iVOD / 160691

Field Value
IVOD_ID 160691
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/160691
日期 2025-04-25
會議資料.會議代碼 院會-11-3-9
會議資料.會議代碼:str 第11屆第3會期第9次會議
會議資料.屆 11
會議資料.會期 3
會議資料.會次 9
會議資料.種類 院會
會議資料.標題 第11屆第3會期第9次會議
影片種類 Clip
開始時間 2025-04-25T14:31:04+08:00
結束時間 2025-04-25T14:51:02+08:00
影片長度 00:19:58
支援功能[0] ai-transcript
支援功能[1] gazette
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/b161887eae65c392d9a34e4207b197a5fbec180d4fb51a06cf9e1f550594d553f952555c339954dd5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 賴士葆
委員發言時間 14:31:04 - 14:51:02
會議時間 2025-04-25T09:00:00+08:00
會議名稱 第11屆第3會期第9次會議(事由:一、對行政院院長提出施政方針及施政報告繼續質詢。二、4月25日上午9時至10時為國是論壇時間。三、4月29日下午2時15分至2時30分為處理臨時提案時間。)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 7.47284375
transcript.pyannote[0].end 8.19846875
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 8.23221875
transcript.pyannote[1].end 8.85659375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 9.53159375
transcript.pyannote[2].end 9.90284375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 10.35846875
transcript.pyannote[3].end 11.84346875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 12.50159375
transcript.pyannote[4].end 13.71659375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 14.15534375
transcript.pyannote[5].end 16.18034375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 16.95659375
transcript.pyannote[6].end 21.00659375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 21.37784375
transcript.pyannote[7].end 23.77409375
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 24.09471875
transcript.pyannote[8].end 24.73596875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 24.95534375
transcript.pyannote[9].end 25.91721875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 26.30534375
transcript.pyannote[10].end 27.60471875
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 36.81846875
transcript.pyannote[11].end 38.79284375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 39.26534375
transcript.pyannote[12].end 41.30721875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 42.04971875
transcript.pyannote[13].end 44.27721875
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 44.41221875
transcript.pyannote[14].end 45.44159375
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 46.55534375
transcript.pyannote[15].end 47.16284375
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 48.71534375
transcript.pyannote[16].end 50.84159375
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 51.26346875
transcript.pyannote[17].end 51.97221875
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 53.05221875
transcript.pyannote[18].end 54.50346875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 54.72284375
transcript.pyannote[19].end 55.83659375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 56.15721875
transcript.pyannote[20].end 57.70971875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 58.08096875
transcript.pyannote[21].end 60.03846875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 60.67971875
transcript.pyannote[22].end 61.57409375
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 61.06784375
transcript.pyannote[23].end 61.43909375
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 62.31659375
transcript.pyannote[24].end 66.24846875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 66.75471875
transcript.pyannote[25].end 68.22284375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 69.50534375
transcript.pyannote[26].end 69.97784375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 69.97784375
transcript.pyannote[27].end 70.33221875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 70.93971875
transcript.pyannote[28].end 72.28971875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 72.82971875
transcript.pyannote[29].end 75.47909375
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 75.85034375
transcript.pyannote[30].end 77.33534375
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 78.02721875
transcript.pyannote[31].end 79.90034375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 80.45721875
transcript.pyannote[32].end 82.76909375
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 83.22471875
transcript.pyannote[33].end 84.49034375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 85.31721875
transcript.pyannote[34].end 87.67971875
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 88.43909375
transcript.pyannote[35].end 98.54721875
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 99.32346875
