
transcript.whisperx[469].text 我們要講的不只是我說外籍幫傭不是萬靈丹不是一勞永逸然後你要想誰需要你要工作因為不能因為生小孩而失去工作不能夠因為生小孩而失去工作這種經濟需求這麼強烈的人不能離職的人
transcript.whisperx[470].start 13047.287
transcript.whisperx[470].end 13056.673
transcript.whisperx[470].text 他們有能力去聘請這個外籍幫傭嗎?你給他們吃頭肉就不行了,一定要去吃頭肉才能夠支付一家所需的人。這樣的婦女有能力申請到外籍幫傭嗎?申請得到他們現在新的年輕人家裡有足夠的房間可以讓這個外籍幫傭一起睡嗎?
transcript.whisperx[471].start 13071.502
transcript.whisperx[471].end 13088.825
transcript.whisperx[471].text 喔居住空間夠嗎所以這樣的政策到底是真正的解決的方法嗎那我更不要講說現在的這個婦女的本國的中高齡的婦女的二度就業其實就是倒載服務和家事清潔在這種狀況裡面破壞我們還知道現在育兒照顧倒載服務的保姆等等都還需要證照制度
transcript.whisperx[472].start 13098.507
transcript.whisperx[472].end 13118.915
transcript.whisperx[472].text 而你破壞現在的政策制度找一個外傭來就可以吃喝拉撒睡我當媽媽的時候我也是兩個小孩的時候我就你知道我最想做的是什麼嗎我最想做就是去上班因為在家裡面要做家事要照顧小孩要照顧兩個小孩我心力交瘁我寧願去上班
transcript.whisperx[473].start 13120.074
transcript.whisperx[473].end 13144.767
transcript.whisperx[473].text 所以我覺得上班是休息那你覺得那個那個幫傭他他不會這麼想嗎發生惡虐的時候怎麼辦然後語言不通怎麼辦教養上怎麼辦然後把專業的照顧變成好像只是隨隨便便都可以做這不是走回頭路嗎那你到底有多少從業人員會失業然後我再講一個我們現在長照是一個福利政策
transcript.whisperx[474].start 13145.547
transcript.whisperx[474].end 13163.055
transcript.whisperx[474].text 但我們都知道長照最終要銜接到保險制度而如果大家長照跟長照一樣大量的這個看護工在那裡要銜接過去是很困難的如果你再繼續放寬再繼續放寬我跟你講長照的保險制度是不可能的
transcript.whisperx[475].start 13163.815
transcript.whisperx[475].end 13167.097
transcript.whisperx[475].text 而這這樣變成什麼你知道變成窮老人窮失能的人沒有人照顧因為沒有國家級的社會保險沒有這個長照保險然後就是有在調請的都去請多了沒有在調請的沒人顧沒的變成家裡面最可憐的那個老女人繼續顧
transcript.whisperx[476].start 13183.189
transcript.whisperx[476].end 13200.314
transcript.whisperx[476].text 所以這種狀況裡面我們以前車之間來看這個這個而照的從業人員他會被衝擊到那如果外籍幫用就可以解決了那我們公共托育也不用做了公共托育也不用做了嗎全部都靠外用來就好了
transcript.whisperx[477].start 13201.519
transcript.whisperx[477].end 13215.254
transcript.whisperx[477].text 所以請了外傭的就外傭請不起了公共托育公共托育品質會不會每況愈下因為大家覺得資源不用花那麼多有錢人都已經有外傭了其他就隨便做一做所以我的意思是說我們認為這個東西
transcript.whisperx[478].start 13217.797
transcript.whisperx[478].end 13237.113
transcript.whisperx[478].text 大家社會會有這種狀況都是因為政府政府做得太少所以才產生這個問題所以讓我們在這裡工作跟育兒只能折衣可是你要想到經濟最弱勢的他工作跟育兒都不能折衣啊他都必須要都要有所以我們在想說這個彈性親子嫁啦等等啦這個配套要要做得好
transcript.whisperx[479].start 13244.32
transcript.whisperx[479].end 13247.964
transcript.whisperx[479].text 這個這已經刻不容緩了所以保證你的長照這個以外你的親子價
transcript.whisperx[480].start 13254.915
transcript.whisperx[480].end 13260.44
transcript.whisperx[480].text 要到12歲的,到12歲的,也不是外傭過你過到六歲而已,六歲之後北部就不用再過孩子了嗎?就不用再參與了嗎?就沒有親子嫁的需求了嗎?當然有啊,啊這外傭開放了以後可以解決6到12歲的嗎?也沒辦法啊
transcript.whisperx[481].start 13274.472
transcript.whisperx[481].end 13287.961
transcript.whisperx[481].text 所以說起碼要有政府啦 政府的角色要進來 不管是照顧老的還是照顧小的最重要是政府要拿出手段 啊現在在搞公共化 損公共化啊現在還要再開放說那幫傭多一點 公共化還需要做嗎 弄個外傭全部你都補助外傭 補助申請外傭就好了
transcript.whisperx[482].start 13298.268
transcript.whisperx[482].end 13325.191
transcript.whisperx[482].text 然後一個外傭顧兩個主婚打掃還要24小時全年無休看他會不會吃光然後你再社福人力再增加一點額略就又出來了所以我的意思是說這是誇張極致但是我們今天要突顯的是政府該有的制度面要進來啦不是只有服務說經濟能力好的家庭空間夠的那經濟能力差的家庭空間不夠的人要怎麼辦
transcript.whisperx[483].start 13326.64
transcript.whisperx[483].end 13334.611
transcript.whisperx[483].text 我難道我就沒有生小孩的權利嗎?難道我就沒有照顧兩個的權利嗎?然後政府都不用進來幫忙照顧嗎?
transcript.whisperx[484].start 13337.049
transcript.whisperx[484].end 13361.012
transcript.whisperx[484].text 大概是這樣子林淑芬委員剛剛我們署長有特別提案第三案臨時提案有做文字修正那是不是文字修正完之後讓蘇委員看過委員報告因為有跟蘇委員這邊溝通所以原來委員所提的這個累計點數一點這部分這個也同意修正那這個修正之後就給予我們一些空間我們來跟社會各界再來做一些研議
transcript.whisperx[485].start 13363.749
transcript.whisperx[485].end 13364.55
transcript.whisperx[485].text 主席有請部長請許部長
transcript.whisperx[486].start 13390.61
transcript.whisperx[486].end 13409.142
transcript.whisperx[486].text 市長好上次我在質詢的時候有提出過這個我們的移工失聯總數那你那時候跟我的回答說不能只看失聯總數要看失聯率嘛對不對那我想請教一下你知道我們去年的移工總數是722622人一月那失聯是80643人失聯率是11.16
transcript.whisperx[487].start 13419.629
transcript.whisperx[487].end 13447.416
transcript.whisperx[487].text 那今年的失聯率是11.36所以看起來今年1月比去年1月失聯率還是比較高啊我當時跟你說的是整年度啦就112跟111去比因為基本上失聯率是在變化嘛對不對那我是拿我們通常失聯率是會統計整年這個去看說有沒有今年的失聯率是一個時間點就可以看失聯率嘛不是嗎
transcript.whisperx[488].start 13449.961
transcript.whisperx[488].end 13464.918
transcript.whisperx[488].text 對阿好沒關係我要跟您講就說我們現在一定要再努力啦對對顯然不只總數啦移工失聯率這樣看至少以今年1月跟去年1月比較也在增加所以這顯示我們政府的移工管理政策我覺得
transcript.whisperx[489].start 13465.879
transcript.whisperx[489].end 13482.506
transcript.whisperx[489].text 好像給外界的感覺就開放的越多啊失聯的就越多所以現在我們講說這個印度移工的開放問題啊我那邊請那個部長可以跟我們保證一下在移工失聯率明顯改善降低之前你可能還要再審慎一下吧
transcript.whisperx[490].start 13486.192
transcript.whisperx[490].end 13499.349
transcript.whisperx[490].text 我們到時候在工作小組會來就相關的你能不能給我一個所以明確的保證就是說如果失聯率沒有明顯改善之前不會貿然開放印度的移工
transcript.whisperx[491].start 13500.931
transcript.whisperx[491].end 13527.909
transcript.whisperx[491].text 外界現在最大質疑就是說其中一個就是說你這後端你沒有管好報告委員因為這是兩個議題就是說我們開放印度移工我一直在講到其實這個是多一個來源國讓僱主多一個選擇降低我們當然這個是兩個議題可是這兩個議題有相關聯性然後移工的失聯我們也一定會努力來把它的失聯人數努力把它降低上次其實我大概就跟那個部長討論過了
transcript.whisperx[492].start 13529.37
transcript.whisperx[492].end 13550.991
transcript.whisperx[492].text 委員會發言說實質上這些年來這個不要講移工的失聯人數越來越多像我看失聯率也在增加嘛所以這種情況之下你不能怪社會大眾對你沒信心吧報告委員因為失聯率因為剛剛委員舉的是去年單月跟今年的1月單月這樣比較沒有關係那你把整個年度所有年度
transcript.whisperx[493].start 13552.713
transcript.whisperx[493].end 13573.889
transcript.whisperx[493].text 這個的那個數字再提供給我好不好 可以可以可以我想請教下一個問題請教您我上次也問到一個就是有關於引渡引渡印度移工的部分我說目前這個連一位懂印地語烏爾都語的司法同意都沒有那請問有去了解一下嗎 報告委員因為我們基本上會以先引進
transcript.whisperx[494].start 13577.945
transcript.whisperx[494].end 13597.434
transcript.whisperx[494].text 我上次已經說過事實上印度來說的話他當然官方語言他憲法所載的語言就22個那其實有很多的重要的語言不只是英語啦他英語大概有占十分之12%大概有1.5億人懂英文的
transcript.whisperx[495].start 13597.974
transcript.whisperx[495].end 13622.145
transcript.whisperx[495].text 所以我未來在就引進一個我們希望說在能夠讓雙方比較容易溝通適應會先歡迎你會把英語作為一個門檻我們會把英語作為一個就是優先的選項了解我想請教這個部長下一個問題那我看這次的業務報告很多在講托育的部分那我想請教您我看到就是
transcript.whisperx[496].start 13623.025
transcript.whisperx[496].end 13639.922
transcript.whisperx[496].text 勞動部業務報告把112年補助了453家企業辦理托兒措施跟設施列為政績可是為什麼沒有講到所謂的僱主辦理托兒設施跟措施的成長率呢
transcript.whisperx[497].start 13640.717
transcript.whisperx[497].end 13665.02
transcript.whisperx[497].text 成長率上對不過我在我看你2018到2025年你是講說補助的加速都達到目標值嗎那達成值是目標值的兩倍嗎可是這五年裡每一年的雇主辦理托兒那個設施或措施成長率平均成長率只有1.4個百分點那我就看到數量雖然倍增了補助數量可是
transcript.whisperx[498].start 13666.623
transcript.whisperx[498].end 13688.73
transcript.whisperx[498].text 這個成長率沒有什麼變動好那這個補助效果就出現一些問題我有看到一些根本的問題請部長研究了好就說事實上在勞動部補助那個相關的作業區之裡面他有一個規定是員工在99人以下的企業優先補助啊但從數據來看的話你的相關補助在2018到2022年號
transcript.whisperx[499].start 13690.75
transcript.whisperx[499].end 13710.541
transcript.whisperx[499].text 一百名員工以上拿走九成二那佔走了四成的百人以下企業只拿百分之八那我覺得這個只補助大企業忽略小企業的部分可能也要稍微檢討一下好不好好以上謝謝謝謝委員好謝謝羅志強委員接下來請牛許廷委員
transcript.whisperx[500].start 13721.789
transcript.whisperx[500].end 13727.19
transcript.whisperx[500].text 好 謝謝主席我們等一下投影片不好意思這個勞動部長有請謝謝請許部長您好部長這個無安辛苦了今天一樣要聊一下這個有關於移工的這個議題因為桃園本身是移工非常大的一個居住的環境所以說移工管理的品質其實會影響桃園市民的生活品質所以今天針對幾個題目來就教勞動部的部長
transcript.whisperx[501].start 13751.116
transcript.whisperx[501].end 13762.029
transcript.whisperx[501].text 第一個我們當然大家啦包含我們在做這個政策的研究調查的時候其實發現我們大部分的研究焦點還是放在移工為什麼會失聯嘛然後把失聯移工變成一個政策重點那
transcript.whisperx[502].start 13763.328
transcript.whisperx[502].end 13792.385
transcript.whisperx[502].text 當然啦我覺得我們不要頭痛一頭腳痛一腳啦現在的狀況是這樣因為失聯移工的數量實在太多了然後本期是內政委會的委員移民署也常常在訴苦專情隊人力500人失聯移工數量是8萬多人而且還有在繼續增加的可能性所以這是問題如果我們不從問題的根源去下手的話恐怕這問題永遠解決不完你抓檢舉也好或抓也好大概也是抓沒有完所以移工問題的三大原因這其實監察院也有提相關的報告所以第一個問題大概叫待遇不佳
transcript.whisperx[503].start 13793.105
transcript.whisperx[503].end 13813.804
transcript.whisperx[503].text 所以走投無路嘛第二個叫做彈性不足也就是有關於自由轉換工作的一些配套其實還不是那麼的完善第三個是財務壓力當然來自於很多停額周顯或者是直接講無良仲介當初在引入的時候就對於移工本人收高額仲介費以至於他們在來台之前就背了大量的債務那這幾個綜合因素下面
transcript.whisperx[504].start 13814.949
transcript.whisperx[504].end 13835.414
transcript.whisperx[504].text 就就變亡命之徒啦因為走投無路啊我按照正常的法規流程去做正常的工作待遇又不好我又沒有辦法這個趕得上有些是甚至是放高利貸這樣一個狀況那當然就挺而走險啊然後有些狀況檢察院的報告也講你在失聯的狀況之下賺的搞不好比合法的還多啊所以這三件事情呢其實本期是希望這個勞動部
transcript.whisperx[505].start 13837.415
transcript.whisperx[505].end 13846.562
transcript.whisperx[505].text 你要持續的提出解決方案嘛我們要把這部分這三個問題解決完之後你才有辦法壓制住這事件移工的數量嘛所以針對這三個問題勞動部現在有沒有什麼精進的作為
transcript.whisperx[506].start 13848.011
transcript.whisperx[506].end 13871.057
transcript.whisperx[506].text 簡單回答一下因為我們還有後面的題目報告委員其實移工在產業移工部分他近來一定是適用基本工資這個沒有問題主要是家庭看護工這個部分他其實不適用勞基法因為包括我們本國家事工也一樣不適用但是在前年因為本來是17000我也把他提高到20000提高到20000
transcript.whisperx[507].start 13871.877
transcript.whisperx[507].end 13900.037
transcript.whisperx[507].text 那未來當然針對這些待遇的問題我們會去滾動的檢討就是基本上經濟因素也是很重要的一個從那個進步的價值來講當然慢慢慢慢要一致嘛要有非其次的待遇但本席也明白啦他這知識體大嘛這跟我們國家的經濟相關使用家庭都是比較弱勢的也有弱勢家庭的問題我同意所以本席希望啦多放一點重點在解決他們本人的財務壓力上也就是針對仲介嘛
transcript.whisperx[508].start 13900.937
transcript.whisperx[508].end 13922.935
transcript.whisperx[508].text 對那你要該做定時的查核跟查緝嘛去了解到底有沒有哪些人在做這樣的事情然後又有押照的狀況我們國內我們是不容許我們是嚴格在查這個如果有這種情形是我們是縱罰然後甚至是撤照這是都是用很嚴密的手段因為時間有限針對這一部分就有關於仲介的管理你如何去避免這種
transcript.whisperx[509].start 13924.676
transcript.whisperx[509].end 13941.022
transcript.whisperx[509].text 的財務壓力然後逼的移工走投無路的狀況發生是不是會後提供一個書面報告給本席也提供當然就順便提供給衛航委員會委員讓他們做問證參考好不好這第一個好第二個本席其實今天更重要的講的是沒有失聯的移工我不要講管理講管理好像有點上對下不太好不太尊重要輔導
transcript.whisperx[510].start 13942.262
transcript.whisperx[510].end 13968.177
transcript.whisperx[510].text 因為現在我們了解的狀況是大概手續辦完之後經濟部希望繼續產業發展多開放勞動部的配合辦理等等那進來之後如果遇到問題丟個移民署查緝可是問題是沒有失聯的移工如果沒有長期的對話沒有長期去關注他們的狀況沒有進行一定的輔導措施他其實也會造成若干社會問題我舉幾個簡單的例子比如說他們不知道不能在10點以後在公園唱卡拉OK比如說他們不知道這個微型電動二輪車不能亂停
transcript.whisperx[511].start 13969.958
transcript.whisperx[511].end 13992.342
transcript.whisperx[511].text 這不是歧視的意思他可能在他的國家沒有相關的法源可是在台灣的環境裡面這個是不被台灣的社區所接受的所以這種界面的融入啊如果沒有長時間的追蹤沒有說我定期的去做宣導也好或者是協助他們融入的時候即便他是沒有失聯的移工他也會有沒有辦法融入的問題也會讓成本外部化
transcript.whisperx[512].start 13992.922
transcript.whisperx[512].end 14013.523
transcript.whisperx[512].text 那第二個我講的是從他們的人權的角度來看部長應該清楚啦我想這我們就打開天窗說亮話有沒有雇主他弄進來之後然後一大堆移工住在一個鐵皮屋裡面的應該是有吧對不對這實際上來講是蠻不人道的待遇那當然他們可能基於要打拼討生活他可以接受可是終究來講這不是一個進步的作為嗎
transcript.whisperx[513].start 14014.364
transcript.whisperx[513].end 14033.144
transcript.whisperx[513].text 那這些凡此種種都是他來到台灣工作之後才開始發生衍生出這一堆問題難道我們的政府不應該有一定的角色嗎部長我們現在針對沒有失聯的移工我們的定期的輔導機制是什麼我們有沒有要求台灣的雇主你在享受相對低廉的人力成本的時候有負擔更多的
transcript.whisperx[514].start 14033.724
transcript.whisperx[514].end 14050.855
transcript.whisperx[514].text 責任輔導的責任跟義務有沒有這樣子的一些說法請簡單說明一下報告委員像我們各地方政府都有訪查員剛進來的移工剛入國我們一定會去了解他整個生活的狀況然後雇主在移工的管理上他也要善盡他的責任這個部分我們都會去
transcript.whisperx[515].start 14051.615
transcript.whisperx[515].end 14078.412