transcript.pyannote[36].end 103.57596875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 103.91346875
transcript.pyannote[37].end 105.24659375
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 106.17471875
transcript.pyannote[38].end 107.71034375
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 108.36846875
transcript.pyannote[39].end 110.96721875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 111.37221875
transcript.pyannote[40].end 115.18596875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 115.37159375
transcript.pyannote[41].end 119.42159375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 119.74221875
transcript.pyannote[42].end 121.78409375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 122.34096875
transcript.pyannote[43].end 123.58971875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 123.99471875
transcript.pyannote[44].end 124.55159375
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 124.83846875
transcript.pyannote[45].end 125.53034375
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 126.10409375
transcript.pyannote[46].end 128.71971875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 129.05721875
transcript.pyannote[47].end 131.74034375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 132.31409375
transcript.pyannote[48].end 132.76971875
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 132.90471875
transcript.pyannote[49].end 134.30534375
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 134.44034375
transcript.pyannote[50].end 136.39784375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 137.19096875
transcript.pyannote[51].end 138.57471875
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 139.23284375
transcript.pyannote[52].end 141.59534375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 142.11846875
transcript.pyannote[53].end 143.53596875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 143.80596875
transcript.pyannote[54].end 144.73409375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 145.18971875
transcript.pyannote[55].end 150.87659375
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 151.34909375
transcript.pyannote[56].end 153.34034375
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 152.61471875
transcript.pyannote[57].end 153.25596875
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 153.84659375
transcript.pyannote[58].end 167.36346875
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 167.48159375
transcript.pyannote[59].end 174.75471875
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 174.95721875
transcript.pyannote[60].end 178.46721875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 179.07471875
transcript.pyannote[61].end 179.46284375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 179.96909375
transcript.pyannote[62].end 180.99846875
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 181.62284375
transcript.pyannote[63].end 182.09534375
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 182.39909375
transcript.pyannote[64].end 190.14471875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 190.38096875
transcript.pyannote[65].end 207.94784375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 208.48784375
transcript.pyannote[66].end 212.23409375
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 208.63971875
transcript.pyannote[67].end 209.90534375
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 211.00221875
transcript.pyannote[68].end 215.59221875
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 216.33471875
transcript.pyannote[69].end 218.39346875
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 218.73096875
transcript.pyannote[70].end 219.03471875
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 219.42284375
transcript.pyannote[71].end 220.06409375
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 220.51971875
transcript.pyannote[72].end 221.44784375
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 221.90346875
transcript.pyannote[73].end 224.36721875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 224.97471875
transcript.pyannote[74].end 227.89409375
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 227.20221875
transcript.pyannote[75].end 227.47221875
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 228.01221875
transcript.pyannote[76].end 228.02909375
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 228.02909375
transcript.pyannote[77].end 231.50534375