transcript.whisperx[515].text 有相關的規定去要求那如果沒有也有相關的一些處罰然後包括移工的權益包括了解本國的法令或者他本身的權益問題我們都有透過多元的管道包括他們多餘的我從那個報告裡面你就看到當初就講說一站式服務也就是入境的時候就把這次處理完了可是我恰恰覺得這是有問題的因為他不應該是一站式服務他不應該一次處理完他反而應該是定期的訪視定期的了解狀況
transcript.whisperx[516].start 14079.332
transcript.whisperx[516].end 14100.999
transcript.whisperx[516].text 好不好一樣因為時間到了啦我也不要耽誤會議時間針對僱主在這一部分的輔導管理的一些責任還有仲介業者也許在裡面也要擔負一定的社會責任嘛對不對有沒有給產業一定的管理準則或者是義務這些部分我也要求會後好不好你會長資料我們來長期追蹤可以嗎我們一起來解決這個問題讓移工可以好好的融入台灣社會可以嗎好謝謝部長辛苦了
transcript.whisperx[517].start 14103.881
transcript.whisperx[517].end 14119.173
transcript.whisperx[517].text 謝謝牛委員齁那我們中午不休息大家可以用餐齁那如果想要上廁所也不用就可以直接直接去齁我們中午就不休息啦這樣可以嗎部長可以可以啦齁OK好那我們接下來請劉建國委員好謝謝趙委又請部長請許部長部長要不要先吃便當
transcript.whisperx[518].start 14132.469
transcript.whisperx[518].end 14153.055
transcript.whisperx[518].text 委員好部長好部長我想今天要來跟討論就是這個缺工問題還有中高齡及高齡者的就業的促進我想中高齡及高齡者的就業促進法也在你的任內推動完成那我們到事實上
transcript.whisperx[519].start 14153.854
transcript.whisperx[519].end 14172.976
transcript.whisperx[519].text 我簡單講幾個背景的資料然後我們來做一個警示嘛齁這個人力銀行的相關的資料說臺灣已住宿餐飲零售電子資訊軟體半導體以及一般製造業陷入嚴重的缺工狀態那我們報告裡面說這波缺工潮起因於3年前的疫情
transcript.whisperx[520].start 14174.237
transcript.whisperx[520].end 14200.118
transcript.whisperx[520].text 導致各行各業人力流失疫情結束後民眾消費力回復但產業界人力流失的缺口卻無法及時補充導致缺工情況發生這是你們報告你認可嗎講到這邊你認可嗎缺工廠是因為這三年的疫情所造成的主因嗎還是這三年之後才有這個缺工廠是因為疫情的關係嗎
transcript.whisperx[521].start 14201.806
transcript.whisperx[521].end 14224.841
transcript.whisperx[521].text 包括少子化,勞動力缺口也不斷的擴大但是我們可能是針對疫情之後因為有一些產業它缺工一直補不足啦尤其像餐飲服務業我們是特別針對這部分來做說明應該藝術蠻多的啦但是只有單純寫這樣我是覺得不夠周全了是不是貴部瞭解還是
transcript.whisperx[522].start 14227.819
transcript.whisperx[522].end 14251.321
transcript.whisperx[522].text 所以所以好那我們就前面就不談我們台後面的那部長認為你們評估起來這個缺工潮會多久?這樣大量缺工會不會成為台灣社會以後的常態?這個會更嚴峻啦因為早子化以後這個我就覺得整個人口勞動力人口他其實一直一直會降低的對阿你們部要怎麼做這個因應?
transcript.whisperx[523].start 14253.055
transcript.whisperx[523].end 14273.054
transcript.whisperx[523].text 因為我們要開放一些勞動力,比如說包括青年的部分,婦女在就業,還有中高齡高齡者,我們是比較小心把它定義成壯世代希望他們能續留職場或重返職場,那也希望說僱主能夠善用這些壯世代的勞動力,不要有這個憐憫歧視的問題
transcript.whisperx[524].start 14275.461
transcript.whisperx[524].end 14286.521
transcript.whisperx[524].text 撞四代勞動力現在撞四代勞動力是我覺得是政府好像完全沒有辦法去掌控而且引導上的力道也是非常薄弱的
transcript.whisperx[525].start 14287.279
transcript.whisperx[525].end 14308.474
transcript.whisperx[525].text 我們其實一直在推計畫啦吼那像我們現在有發覺到說55歲以上的這個勞參率喔比起韓日大概低了到20%所以我們現在有推一個壯世代的一個計畫希望能夠三年計畫希望能夠在這三年內多增加30萬的這個55歲以上壯世代能夠
transcript.whisperx[526].start 14313.84
transcript.whisperx[526].end 14341.962
transcript.whisperx[526].text 進入到職場來提高他的勞參率你先把他定位55歲以上叫做壯士代然後你預計多久要提高到30萬可以進到職場3年3年內了對從2024年開始起算去年去年就起算了去年5月開始ok去年5月那到現在快也將近快1年了嘛剩下幾個就1年嘛對那30萬到目前實際上有進入到這個陳主委所講的壯士代對有多少
transcript.whisperx[527].start 14343.28
transcript.whisperx[527].end 14346.864
transcript.whisperx[527].text 站比是多少?這30萬的站比是多少?大概19萬已經進到19萬了那效益不錯啊19萬了
transcript.whisperx[528].start 14356.784
transcript.whisperx[528].end 14361.049
transcript.whisperx[528].text 我要修正一下,這個是除外是中高齡以上,但是55歲的我要再請他們的數據再
transcript.whisperx[529].start 14375.966
transcript.whisperx[529].end 14396.065
transcript.whisperx[529].text 再分離一下你現在是講中高齡,中高齡就從45歲到64歲嘛對不對?對對對阿所以這個要再算啦那剛剛對數字不對我看了一下那不是不是壯士代55如果這樣就不需要再引進那個移工進來了嘛對不對?如果照這樣的力道阿就是我們移工還是對於缺工這是得證了
transcript.whisperx[530].start 14397.746
transcript.whisperx[530].end 14410.835
transcript.whisperx[530].text 移工是針對本國人不願意從事的產業那我們現在壯士在這個當然是希望不是不是不是部長我想那些背景資料你都比我清楚但是國會這邊有特別提到他在2033年臺灣整體的勞動力重心也將從現在的40到19歲轉移到50到59歲
transcript.whisperx[531].start 14419.461
transcript.whisperx[531].end 14445.803
transcript.whisperx[531].text 就呼籲你剛才的講法也說臺灣在10年內整個勞動力的市長將產生這個天翻地覆的大變動所以國會事務組也曾公開表示人口的紅利減少的速度比預期快坦白講這句話我是很難接受政府的預期怎麼會預期的這麼不精準這其一其二政府預計要在2030年前引進40萬外來的人口就業
transcript.whisperx[532].start 14447.396
transcript.whisperx[532].end 14461.289
transcript.whisperx[532].text 這是國會講的才能解除警報喔所以我才會講說如果面對這樣的事情國會也這樣的對外做這樣的表達那我們的因應知道在勞動部的核心主要的政策是什麼
transcript.whisperx[533].start 14462.076
transcript.whisperx[533].end 14482.086
transcript.whisperx[533].text 那個報告委員剛剛國話會那個203040萬那個是中階以上的對包括白領灰領我們所謂灰領橋外生他是要在這8年內要希望引進40萬那像勞動部的部分就是中階技術人力我就是把現在在臺灣的藍領低階的這些勞工
transcript.whisperx[534].start 14485.228
transcript.whisperx[534].end 14509.042
transcript.whisperx[534].text 他具有技術他心智大一點的門檻現在他轉成中階技術人力來填補我們現在中階人力的不足他這個地方是這樣子我現在先說比較小的範圍因為特別提到中高齡及高齡者的就業蘇慶華也在部長任內來推動完成對不對你看一個數據老花鼠臺灣中高齡就業人口60到64歲都還有39.6
transcript.whisperx[535].start 14511.874
transcript.whisperx[535].end 14536.585
transcript.whisperx[535].text 但是65歲以上就直接掉到9.6如果你對比其他的國家你自己看齁臺灣65歲以上的勞參率低了將近其他對比其他國家是19到37這明顯偏高嘛這你們認可嘛齁那不如今天在報告中也闡述啦齁中高齡就45到6歲勞參率有逐步在提升就曾委員剛才所講的嘛齁但但剛剛委員特別提到國會講
transcript.whisperx[536].start 14538.291
transcript.whisperx[536].end 14559.171
transcript.whisperx[536].text 不到10點時間就是從40歲到19歲會轉移到50到59歲這個是我如果要檢視部長在推動中高齡及高齡的就業的這個政策有成效通過法律的制定然後推動整個執行面有成效還是還是這個整體的勞動力的重心已經朝向中高齡的區塊去做螺蟻到底是哪一個到底是哪一個
transcript.whisperx[537].start 14562.625
transcript.whisperx[537].end 14576.964
transcript.whisperx[537].text 我要跟你討論是本質問題啦都會有對因為未來的勞動力恐怕還是會往中高年這邊靠因為出生少嘛我覺得部長不要誤判一般人要講三次
transcript.whisperx[538].start 14577.685
transcript.whisperx[538].end 14606.747
transcript.whisperx[538].text 我就講不要誤判N次啦齁如果中高齡的就業政策推得好齁65歲以上的長輩應該是現在會以半退休的狀況嘛對不對齁持續在職場上服務但是目前台灣為此的65歲退休之後沒事做的現在僅有9.6%還在職場服務所以我要跟部長討論是說你認為啦齁跟普遍職場仍然要求勞工必須要一個完整的勞動工時有沒有關係啊
transcript.whisperx[539].start 14608.783
transcript.whisperx[539].end 14634.493
transcript.whisperx[539].text 有沒有?完整的勞動工時?對嘛!職長薩爾普遍認為勞動還是一個完整的勞動工時有沒有關係?這個我是覺得針對不同的好像這些世代應該有可能不同的勞動工時我現在針對高齡者跟高齡者高齡者他可能要有彈性的工時啦對阿你覺得你覺得現在的這樣的我們的這些環境對高齡者
transcript.whisperx[540].start 14635.473
transcript.whisperx[540].end 14655.861
transcript.whisperx[540].text 有達到友善有達到彈性這部分還要在很大的努力空間很大的努力空間部長有回答問題了因為我覺得現在你看要讓65歲的這些高齡者因為體育上本身就有一些障礙了對不對然後他還要克服很多問題除此之外讓高齡者要有一個完整的8個工作
transcript.whisperx[541].start 14656.882
transcript.whisperx[541].end 14669.151
transcript.whisperx[541].text 的這個時間來從事他的退休之後的就業的一個環境這既不友善也不健康所以他的勞參率當然就很低我是要從這部分跟部長來做一個討論那你看喔
transcript.whisperx[542].start 14672.594
transcript.whisperx[542].end 14695.039
transcript.whisperx[542].text 我們責任時至於有一個統計嘛,台灣外送人員從2019年四萬五千人的人數增加到2022年的十四萬五千人等於三年成長百分之三百然後人力營養更發現外送人大多是來自這個製造業的基層跟餐飲業這個是一個板塊的很大很大的很快的速度在
transcript.whisperx[543].start 14695.464
transcript.whisperx[543].end 14718.754
transcript.whisperx[543].text 在做一個轉移嘛對不對這是你們的資料嘛然後這個WTW2023的組織跟人才的關鍵報告中指出歷史代齁人才最關鍵的因素他不再是薪水而是職矮的發展機會他們相當在意公司是我提供彈性工時及和員工福利以及這個成功做內容找到這個使命感
transcript.whisperx[544].start 14720.278
transcript.whisperx[544].end 14741.47
transcript.whisperx[544].text 這個是你們的資料支撐會在去年7到9月實行彈性工時的實驗一共有105位的同仁參加參加的員工一個月內要滿足168的總工時但不拘束員工的上下班時間和工作定點實驗的結果證實工作的產出跟表現並沒有變得不好
transcript.whisperx[545].start 14742.31
transcript.whisperx[545].end 14744.612
transcript.whisperx[545].text 對中高齡及高齡者的就業環境應該要有所來做這個因應才對嘛我是要很
transcript.whisperx[546].start 14760.68
transcript.whisperx[546].end 14783.985
transcript.whisperx[546].text 很誠懇的提醒部長這事情齁那你們自己已有結合相關部會嘛齁在偏鄉推動這個婦女再就業計畫然後什麼婦女什麼兼顧家庭勞動部提供僱主公使調整獎勵還有公使調整獎勵嘛齁然後針對僱主提供有照顧家庭需求的婦女比較彈性公使調整其中就有舉出這個系統貴供應商的成功案例
transcript.whisperx[547].start 14785.198
transcript.whisperx[547].end 14813.793
transcript.whisperx[547].text 然後李肅岳哲也併顧鍾高齡也提出了相對的這個彈性的工時多半是這個彈性工時的班表這個你們又有在做啊但是好像那個量能好像那個速度緩不濟急沒有辦法追過人口老化沒有辦法追過這些想要在給高齡者要從事這個就業的環境裡面提高他們的意願這個我覺得很大大的討論空間
transcript.whisperx[548].start 14815.225
transcript.whisperx[548].end 14840.397
transcript.whisperx[548].text 我是覺得雇主可能觀念的改變非常重要因為面對這個勞動力的短缺大家可能對於這個勞動力的來源要更能夠接受這些壯世代或者二度就業婦女這些所以剛剛您委員講的一些話坦白講我心裡有戚戚焉政府應該要扮演更強大的這樣的一個力道我們這個法律法律部長你記得什麼時候通過的嗎
transcript.whisperx[549].start 14842.574
transcript.whisperx[549].end 14845.338
transcript.whisperx[549].text 201919吧2019108年嘛對不對但是我們上路往2020那我108啊
transcript.whisperx[550].start 14850.188
transcript.whisperx[550].end 14871.181
transcript.whisperx[550].text 因為是108公告的109才上路因為疫情109、110、11、12、13、15年可以大大來討論當然要檢討了嘛快速來盤整嘛好不好那我們這個高齡者的勞動率可以提高嘛那這個板塊移動到底是因為你們的政策推動的很好很有力道還是還是這個是
transcript.whisperx[551].start 14873.622
transcript.whisperx[551].end 14873.842
transcript.whisperx[551].text 接下來請王宏威委員
transcript.whisperx[552].start 14901.015
transcript.whisperx[552].end 14903.938
transcript.whisperx[552].text 謝謝主席我請徐部長徐部長好部長好委員好最近大家又開始關心勞保基金會不會破產會不會在2018年破產那麼2028 對不起2028年破產所以你也認為2028那是110年計算報告跟委員報告我們今年要再重新做計算
transcript.whisperx[553].start 14929.46
transcript.whisperx[553].end 14943.484
transcript.whisperx[553].text 我現在的問題是請教你在去年因為稅收超生4500億的關係那麼當時除了普發現金之外有部分拿來撥補包含台電還有我們勞保基金對不對當時去年撥補550億300
transcript.whisperx[554].start 14948.686
transcript.whisperx[554].end 14968.054
transcript.whisperx[554].text 去年 各位幫我們的特別預算是撥補勞保300億分3年去年先給100億然後另外450是公務預算公務預算的撥補所以去年一共撥補了550億是含公務預算的450加公務預算加特別預算100億所以剛好550
transcript.whisperx[555].start 14970.275
transcript.whisperx[555].end 14970.856
transcript.whisperx[555].text 那我想請教一下你們會爭取你們會爭取那個
transcript.whisperx[556].start 14989.328
transcript.whisperx[556].end 15000.836
transcript.whisperx[556].text 今年稅收超徵大概3800億的一個水準然後像去年一樣然後再爭取再多撥補到勞保基金裡面
transcript.whisperx[557].start 15019.369
transcript.whisperx[557].end 15034.95
transcript.whisperx[557].text 那你們希望能夠爭取到多少?我是希望不低於去年的300 不低啊我是希望不低於如果能夠有多的盈餘我們希望能夠多爭取一些對我們財務的穩定是有很大的幫助
transcript.whisperx[558].start 15035.25
transcript.whisperx[558].end 15063.493
transcript.whisperx[558].text 好那部長我跟你講你的期待可能會落空因為我剛才才在財政委員會去問過那個朱澤民主計長他說現在看起來好像是三千八百億但是呢七折八扣又包含他要發行公債等等喔那麼事實上只剩下一千五百億那你也知道經濟部長剛委員他們也是去爭取了一千五百億但是朱澤民主計長的意思說如果
transcript.whisperx[559].start 15064.153
transcript.whisperx[559].end 15084.16
transcript.whisperx[559].text 一千五百億全部都補給台電的話那麼明年的預算會非常困難明年的預算就會非常困難編起來因為已經沒有剩餘所以也就是說現在呢大家都看到這個稅收這個稅收超車的這筆錢可是呢這個餅就是這麼大尤其台電的部分現在他們
transcript.whisperx[560].start 15085.029
transcript.whisperx[560].end 15111.119
transcript.whisperx[560].text 比較講不好聽獅子大開口啦他們要爭取1500億所以你這300億我覺得有困難好那如果在這樣的狀況之下那麼因為現在有很多立委都要求就是說要提出勞保年金的改革方案來改善或者是延緩我們勞保基金可能破產的這個年限那你有什麼辦法嗎
transcript.whisperx[561].start 15112.543
transcript.whisperx[561].end 15136.37
transcript.whisperx[561].text 報告委員因為大概幾個面向大概大家可能需要跟這個勞資團體還有這個各界在做一些溝通還有收集他們意見因為撥補這個面向應該我們現在都持續在做了撥補大概是最容易有人給你錢就立了對持續但是這也是很重要的面向因為所有的改革方案裡面撥補是一定要的
transcript.whisperx[562].start 15136.93
transcript.whisperx[562].end 15159.742
transcript.whisperx[562].text 而且部部的金額會連動到其他的面向他的調整的幅度所以其他的部分包括說費率的調整包括平均性質的採集年間包括年金給付率是不是要做調整這個都還要再爭取大家因為主要是像費率的調整會牽涉到資方的負擔那這個
transcript.whisperx[563].start 15163.724
transcript.whisperx[563].end 15164.664
transcript.whisperx[563].text 520之前你們會有具體的方案出來嗎?