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 231.57284375
transcript.pyannote[78].end 238.79534375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 231.64034375
transcript.pyannote[79].end 231.75846875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 238.79534375
transcript.pyannote[80].end 239.45346875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 239.45346875
transcript.pyannote[81].end 239.55471875
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 239.55471875
transcript.pyannote[82].end 239.65596875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 239.77409375
transcript.pyannote[83].end 250.13534375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 243.63846875
transcript.pyannote[84].end 243.95909375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 249.91596875
transcript.pyannote[85].end 254.30346875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 253.03784375
transcript.pyannote[86].end 253.10534375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 253.10534375
transcript.pyannote[87].end 253.76346875
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 253.76346875
transcript.pyannote[88].end 253.81409375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 253.81409375
transcript.pyannote[89].end 253.89846875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 254.65784375
transcript.pyannote[90].end 256.42971875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 254.82659375
transcript.pyannote[91].end 254.89409375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 254.89409375
transcript.pyannote[92].end 254.97846875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 254.97846875
transcript.pyannote[93].end 257.54346875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 257.27346875
transcript.pyannote[94].end 259.02846875
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 257.67846875
transcript.pyannote[95].end 259.61909375
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 260.15909375
transcript.pyannote[96].end 260.85096875
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 261.20534375
transcript.pyannote[97].end 262.58909375
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 262.89284375
transcript.pyannote[98].end 265.01909375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 265.47471875
transcript.pyannote[99].end 267.14534375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 267.39846875
transcript.pyannote[100].end 267.65159375
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 267.88784375
transcript.pyannote[101].end 270.16596875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 270.65534375
transcript.pyannote[102].end 273.28784375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 273.45659375
transcript.pyannote[103].end 274.45221875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 275.00909375
transcript.pyannote[104].end 277.65846875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 278.29971875
transcript.pyannote[105].end 282.07971875
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 282.92346875
transcript.pyannote[106].end 284.67846875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 285.18471875
transcript.pyannote[107].end 287.00721875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 287.39534375
transcript.pyannote[108].end 289.50471875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 289.92659375
transcript.pyannote[109].end 292.71096875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 293.70659375
transcript.pyannote[110].end 311.76284375
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 312.18471875
transcript.pyannote[111].end 313.43346875
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 314.37846875
transcript.pyannote[112].end 315.03659375
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 315.13784375
transcript.pyannote[113].end 316.57221875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 317.28096875
transcript.pyannote[114].end 319.49159375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 320.28471875
transcript.pyannote[115].end 321.71909375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 321.87096875
transcript.pyannote[116].end 323.52471875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 324.46971875
transcript.pyannote[117].end 325.93784375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 326.19096875
transcript.pyannote[118].end 328.50284375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 329.04284375
transcript.pyannote[119].end 330.39284375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 331.16909375