transcript.whisperx[564].start 15183.64
transcript.whisperx[564].end 15193.088
transcript.whisperx[564].text 包括我這個部分我還沒辦法回答您所以我看起來要留待新政府來做了對不對現在你們短期呢只有可能去能夠爭取這個撥補的金額好剩下一點時間我要特別講就是我必須
transcript.whisperx[565].start 15200.394
transcript.whisperx[565].end 15219.034
transcript.whisperx[565].text 我們要改善嫂子化但是呢我們現在對其實生小孩的很多的年輕父母事實上是非常辛苦因為我們知道外籍幫傭他要去拿到你們所規定的點數16點非常困難是可以看一下那個請我們部長看一下是
transcript.whisperx[566].start 15219.414
transcript.whisperx[566].end 15241.648
transcript.whisperx[566].text 如果我們要申請到外籍的幫傭那按照你們的點數我把它算一下有個狀況兩個兩歲以下的子女要配上78歲以上的長者你才有16點那如果你有三個子女在五歲以下比如說兩歲三歲五歲還不夠你還要再加上79歲以上的長者才有16點以上
transcript.whisperx[567].start 15245.03
transcript.whisperx[567].end 15265.18
transcript.whisperx[567].text 這個太困難了啦所以我覺得我們既然說要改善草子化減輕我們生小孩的負擔另外一方面我們在外籍幫庸卻這麼嚴苛我剛講這個這個狀況是根本很少的家庭可以達到這樣的狀況所以我趕快我具體的在這邊的
transcript.whisperx[568].start 15266.721
transcript.whisperx[568].end 15276.615
transcript.whisperx[568].text 要求和建議是我希望你們能夠去修正這個標準第一家裡有一名6歲以下輕度或中度的
transcript.whisperx[569].start 15277.999
transcript.whisperx[569].end 15304.269
transcript.whisperx[569].text 韓病兒就可以申請外籍幫傭我真的有很多朋友家裡一個韓病兒非常非常辛苦然後另外家裡面有兩名4歲以下的幼兒已經很辛苦了現在願意生就很好還給你生兩個然後還這樣的密集的生是不是我們也應該給他們一些在我們政策上的資助政策資助另外我希望你們這16
transcript.whisperx[570].start 15305.669
transcript.whisperx[570].end 15305.689
transcript.whisperx[570].text 對不對?
transcript.whisperx[571].start 15332.288
transcript.whisperx[571].end 15335.391
transcript.whisperx[571].text 謝謝王宏威委員接下來請張雅玲委員張維豪有請部長謝謝請許部長
transcript.whisperx[572].start 15358.755
transcript.whisperx[572].end 15375.732
transcript.whisperx[572].text 我的螢幕這邊沒跳三位你好你好欸抱歉我的投影片這邊還沒有出來投影片投影片正在用是嗎喔好那
transcript.whisperx[573].start 15379.335
transcript.whisperx[573].end 15398.095
transcript.whisperx[573].text 部長您好那在準備投影片的時間喔最主要今天是想跟您討論就是前面其實也有其他委員有提到就是有關於輕職假的部分喔還有所謂的生產照顧假那我想喔其實大家現在這幾年都非常關注所謂的少子化的問題喔我們一直在講少子化是一個國安危機那我現在時間開始介紹好不好
transcript.whisperx[574].start 15399.176
transcript.whisperx[574].end 15415.338
transcript.whisperx[574].text 那就是說其實因為我過去在民間就是一直非常關心我們的兒童的福利那其實我也發現就是聯合國兒童基金會其實有講一件事情就是我們如何去增進勞工福祉來推動這個所謂的家庭友善政策那在去年呢
transcript.whisperx[575].start 15416.059
transcript.whisperx[575].end 15431.286
transcript.whisperx[575].text 日本也成立了兒童家庭廳他們也發布了相關的政策其中一個很重要的闡述就是少子化要解決的一件事情不是只有叫女生媽媽家長一直生小孩我們必須要提供更完善的家庭支持政策
transcript.whisperx[576].start 15432.566
transcript.whisperx[576].end 15456.936
transcript.whisperx[576].text 那我想要跟部長說一下我們看到這張表其實大部分這個我們勞基法是規定每週工時40小時雖然我們持續的在改建但是加班還是家長的共同日常這個每週工時不管是男生女生都是超過40小時的那瑞福部其實去在11年的時候有一個統計是在講工作家庭
transcript.whisperx[577].start 15459.225
transcript.whisperx[577].end 15486.74
transcript.whisperx[577].text 兩頭燒這描述我們的家長其實他雖然工時很他平常工時已經很長了他他要帶小孩的時候他根本沒有時間有將近四成的家長是沒有時間陪小孩了那我們去年在特工盟的民間的團體他也做了一個資料就是說小孩也抱怨就是這個工時很長老小孩也抱怨說爸爸媽媽平常已經把我留在課後班補習班我沒有時間照顧也就算了連週末他都很累
transcript.whisperx[578].start 15487.54
transcript.whisperx[578].end 15504.054
transcript.whisperx[578].text 好懶得帶我出去玩所以變成他可以出去玩這件事情一定是偶一為之的奢侈那其實玩直接的影響到我們兒少的一個身心健康好造成一些社會的身心的問題那我們雖然有留職停薪的這個育嬰育嬰假
transcript.whisperx[579].start 15505.205
transcript.whisperx[579].end 15526.052
transcript.whisperx[579].text 但是我們也知道我們請的人數一直沒有很多吼我們可以來看看這個成長率喔暈流停很少人用最主要是在過去這兩個高峰只有出現在我們修訂的剛修訂這個暈假的時候還有疫情期間那為什麼呢為什麼我們的暈流停很少人用呢我想要請教我們的部長其實我們
transcript.whisperx[580].start 15531.175
transcript.whisperx[580].end 15550.888
transcript.whisperx[580].text 報告委員當然之前可能有一些不夠彈性那我們其實在前年修法應該是前年修法我們也放寬然後也可以比較短時間的申請然後父母親可以同時申請所以我們其實也一直在滾動檢討覺得說如果有不好用的不夠友善的盡量來把它改
transcript.whisperx[581].start 15551.308
transcript.whisperx[581].end 15577.023
transcript.whisperx[581].text 好謝謝部長所以我們現在最新因為我們現在的法規我們來看還是要一個月那我想從我自己的生命經驗來出發就是我以前在職場上班的時候我一年的休假其實有12天而是因為我想要提早去接我小孩因為我老闆是希望我可以配合但是我沒有辦法因為保姆不願意配合所以我只能提早我必須把我所有一整年的特休用掉我才能夠去提早接我小孩那再來就是說我想還有一個很現實的問題就是說現在
transcript.whisperx[582].start 15578.524
transcript.whisperx[582].end 15579.524
transcript.whisperx[582].text 其實包委像這個喔
transcript.whisperx[583].start 15605.974
transcript.whisperx[583].end 15624.714
transcript.whisperx[583].text 當然就是說現在我們也請同仁在做一些研議啦其實這件事情一直朝鮮委員都有提出啦就是那個讓這個能夠零碎化來照顧不是只有集中在一段時間那我是覺得這個可以雙軌去處理啦就是說這種零碎化的運用恐怕有些
transcript.whisperx[584].start 15625.715
transcript.whisperx[584].end 15626.376
transcript.whisperx[584].text 期也可能不適合
transcript.whisperx[585].start 15656.555
transcript.whisperx[585].end 15678.144
transcript.whisperx[585].text 這個我們都會通盤來來演繹規劃啦因為就是說這種事辦我是覺得可能一個制度先事辦有些行業是可以的有些是沒有辦法因為像輪班排班同意瞭解可以的部分我們包括年紀或什麼我們可以先理一下然後先推推看啦如果有可以的或許將來未來修法或怎樣都可以來做
transcript.whisperx[586].start 15678.524
transcript.whisperx[586].end 15702.693
transcript.whisperx[586].text 好那不好意思我想請部長因為現在看起來已經有一些方向有一些方向出來了那是不是可以請部長把相關的一些資料在大概什麼時候可以提到我們辦公室呢一些規劃的方向好他說提資料好我們一個月內也去跟委員做說明好謝謝部長謝謝好謝謝張雅玲委員接下來請黃仁委員
transcript.whisperx[587].start 15722.819
transcript.whisperx[587].end 15724.985
transcript.whisperx[587].text 有請部長請許部長黃偉昊
transcript.whisperx[588].start 15731.171
transcript.whisperx[588].end 15755.179
transcript.whisperx[588].text 國會推估的15歲到65歲的工作人員年齡人口持續下滑將從112年到119年的總共有7年減少了113萬人口基層的勞動勞力嚴重不足製造業營造業服務業等行業的缺工問題非常的嚴重
transcript.whisperx[589].start 15755.999
transcript.whisperx[589].end 15781.983
transcript.whisperx[589].text 那就我針對原住民的問題來討論因為現在很多這個大量的移工進來的時候衝擊到原住民的就業的問題你們有沒有相關的配套針對國人原住民的就業勞工的方案你能說幾句吧
transcript.whisperx[590].start 15783.271
transcript.whisperx[590].end 15801.237
transcript.whisperx[590].text 報告委員這些缺工的產業我們還是以優先媒合國人就業為主就是說你必須媒合不到我們才會就是說或者你雇主這個招募不到才會引進這個
transcript.whisperx[591].start 15803.298
transcript.whisperx[591].end 15816.976
transcript.whisperx[591].text 所以今天勞動部改善疫情後的產業復甦所形成切工的現象應該從獎勵勞工的就業及鼓勵雇主禁用的兩大面向
transcript.whisperx[592].start 15819.739
transcript.whisperx[592].end 15839.037
transcript.whisperx[592].text 就是應該朝向這個嘛因為疫情之後的這個缺工擴大就業方案從112年到6月15日至專案缺工就業獎勵事辦實施要點又回溯到同年5月1日生效事辦期間至113年6月30號為止那這個方案
transcript.whisperx[593].start 15846.01
transcript.whisperx[593].end 15863.518
transcript.whisperx[593].text 就是也要促進媒合能夠讓我們的就業的原住民更能夠保障那另外是我特別要講的是針對安定基金安定基金的立場是
transcript.whisperx[594].start 15865.899
transcript.whisperx[594].end 15885.285
transcript.whisperx[594].text 從2023年第一季原住民的就業狀況的調查中原住民勞動力人數291424人投入行業比例最高皆為營造工程最多占17.8%且原住民失業率3.62%高於全體失業率3.56%
transcript.whisperx[595].start 15893.687
transcript.whisperx[595].end 15916.078
transcript.whisperx[595].text 那這個部分那為什麼在安定基金裡面是正式園民會爭取安定基金的這個方案那為什麼會有安定基金的委員會有餘力針對這個部分哪些他們提出的方案餘力是什麼
transcript.whisperx[596].start 15918.086
transcript.whisperx[596].end 15946.062
transcript.whisperx[596].text 報告委員因為我們的那個救安委員會他是一個合意制啦齁那每個提案都是委員要去他們會表達意見齁那去做一個決議那因為這個當初他們認為說勞保費的部分我記得委員是認為說可能其他弱勢族群也是會來比照援引齁那還有他認為說應該是不是有其他的包括原民會這邊是不是有其他一些作為齁
transcript.whisperx[597].start 15947.463
transcript.whisperx[597].end 15952.076
transcript.whisperx[597].text 好在請委員請委員會這邊再評估啦他今天我特別要講的是第一個
transcript.whisperx[598].start 15953.453
transcript.whisperx[598].end 15979.806
transcript.whisperx[598].text 所謂的保障優先保障原住民的就業方案這個方案本來就應該有的按照比例對嘛那所以已經跟你們勞動部就業安定基金這個金管會爭取到3.5億的經費這就是鼓勵補助事業單位的促進原住民的就業計畫的方案
transcript.whisperx[599].start 15980.606
transcript.whisperx[599].end 16002.247
transcript.whisperx[599].text 那為什麼這個安定基金的委員會會有其他的意見每個委員都是他都是代表他本來就可以表達不同的看法對嘛那既然應該要保障原住民的就業方案的話是應該不會有其他太多的意見吧這個
transcript.whisperx[600].start 16006.974
transcript.whisperx[600].end 16034.152
transcript.whisperx[600].text 保障原住民的就業跟這個勞保費的負擔的是是兩個問題啦因為兩個問題當然沒有錯那不是就他們的就業方案的一個協助我們勞動部一直很積極在所以我所以我這邊建議說那個勞保費的負擔當然有些人認為說那是不是要針對特定族群這個可能大家要考慮一下公平性和平性那也請原民會再加強論述說明啦這個案
transcript.whisperx[601].start 16035.693
transcript.whisperx[601].end 16040.356
transcript.whisperx[601].text 因為這一次是大量的你們有採取大量的移工要增加的問題也就是會衝擊到原住民的就業我們沒有開放大量移工我們只是多一個來源果讓
transcript.whisperx[602].start 16061.408
transcript.whisperx[602].end 16073.814
transcript.whisperx[602].text 議員.
transcript.whisperx[603].start 16076.656
transcript.whisperx[603].end 16098.135
transcript.whisperx[603].text 謝謝黃仁委員接下來請葉元芝委員葉元芝委員葉元芝委員不在接下來請鄭天才委員鄭天才委員鄭天才委員不在接下來請洪孟楷委員洪孟楷委員洪孟楷委員不在接下來請吳春成委員
transcript.whisperx[604].start 16111.887
transcript.whisperx[604].end 16113.15
transcript.whisperx[604].text 主席有請徐部長
transcript.whisperx[605].start 16118.053
transcript.whisperx[605].end 16129.103
transcript.whisperx[605].text 部長好,我今天特別來寫壯世代要感謝你,有你真好因為長壽社會來臨,我在民間推動了壯世代推動了三年
transcript.whisperx[606].start 16142.054
transcript.whisperx[606].end 16161.983
transcript.whisperx[606].text 我們政府是普遍沒有人口學的概念就沒有這種長遠人口的計畫那感謝部長這一年來看到部長注意到這個問題把這個壯士代帶進了政府體系剛才看到劉建國委員也是出口都是壯士代顯然是部長帶動的這個風氣有看到他的成效
transcript.whisperx[607].start 16168.771
transcript.whisperx[607].end 16196.899
transcript.whisperx[607].text 所以呢這個這個長壽時代來臨我們經常把這個當作是這個這個衛福的一種思維就是一種照顧思維其實真正的未來這個高齡人口會佔臺灣人口的一半超越人半沒有一個社會能夠照顧一半用社福的思維來照顧一半人口的所以勞動其實勞動部是是一個很重要的解方
transcript.whisperx[608].start 16197.939
transcript.whisperx[608].end 16216.045
transcript.whisperx[608].text 是在這種長壽社會當中一個很重要的解放那看部長也是我們所有政府當中第一個有這種覺悟的人看到了這個問題看到了這個問題因為如果不改變的話那就會變成一場引髮大海嘯
transcript.whisperx[609].start 16217.891
transcript.whisperx[609].end 16232.131
transcript.whisperx[609].text 因法代效不僅是高齡者會臥倒連年輕人也沒希望了但是事實上如果勞動力處理的好他可以把它轉變成國家發展的動力那所以呢看到這個
transcript.whisperx[610].start 16233.786
transcript.whisperx[610].end 16248.879
transcript.whisperx[610].text 部長,我們勞動部有很多的政策的推出,55plus對於就業促進還有對於就業網合作的一些獎勵的一些措施
transcript.whisperx[611].start 16250.14
transcript.whisperx[611].end 16274.78
transcript.whisperx[611].text 都有看到這一些這方向都很好那也看到了部長不過現在比較讓我擔心了一點部長也講了這個沒有考慮要續任那說部長說這媒體上引用你的話說未來如果考慮跨業會善用勞動部的中高齡促進就業資源
transcript.whisperx[612].start 16276.081
transcript.whisperx[612].end 16294.734
transcript.whisperx[612].text 那比起中高齡更喜歡壯世代這個稱呼那請問一下部長為什麼喜歡這個稱呼因為我覺得其實我們現在的45歲以上的人其實都很健康那在人際還有經驗方面都是達到一個頂峰
transcript.whisperx[613].start 16295.796
transcript.whisperx[613].end 16316.337
transcript.whisperx[613].text 好那其實還可以很發揮啦可是常常尤其到5555歲以後常常會好像就自己覺得好像年紀衰退了會被歧視的我就說我們應該先自我期許喔對健康的身心靈來面對說我其實還是很壯的然後能夠
transcript.whisperx[614].start 16319.18
transcript.whisperx[614].end 16330.925
transcript.whisperx[614].text 續留職場或重返職場對這個部長這個作為我們壯世代的代言人可以嗎可以啊可以作為我們壯世代代言人喔好這個因為現在60歲以上已經600萬人了
transcript.whisperx[615].start 16334.827
transcript.whisperx[615].end 16349.732
transcript.whisperx[615].text 我們平均退休60.3歲也就是說這樣子龐大的退休人潮大家都不知何去何從所以壯士代鼓勵部長也以聲另外一個很重要的問題就是這個撫養比的問題
transcript.whisperx[616].start 16352.073
transcript.whisperx[616].end 16352.653
transcript.whisperx[616].text 這是唯一的解方了啦