transcript.pyannote[120].end 331.60784375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 331.60784375
transcript.pyannote[121].end 331.86096875
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 331.62471875
transcript.pyannote[122].end 331.96221875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 331.96221875
transcript.pyannote[123].end 332.09721875
transcript.pyannote[124].speaker SPEAKER_02
transcript.pyannote[124].start 332.09721875
transcript.pyannote[124].end 333.09284375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 333.09284375
transcript.pyannote[125].end 345.27659375
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 333.37971875
transcript.pyannote[126].end 334.02096875
transcript.pyannote[127].speaker SPEAKER_03
transcript.pyannote[127].start 341.49659375
transcript.pyannote[127].end 342.15471875
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 342.15471875
transcript.pyannote[128].end 342.28971875
transcript.pyannote[129].speaker SPEAKER_03
transcript.pyannote[129].start 342.28971875
transcript.pyannote[129].end 343.20096875
transcript.pyannote[130].speaker SPEAKER_03
transcript.pyannote[130].start 344.38221875
transcript.pyannote[130].end 344.97284375
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 345.44534375
transcript.pyannote[131].end 346.81221875
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 346.15409375
transcript.pyannote[132].end 346.22159375
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 346.22159375
transcript.pyannote[133].end 346.23846875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 346.23846875
transcript.pyannote[134].end 346.44096875
transcript.pyannote[135].speaker SPEAKER_00
transcript.pyannote[135].start 346.44096875
transcript.pyannote[135].end 346.64346875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 347.01471875
transcript.pyannote[136].end 359.04659375
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 350.91284375
transcript.pyannote[137].end 351.21659375
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 351.62159375
transcript.pyannote[138].end 351.72284375
transcript.pyannote[139].speaker SPEAKER_03
transcript.pyannote[139].start 351.72284375
transcript.pyannote[139].end 351.94221875
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 351.94221875
transcript.pyannote[140].end 351.99284375
transcript.pyannote[141].speaker SPEAKER_03
transcript.pyannote[141].start 356.17784375
transcript.pyannote[141].end 356.21159375
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 356.21159375
transcript.pyannote[142].end 357.74721875
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 359.94096875
transcript.pyannote[143].end 364.00784375
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 364.46346875
transcript.pyannote[144].end 366.45471875
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 366.70784375
transcript.pyannote[145].end 368.81721875
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 369.40784375
transcript.pyannote[146].end 371.56784375
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 372.17534375
transcript.pyannote[147].end 373.05284375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 372.81659375
transcript.pyannote[148].end 374.70659375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 374.70659375
transcript.pyannote[149].end 374.72346875
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 375.65159375
transcript.pyannote[150].end 377.64284375
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 377.64284375
transcript.pyannote[151].end 377.71034375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 378.95909375
transcript.pyannote[152].end 380.84909375
transcript.pyannote[153].speaker SPEAKER_03
transcript.pyannote[153].start 381.20346875
transcript.pyannote[153].end 381.22034375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 381.22034375
transcript.pyannote[154].end 381.70971875
transcript.pyannote[155].speaker SPEAKER_03
transcript.pyannote[155].start 381.70971875
transcript.pyannote[155].end 381.72659375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 383.34659375
transcript.pyannote[156].end 383.49846875
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 383.49846875
transcript.pyannote[157].end 383.80221875
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 383.80221875
transcript.pyannote[158].end 383.83596875
transcript.pyannote[159].speaker SPEAKER_03
transcript.pyannote[159].start 383.83596875