transcript.whisperx[617].start 16377.245
transcript.whisperx[617].end 16389.539
transcript.whisperx[617].text 但是現在很關鍵的勞動部一個叫中高齡及高齡者就業促進法這個法當中有指所謂的中高齡的定義是指45歲到65歲
transcript.whisperx[618].start 16392.762
transcript.whisperx[618].end 16413.935
transcript.whisperx[618].text 然後我不曉得這個依據是從哪裡來45歲就是中高齡嗎?真恐怖欸因為很多人如果出國念書回來都快40歲了然後工作沒幾年就變中高齡了這太恐怖了吧所以我不曉得我們這個法的依據是從哪裡來然後高齡者65歲幾歲年齡然後我們就稱他叫高齡者像勞動部這個法的這個名稱就已經誤導了方向
transcript.whisperx[619].start 16421.782
transcript.whisperx[619].end 16449.143
transcript.whisperx[619].text 這個其實過去的這個想法所以部長你是第一個當初也是因為國際的標準大概就這樣子但是我覺得其實現在應該有不同的對就是因為部長第一個就是就整個不管世界怎麼樣臺灣都是世界第一的領先的我們應該已經覺得這個已經不適當的不符合事實的所以部長可不可以再因為這個法要改名叫壯士代就業促進法我樂觀其成
transcript.whisperx[620].start 16450.464
transcript.whisperx[620].end 16465.089
transcript.whisperx[620].text 樂觀七省部長我們可以努力嗎就是這個法因為你這個法包括我剛才從經濟委員會來經濟委員會中小企業獎勵條例就在獎勵這個他依據的就是你們勞動部的這個法你知道嗎所以他也是獎勵45歲如果說45歲我們勞參率沒有太大問題
transcript.whisperx[621].start 16471.96
transcript.whisperx[621].end 16499.446
transcript.whisperx[621].text 真正大的問題是大概55歲以上55歲以後那個勞產率急速的下降這個問題才會不然你那個獎勵45歲所有企業都去聘45歲不會去聘那個65歲的啦所以那個但是他的依據就可能來自於勞動部的這一個所以這個示範如果你把它改成壯士代就會促進法對整個的政府各部會應該有很大的那個啟發的作用
transcript.whisperx[622].start 16500.546
transcript.whisperx[622].end 16501.089
transcript.whisperx[622].text 謝謝部長 謝謝委員
transcript.whisperx[623].start 16505.652
transcript.whisperx[623].end 16532.926
transcript.whisperx[623].text 謝謝謝謝吳春成委員接下來請謝依鳳委員謝依鳳委員謝依鳳委員不在接下來請徐欣盈委員徐欣盈委員徐欣盈委員不在接下來請鄭正前委員鄭正前委員鄭正前委員不在接下來請蔡易瑜委員蔡易瑜委員蔡易瑜委員不在接下來請林德福委員林德福委員林德福委員不在
transcript.whisperx[624].start 16533.53
transcript.whisperx[624].end 16559.142
transcript.whisperx[624].text 接下來請吳秉瑞委員吳秉瑞委員吳秉瑞委員不在接下來請林楚英委員林楚英委員林楚英委員不在接下來請羅明財委員羅明財委員羅明財委員不在接下來請鍾嘉斌委員鍾嘉斌委員鍾嘉斌委員不在接下來請陳冠廷委員陳冠廷委員陳冠廷委員不在接下來請陳瑩委員
transcript.whisperx[625].start 16568.052
transcript.whisperx[625].end 16594.473
transcript.whisperx[625].text 謝謝主席我們今天請周署長請周署長署長好根據本席的調查您是這個治安署歷年來歷任以來最長壽的署長想必在這麼多年的你任內的這個7年當中呢有不少的豐功偉業那我想說這個這些攻擊呢
transcript.whisperx[626].start 16595.153
transcript.whisperx[626].end 16620.217
transcript.whisperx[626].text 都可以反映在數字上那因為數字會說話所以呢現在就讓我們繼續看下去來那個首先呢是這個檢查人力短缺的問題我要請教中央級地方現在有就是現在沒有填補的正職檢察員還有多少職缺那其中這個職業安全衛生的這個缺是多少
transcript.whisperx[627].start 16621.267
transcript.whisperx[627].end 16648.69
transcript.whisperx[627].text 報告委員那個缺是一直在浮動不過我們的正式的編制檢察院大概那個債值率大概是8成5到9成上下在一份浮動8成5到9成是對我們的值缺是一成左右好所以你就講成數那你沒有具體的這個統計數字對報告委員是浮動的那你今天下班前你把截至目前為止的數字給我們辦公室好不好
transcript.whisperx[628].start 16649.653
transcript.whisperx[628].end 16674.79
transcript.whisperx[628].text 我手邊的資料是在2月底是我們現在缺了是86人只有86人只有缺86人對是好那這些這些缺額是中央的比較多還是地方政府的這個缺額比較多各位報告委員都有像台北市我目前手邊資料是缺了9個新北市缺更多23個哪裡多啊新北市23桃園12台中16
transcript.whisperx[629].start 16678.581
transcript.whisperx[629].end 16703.079
transcript.whisperx[629].text 那我們的北區也缺8我就問你中央的缺額比較多還是地方政府缺額比較多好那據我所知這些缺額已經就是沒有補齊的這個時間其實已經過了很久了那跟這個去年的這個跟去年的今天比較那我們檢察員的這個人數是增加還是減少緣和沒有變人數減少
transcript.whisperx[630].start 16705.354
transcript.whisperx[630].end 16733.734
transcript.whisperx[630].text 原額沒變人數減少好那其實我聽到的聲音就是說新進的這個檢察員然後很多他就是受訓他是他是不來報到的或者是說他實習完的時候他就離職就轉掉了那這個是其實是令人非常擔心的問題因為衍生的這個接下來就是說我們衍生了這個我接下來要提問的這些問題
transcript.whisperx[631].start 16734.795
transcript.whisperx[631].end 16760.636
transcript.whisperx[631].text 我們看一下這個檢查檢查次量合理分配的問題有些地方政府呢的這個檢查單位反映只會分配讓他們難以負荷的這個檢查次量並沒有考慮到他們所承擔的這些工作壓力那這個問題其實是呈現到底合理的檢查次數的是多少的問題那署長
transcript.whisperx[632].start 16763.118
transcript.whisperx[632].end 16777.739
transcript.whisperx[632].text 以你的經驗一位檢察員每天合理的檢查場次是多少?我說的場次是工廠的場合理的場次是多少?那是兩場次早上一場下午一場
transcript.whisperx[633].start 16778.718
transcript.whisperx[633].end 16806.281
transcript.whisperx[633].text 一天場次但是這個場其實其實也有分大小嗎如果大到像那個台塑我想他一天你要叫他兩個台塑這麼大的場也是檢查不完的所以因為場次有分大小嗎那當然就是說按照我其實也有參考了這個年報你們這個年報的部分等一下在那邊
transcript.whisperx[634].start 16811.684
transcript.whisperx[634].end 16825.118
transcript.whisperx[634].text 好我有看了等一下那個因為在桌上吼我有看了你們這個年報吼你們大概就是年報大概一年一百一十一年吧統計的這個數量大概有這個總共
transcript.whisperx[635].start 16828.102
transcript.whisperx[635].end 16830.305
transcript.whisperx[635].text 111年的檢查機構的這個對事業單位實施這個你們的這個指案會的檢查有171177個場次看起來量還蠻多的17萬多
transcript.whisperx[636].start 16842.381
transcript.whisperx[636].end 16847.765
transcript.whisperx[636].text 好那但是17萬的這個場次我剛剛問的是工廠的場但是17萬這個場是一場兩場的場但是這一場這個場次你們所謂的場次呢其中還包含了這個起重機升降狙擊的座次33000多的座次還有這個鍋爐的6000大概鍋爐的6000座次
transcript.whisperx[637].start 16871.68
transcript.whisperx[637].end 16900.7
transcript.whisperx[637].text 還有這個壓力鍋壓力容器檢查兩萬九千座次還有其他高壓高壓氣體設備的座次也是三萬多這些都是座次那我剛剛把你們這個年報的統計一下這個座次的部分總共有十萬七千一百八十九件所以檢完之後呢
transcript.whisperx[638].start 16902.622
transcript.whisperx[638].end 16927.052
transcript.whisperx[638].text 大概還有7萬的場次你知道我在講什麼啦所以我剛剛把這些換算出來我是要告訴你們就是說在你這個因為我不曉得你今年按照你這樣子換算那我先請教你今年訂定的這個全年的目標是多少場次工廠的場
transcript.whisperx[639].start 16928.473
transcript.whisperx[639].end 16941.371
transcript.whisperx[639].text 那按照你現在就是說你們按照你們這樣算是那個還有場次的場那你覺得多少場工廠的場次跟多少你們算算的場次是是合理的
transcript.whisperx[640].start 16943.304
transcript.whisperx[640].end 16961.358
transcript.whisperx[640].text 謝謝委員提問,剛剛委員提醒那個委員機械設備是我們待遇檢查的量你們今年設定的這個全年的目標是要怎麼算我們認為我們同仁已經負荷非常重,我們會以去年維持去年的水平不要減少為原則