transcript.pyannote[159].end 383.92034375
transcript.pyannote[160].speaker SPEAKER_02
transcript.pyannote[160].start 383.92034375
transcript.pyannote[160].end 383.95409375
transcript.pyannote[161].speaker SPEAKER_03
transcript.pyannote[161].start 383.95409375
transcript.pyannote[161].end 383.97096875
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 383.97096875
transcript.pyannote[162].end 384.29159375
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 384.29159375
transcript.pyannote[163].end 394.12971875
transcript.pyannote[164].speaker SPEAKER_02
transcript.pyannote[164].start 384.79784375
transcript.pyannote[164].end 384.96659375
transcript.pyannote[165].speaker SPEAKER_03
transcript.pyannote[165].start 384.96659375
transcript.pyannote[165].end 385.10159375
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 385.10159375
transcript.pyannote[166].end 385.13534375
transcript.pyannote[167].speaker SPEAKER_03
transcript.pyannote[167].start 385.13534375
transcript.pyannote[167].end 385.15221875
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 394.83846875
transcript.pyannote[168].end 404.28846875
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 394.95659375
transcript.pyannote[169].end 395.49659375
transcript.pyannote[170].speaker SPEAKER_03
transcript.pyannote[170].start 395.49659375
transcript.pyannote[170].end 395.78346875
transcript.pyannote[171].speaker SPEAKER_02
transcript.pyannote[171].start 401.53784375
transcript.pyannote[171].end 412.81034375
transcript.pyannote[172].speaker SPEAKER_01
transcript.pyannote[172].start 406.83659375
transcript.pyannote[172].end 407.19096875
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 413.26596875
transcript.pyannote[173].end 418.56471875
transcript.pyannote[174].speaker SPEAKER_01
transcript.pyannote[174].start 417.02909375
transcript.pyannote[174].end 423.52596875
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 420.38721875
transcript.pyannote[175].end 421.41659375
transcript.pyannote[176].speaker SPEAKER_01
transcript.pyannote[176].start 423.55971875
transcript.pyannote[176].end 423.62721875
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 423.62721875
transcript.pyannote[177].end 433.49909375
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 423.77909375
transcript.pyannote[178].end 424.57221875
transcript.pyannote[179].speaker SPEAKER_02
transcript.pyannote[179].start 433.97159375
transcript.pyannote[179].end 435.55784375
transcript.pyannote[180].speaker SPEAKER_02
transcript.pyannote[180].start 435.82784375
transcript.pyannote[180].end 438.89909375
transcript.pyannote[181].speaker SPEAKER_02
transcript.pyannote[181].start 439.50659375
transcript.pyannote[181].end 444.53534375
transcript.pyannote[182].speaker SPEAKER_02
transcript.pyannote[182].start 445.24409375
transcript.pyannote[182].end 445.85159375
transcript.pyannote[183].speaker SPEAKER_02
transcript.pyannote[183].start 445.96971875
transcript.pyannote[183].end 447.48846875
transcript.pyannote[184].speaker SPEAKER_02
transcript.pyannote[184].start 447.80909375
transcript.pyannote[184].end 449.02409375
transcript.pyannote[185].speaker SPEAKER_01
transcript.pyannote[185].start 450.05346875
transcript.pyannote[185].end 450.71159375
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 451.18409375
transcript.pyannote[186].end 456.12846875
transcript.pyannote[187].speaker SPEAKER_02
transcript.pyannote[187].start 456.76971875
transcript.pyannote[187].end 457.24221875
transcript.pyannote[188].speaker SPEAKER_02
transcript.pyannote[188].start 457.36034375
transcript.pyannote[188].end 459.94221875
transcript.pyannote[189].speaker SPEAKER_02
transcript.pyannote[189].start 460.81971875
transcript.pyannote[189].end 461.29221875
transcript.pyannote[190].speaker SPEAKER_02
transcript.pyannote[190].start 461.52846875
transcript.pyannote[190].end 461.89971875
transcript.pyannote[191].speaker SPEAKER_02
transcript.pyannote[191].start 462.23721875
transcript.pyannote[191].end 462.96284375
transcript.pyannote[192].speaker SPEAKER_02
transcript.pyannote[192].start 463.60409375
transcript.pyannote[192].end 465.22409375
transcript.pyannote[193].speaker SPEAKER_02
transcript.pyannote[193].start 465.73034375
transcript.pyannote[193].end 467.90721875
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 468.10971875
transcript.pyannote[194].end 469.52721875
transcript.pyannote[195].speaker SPEAKER_01
transcript.pyannote[195].start 471.58596875
transcript.pyannote[195].end 472.37909375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 472.71659375
transcript.pyannote[196].end 474.35346875
transcript.pyannote[197].speaker SPEAKER_01
transcript.pyannote[197].start 474.69096875
transcript.pyannote[197].end 476.02409375
transcript.pyannote[198].speaker SPEAKER_02
transcript.pyannote[198].start 474.82596875
transcript.pyannote[198].end 475.53471875
transcript.pyannote[199].speaker SPEAKER_02
transcript.pyannote[199].start 476.02409375
transcript.pyannote[199].end 476.29409375
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 476.29409375
transcript.pyannote[200].end 477.03659375
transcript.pyannote[201].speaker SPEAKER_02
transcript.pyannote[201].start 477.03659375
transcript.pyannote[201].end 478.31909375
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 478.31909375
transcript.pyannote[202].end 478.33596875
transcript.pyannote[203].speaker SPEAKER_02
transcript.pyannote[203].start 478.60596875
transcript.pyannote[203].end 489.50721875
transcript.pyannote[204].speaker SPEAKER_01
transcript.pyannote[204].start 488.79846875
transcript.pyannote[204].end 489.96284375
transcript.pyannote[205].speaker SPEAKER_02
transcript.pyannote[205].start 490.11471875
transcript.pyannote[205].end 497.62409375
transcript.pyannote[206].speaker SPEAKER_01
transcript.pyannote[206].start 491.17784375
transcript.pyannote[206].end 491.65034375
transcript.pyannote[207].speaker SPEAKER_01
transcript.pyannote[207].start 491.98784375
transcript.pyannote[207].end 492.42659375
transcript.pyannote[208].speaker SPEAKER_01
transcript.pyannote[208].start 497.94471875
transcript.pyannote[208].end 500.72909375
transcript.pyannote[209].speaker SPEAKER_01
transcript.pyannote[209].start 500.88096875
transcript.pyannote[209].end 509.68971875
transcript.pyannote[210].speaker SPEAKER_03
transcript.pyannote[210].start 503.78346875
transcript.pyannote[210].end 504.72846875
transcript.pyannote[211].speaker SPEAKER_02
transcript.pyannote[211].start 504.72846875
transcript.pyannote[211].end 504.74534375
transcript.pyannote[212].speaker SPEAKER_03
transcript.pyannote[212].start 505.94346875
transcript.pyannote[212].end 506.26409375
transcript.pyannote[213].speaker SPEAKER_02
transcript.pyannote[213].start 506.26409375
transcript.pyannote[213].end 506.31471875
transcript.pyannote[214].speaker SPEAKER_02
transcript.pyannote[214].start 508.40721875
transcript.pyannote[214].end 509.67284375
transcript.pyannote[215].speaker SPEAKER_02
transcript.pyannote[215].start 509.68971875
transcript.pyannote[215].end 509.75721875
transcript.pyannote[216].speaker SPEAKER_01
transcript.pyannote[216].start 509.75721875
transcript.pyannote[216].end 509.77409375
transcript.pyannote[217].speaker SPEAKER_02
transcript.pyannote[217].start 509.77409375
transcript.pyannote[217].end 521.50221875
transcript.pyannote[218].speaker SPEAKER_01
transcript.pyannote[218].start 512.71034375
transcript.pyannote[218].end 512.96346875
transcript.pyannote[219].speaker SPEAKER_01
transcript.pyannote[219].start 514.76909375
transcript.pyannote[219].end 515.42721875
transcript.pyannote[220].speaker SPEAKER_01
transcript.pyannote[220].start 520.97909375
transcript.pyannote[220].end 521.23221875
transcript.pyannote[221].speaker SPEAKER_01
transcript.pyannote[221].start 521.50221875
transcript.pyannote[221].end 522.10971875
transcript.pyannote[222].speaker SPEAKER_02
transcript.pyannote[222].start 522.10971875
transcript.pyannote[222].end 527.99909375
transcript.pyannote[223].speaker SPEAKER_01
transcript.pyannote[223].start 522.32909375
transcript.pyannote[223].end 522.37971875
transcript.pyannote[224].speaker SPEAKER_02
transcript.pyannote[224].start 528.38721875
transcript.pyannote[224].end 530.19284375
transcript.pyannote[225].speaker SPEAKER_02
transcript.pyannote[225].start 530.54721875
transcript.pyannote[225].end 531.42471875
transcript.pyannote[226].speaker SPEAKER_02
transcript.pyannote[226].start 531.86346875
transcript.pyannote[226].end 532.55534375
transcript.pyannote[227].speaker SPEAKER_02
transcript.pyannote[227].start 532.92659375
transcript.pyannote[227].end 536.72346875
transcript.pyannote[228].speaker SPEAKER_02
transcript.pyannote[228].start 537.73596875
transcript.pyannote[228].end 538.41096875
transcript.pyannote[229].speaker SPEAKER_01
transcript.pyannote[229].start 538.05659375
transcript.pyannote[229].end 538.29284375
transcript.pyannote[230].speaker SPEAKER_01
transcript.pyannote[230].start 538.41096875
transcript.pyannote[230].end 538.44471875
transcript.pyannote[231].speaker SPEAKER_01
transcript.pyannote[231].start 538.93409375