transcript.whisperx[641].start 16963.612
transcript.whisperx[641].end 16977.316
transcript.whisperx[641].text 但是你人數減少了所以我們今天就是跟委員報告我們因為我們那個行政院高雄部長支持我們現在有讓同仁有那個風險工作費的一些支持希望同仁能夠留任或留才因為給錢就了事了嗎加個3000塊5000塊就好了嗎
transcript.whisperx[642].start 16980.157
transcript.whisperx[642].end 17008.934
transcript.whisperx[642].text 因為以現有的這個檢察員努力的工作那換算你要算下來他可以合理完成的這個職安署所設定的年度目標嗎可不可以你說加了那個錢也是就加了錢就可以完成這個我講的是合理的目標合理的目標包含有效有品質的檢查所以委員提醒有關合理的工作量我們會再跟各檢察機構做進步的對所以你現在是不知道嗎如果按照你這樣的回答
transcript.whisperx[643].start 17015.929
transcript.whisperx[643].end 17027.635
transcript.whisperx[643].text 我這樣說好了啦我們從檢查年報來看我們檢查次量逐年增加嘛那重大值在傷亡的人數並沒有跟著減少啊而且喔
transcript.whisperx[644].start 17027.995
transcript.whisperx[644].end 17046.988
transcript.whisperx[644].text ﹏﹏
transcript.whisperx[645].start 17047.388
transcript.whisperx[645].end 17064.245
transcript.whisperx[645].text 會有一個什麼狀況你知道嗎因為大家為了要衝那個量去衝那個數字就是會變成為周署長去創造這個為你所定的這個目標去創造一個美麗的數字然後會讓周署長
transcript.whisperx[646].start 17064.926
transcript.whisperx[646].end 17079.74
transcript.whisperx[646].text 可以如果在重災重大直在發生的時候那你可以跟立委報告跟全國的民眾報告說我們勞檢了多少的場次是擬定了那個場包含作次的一個量衝很高的一個場次的數據所以
transcript.whisperx[647].start 17083.315
transcript.whisperx[647].end 17110.432
transcript.whisperx[647].text 從這個檢查就是說明年的這個檢查的這個次量我們是不是應該要根據各地檢查人員的這個人數來做一個合理的分配而不是你周子蓮坐在辦公室裡訂一個盲目的這個數據讓大家無止盡的在這邊追求一直在追求一直在增加去達到你訂的KPI嘛因為你訂了KPI就有問題嘛
transcript.whisperx[648].start 17111.806
transcript.whisperx[648].end 17138.471
transcript.whisperx[648].text 主長怎麼看?謝謝委員提醒我們講質量並重是我們的期待齁那各個機構人力因為就是現在的原流動也是一個很大的困難所以我也提醒跟建議我們會好好來檢討因為我對於你們的統計我是有很大的質疑啦因為呢剛剛講嘛工廠有分大小而且按照署長剛剛的回應你們現在已經不用那個早期的工廠的廠次廠次來做計算了那
transcript.whisperx[649].start 17139.571
transcript.whisperx[649].end 17155.801
transcript.whisperx[649].text 現在呢比較誇張的是你們用相次打一打一個勾好這個檢核表裡面打一個勾就算就算一場哎我看你們自己統計也是這樣子一座一個座就就一座就是一場啊你們是這樣子統計的呢
transcript.whisperx[650].start 17158.325
transcript.whisperx[650].end 17179.076
transcript.whisperx[650].text 你你不知道有這個狀況嗎我就說你不知道說打打那個檢核表打個勾就算一場你知道有這個狀況嗎我們這叫做交叉檢查現在交叉檢查檢查到工地或到社道看做一般檢查如果發現特別危險的東西我們鼓勵大家做那個特別危險的項目做檢查所以我們有這樣子的要求
transcript.whisperx[651].start 17179.976
transcript.whisperx[651].end 17197.813
transcript.whisperx[651].text 對阿所以你們有這樣的要求那計算上就要就是給他算一個場次好大家聽到了原來我們的檢查場次是這樣計算出來好這樣我知道了你們就是也是堅持就是要這樣子算那沒關係那你們下次應該訂個20萬之類的KPI
transcript.whisperx[652].start 17201.82
transcript.whisperx[652].end 17224.634
transcript.whisperx[652].text 可以啊因為因為你一個一個項目你就打個勾嘛包委員不是一個項目我們是鼓勵同仁做更實際的深入的檢查對啊那在你鼓勵的結果結果是怎麼樣在你的這些鼓勵的方式我們產生的結果是什麼重大值按死亡人數標新高啊包委員我們去年比前年略減一點當然我們真的是不滿意我們還在檢討
transcript.whisperx[653].start 17225.675
transcript.whisperx[653].end 17247.571
transcript.whisperx[653].text 最好是要好好檢討因為我們最後就是我現在看一下就是說請教那個檢查品質的問題啦好因為這個很重要我要提完我會加速來那個署長新進檢查員還沒有完成一個月學科訓練跟60次數科的實習他所做的檢查具有法律效益嗎
transcript.whisperx[654].start 17249.076
transcript.whisperx[654].end 17255.309
transcript.whisperx[654].text 有嗎有沒有你先回答我有沒有他如果沒有完成就像一個醫生他沒有完成實習
transcript.whisperx[655].start 17257.54
transcript.whisperx[655].end 17280.423
transcript.whisperx[655].text 然後他可以算是一個合格的醫生嗎?不是你先回答我有沒有法律的效力阿有沒有對所以是沒有的嘛那如果這個不合格的檢察員如果造成人民的權益損失有沒有國家賠償的問題有沒有我想要個案來做討論
transcript.whisperx[656].start 17282.731
transcript.whisperx[656].end 17303.424
transcript.whisperx[656].text 所以討論完可能沒有也可能有是這樣嗎因為他已經不合格了然後他還可以到下個階段一個不合格的檢察員然後去做出了對這個廠家做出了決定做出了處分那這個是有效率的嗎他自己已經是不合格了這還有什麼後續討論的問題
transcript.whisperx[657].start 17305.495
transcript.whisperx[657].end 17330.329
transcript.whisperx[657].text 你的邏輯也是很奇怪捏那所以國家賠償那是人家你們造成的損失啊那如果在這個高度檢查量的要求之下現在有多少檢察員還沒有完成授訊就在檢查了你有沒有掌握報告委員我們都會要求檢察機構的首長跟組長要確定他是有對啦你有要求但你有沒有掌握這些人沒有拿到資格然後就去檢查你有沒有掌握目前沒有
transcript.whisperx[658].start 17331.803
transcript.whisperx[658].end 17357.814
transcript.whisperx[658].text 好那我在這裡呼籲所有的廠家如果你們有遇到不合格的檢察員勞檢員去檢查的時候或者造成你們的損失麻煩跟本席辦公室聯絡來跟我檢舉好不好好那我想這個事業單位如果檢查合格沒有多久就發生職災那檢察員到底有沒有責任
transcript.whisperx[659].start 17359.861
transcript.whisperx[659].end 17375.889
transcript.whisperx[659].text 那是不是檢查合格之後就不會發生職災了這些勞動檢查跟預防職災之間關聯性到底是什麼如果他們不是一個這個正向就是說不是一個絕對正向的關係那你們每年增加這個勞檢的次量的意義在哪裡
transcript.whisperx[660].start 17377.369
transcript.whisperx[660].end 17403.721
transcript.whisperx[660].text 我丟出這些問題給你啦所以我覺得這個就是說我們勞檢的現況角色跟防災的功能我是希望說治安署你們能夠檢查這個解決這個檢查員缺耳日益嚴重的問題那因為這個已經不是一天兩天了也不能說歸咎於說有沒有這個危險佳績然後甩鍋給部長去解決
transcript.whisperx[661].start 17404.821
transcript.whisperx[661].end 17424.415
transcript.whisperx[661].text 那因為缺額那衍生檢查次量合理分配的問題它結果是一個惡性的循環那關鍵可能在說職安署長期迷戀於這個檢查的次量認為越多越好所以如果沒有好的品質事實證明根本就是你對職災預防是沒有效的
transcript.whisperx[662].start 17424.775
transcript.whisperx[662].end 17444.324
transcript.whisperx[662].text 所以我今天特別提出這樣的問題讓署長你們回去好好的檢討好好的質量減少職災的發生減少職災死亡的這個人數才是我們真正關心的事情而不是你去檢查了多少場次然後還要加權計算以上謝謝
transcript.whisperx[663].start 17446.246
transcript.whisperx[663].end 17475.496
transcript.whisperx[663].text 好謝謝呃陳英委員齁本日會議詢答全部結束委員廖偉翔林德福葉元之所提書面質詢列入記錄刊登公報現在做以下決定報告及詢答完畢委員質詢未及答覆或請補充資料者請相關機關於兩週內以書面答覆委員另要求期限者從其所定本日會議到此結束現在休息
transcript.whisperx[664].start 17476.056
transcript.whisperx[664].end 17476.977
transcript.whisperx[664].text 星期四上午9點繼續開會。
transcript.whisperx[665].start 17506.162
transcript.whisperx[665].end 17506.522
transcript.whisperx[665].text 委員會主席