transcript.pyannote[231].end 543.25409375
transcript.pyannote[232].speaker SPEAKER_02
transcript.pyannote[232].start 542.03909375
transcript.pyannote[232].end 546.98346875
transcript.pyannote[233].speaker SPEAKER_01
transcript.pyannote[233].start 547.57409375
transcript.pyannote[233].end 548.72159375
transcript.pyannote[234].speaker SPEAKER_02
transcript.pyannote[234].start 548.31659375
transcript.pyannote[234].end 551.79284375
transcript.pyannote[235].speaker SPEAKER_02
transcript.pyannote[235].start 552.01221875
transcript.pyannote[235].end 554.40846875
transcript.pyannote[236].speaker SPEAKER_02
transcript.pyannote[236].start 554.62784375
transcript.pyannote[236].end 556.09596875
transcript.pyannote[237].speaker SPEAKER_02
transcript.pyannote[237].start 556.29846875
transcript.pyannote[237].end 558.98159375
transcript.pyannote[238].speaker SPEAKER_02
transcript.pyannote[238].start 559.18409375
transcript.pyannote[238].end 559.72409375
transcript.pyannote[239].speaker SPEAKER_02
transcript.pyannote[239].start 560.28096875
transcript.pyannote[239].end 561.29346875
transcript.pyannote[240].speaker SPEAKER_02
transcript.pyannote[240].start 562.05284375
transcript.pyannote[240].end 563.21721875
transcript.pyannote[241].speaker SPEAKER_02
transcript.pyannote[241].start 563.36909375
transcript.pyannote[241].end 564.90471875
transcript.pyannote[242].speaker SPEAKER_02
transcript.pyannote[242].start 565.51221875
transcript.pyannote[242].end 566.79471875
transcript.pyannote[243].speaker SPEAKER_02
transcript.pyannote[243].start 566.98034375
transcript.pyannote[243].end 568.93784375
transcript.pyannote[244].speaker SPEAKER_02
transcript.pyannote[244].start 569.03909375
transcript.pyannote[244].end 569.56221875
transcript.pyannote[245].speaker SPEAKER_02
transcript.pyannote[245].start 569.88284375
transcript.pyannote[245].end 572.29596875
transcript.pyannote[246].speaker SPEAKER_02
transcript.pyannote[246].start 573.05534375
transcript.pyannote[246].end 573.59534375
transcript.pyannote[247].speaker SPEAKER_02
transcript.pyannote[247].start 574.03409375
transcript.pyannote[247].end 581.72909375
transcript.pyannote[248].speaker SPEAKER_01
transcript.pyannote[248].start 582.64034375
transcript.pyannote[248].end 585.01971875
transcript.pyannote[249].speaker SPEAKER_02
transcript.pyannote[249].start 585.01971875
transcript.pyannote[249].end 592.10721875
transcript.pyannote[250].speaker SPEAKER_01
transcript.pyannote[250].start 592.37721875
transcript.pyannote[250].end 593.08596875
transcript.pyannote[251].speaker SPEAKER_02
transcript.pyannote[251].start 593.82846875
transcript.pyannote[251].end 595.54971875
transcript.pyannote[252].speaker SPEAKER_02
transcript.pyannote[252].start 596.91659375
transcript.pyannote[252].end 597.38909375
transcript.pyannote[253].speaker SPEAKER_02
transcript.pyannote[253].start 597.59159375
transcript.pyannote[253].end 598.65471875
transcript.pyannote[254].speaker SPEAKER_02
transcript.pyannote[254].start 598.92471875
transcript.pyannote[254].end 600.78096875
transcript.pyannote[255].speaker SPEAKER_02
transcript.pyannote[255].start 601.43909375
transcript.pyannote[255].end 603.71721875
transcript.pyannote[256].speaker SPEAKER_02
transcript.pyannote[256].start 604.07159375
transcript.pyannote[256].end 608.96534375
transcript.pyannote[257].speaker SPEAKER_01
transcript.pyannote[257].start 609.15096875
transcript.pyannote[257].end 611.10846875
transcript.pyannote[258].speaker SPEAKER_02
transcript.pyannote[258].start 609.50534375
transcript.pyannote[258].end 611.02409375
transcript.pyannote[259].speaker SPEAKER_03
transcript.pyannote[259].start 611.02409375
transcript.pyannote[259].end 611.04096875
transcript.pyannote[260].speaker SPEAKER_03
transcript.pyannote[260].start 611.10846875
transcript.pyannote[260].end 611.58096875
transcript.pyannote[261].speaker SPEAKER_01
transcript.pyannote[261].start 611.58096875
transcript.pyannote[261].end 612.44159375
transcript.pyannote[262].speaker SPEAKER_03
transcript.pyannote[262].start 611.59784375
transcript.pyannote[262].end 611.81721875
transcript.pyannote[263].speaker SPEAKER_02
transcript.pyannote[263].start 611.81721875
transcript.pyannote[263].end 611.96909375
transcript.pyannote[264].speaker SPEAKER_03
transcript.pyannote[264].start 611.96909375
transcript.pyannote[264].end 612.03659375
transcript.pyannote[265].speaker SPEAKER_02
transcript.pyannote[265].start 612.03659375
transcript.pyannote[265].end 612.35721875
transcript.pyannote[266].speaker SPEAKER_03
transcript.pyannote[266].start 612.35721875
transcript.pyannote[266].end 612.40784375
transcript.pyannote[267].speaker SPEAKER_03
transcript.pyannote[267].start 612.44159375
transcript.pyannote[267].end 613.58909375
transcript.pyannote[268].speaker SPEAKER_03
transcript.pyannote[268].start 613.96034375
transcript.pyannote[268].end 614.77034375
transcript.pyannote[269].speaker SPEAKER_02
transcript.pyannote[269].start 614.77034375
transcript.pyannote[269].end 614.97284375
transcript.pyannote[270].speaker SPEAKER_01
transcript.pyannote[270].start 614.77034375
transcript.pyannote[270].end 618.60096875
transcript.pyannote[271].speaker SPEAKER_03
transcript.pyannote[271].start 614.97284375
transcript.pyannote[271].end 615.17534375
transcript.pyannote[272].speaker SPEAKER_02
transcript.pyannote[272].start 615.17534375
transcript.pyannote[272].end 615.19221875
transcript.pyannote[273].speaker SPEAKER_02
transcript.pyannote[273].start 618.87096875
transcript.pyannote[273].end 622.56659375
transcript.pyannote[274].speaker SPEAKER_02
transcript.pyannote[274].start 622.93784375
transcript.pyannote[274].end 625.30034375
transcript.pyannote[275].speaker SPEAKER_02
transcript.pyannote[275].start 625.89096875
transcript.pyannote[275].end 631.44284375
transcript.pyannote[276].speaker SPEAKER_02
transcript.pyannote[276].start 631.76346875
transcript.pyannote[276].end 635.03721875
transcript.pyannote[277].speaker SPEAKER_02
transcript.pyannote[277].start 635.50971875
transcript.pyannote[277].end 636.57284375
transcript.pyannote[278].speaker SPEAKER_02
transcript.pyannote[278].start 637.26471875
transcript.pyannote[278].end 637.87221875
transcript.pyannote[279].speaker SPEAKER_02
transcript.pyannote[279].start 638.49659375
transcript.pyannote[279].end 639.37409375
transcript.pyannote[280].speaker SPEAKER_02
transcript.pyannote[280].start 639.74534375
transcript.pyannote[280].end 641.73659375
transcript.pyannote[281].speaker SPEAKER_02
transcript.pyannote[281].start 642.04034375
transcript.pyannote[281].end 643.40721875
transcript.pyannote[282].speaker SPEAKER_02
transcript.pyannote[282].start 643.54221875
transcript.pyannote[282].end 645.93846875
transcript.pyannote[283].speaker SPEAKER_02
transcript.pyannote[283].start 646.00596875
transcript.pyannote[283].end 648.25034375
transcript.pyannote[284].speaker SPEAKER_02
transcript.pyannote[284].start 648.99284375
transcript.pyannote[284].end 661.69971875
transcript.pyannote[285].speaker SPEAKER_02
transcript.pyannote[285].start 662.25659375
transcript.pyannote[285].end 665.71596875
transcript.pyannote[286].speaker SPEAKER_02
transcript.pyannote[286].start 666.82971875
transcript.pyannote[286].end 667.72409375
transcript.pyannote[287].speaker SPEAKER_02
transcript.pyannote[287].start 668.38221875
transcript.pyannote[287].end 669.42846875
transcript.pyannote[288].speaker SPEAKER_02
transcript.pyannote[288].start 669.88409375
transcript.pyannote[288].end 672.66846875
transcript.pyannote[289].speaker SPEAKER_02
transcript.pyannote[289].start 673.37721875
transcript.pyannote[289].end 674.13659375
transcript.pyannote[290].speaker SPEAKER_02
transcript.pyannote[290].start 674.79471875
transcript.pyannote[290].end 678.77721875
transcript.pyannote[291].speaker SPEAKER_02
transcript.pyannote[291].start 679.45221875
transcript.pyannote[291].end 682.23659375
transcript.pyannote[292].speaker SPEAKER_02
transcript.pyannote[292].start 682.69221875
transcript.pyannote[292].end 684.37971875
transcript.pyannote[293].speaker SPEAKER_02
transcript.pyannote[293].start 684.64971875
transcript.pyannote[293].end 685.47659375
transcript.pyannote[294].speaker SPEAKER_02
transcript.pyannote[294].start 685.67909375
transcript.pyannote[294].end 687.19784375
transcript.pyannote[295].speaker SPEAKER_02
transcript.pyannote[295].start 687.87284375
transcript.pyannote[295].end 691.38284375
transcript.pyannote[296].speaker SPEAKER_02
transcript.pyannote[296].start 692.22659375
transcript.pyannote[296].end 698.95971875
transcript.pyannote[297].speaker SPEAKER_02
transcript.pyannote[297].start 699.58409375
transcript.pyannote[297].end 700.41096875
transcript.pyannote[298].speaker SPEAKER_02
transcript.pyannote[298].start 700.57971875
transcript.pyannote[298].end 703.90409375
transcript.pyannote[299].speaker SPEAKER_02
transcript.pyannote[299].start 704.39346875
transcript.pyannote[299].end 705.47346875
transcript.pyannote[300].speaker SPEAKER_02
transcript.pyannote[300].start 706.46909375
transcript.pyannote[300].end 709.03409375
transcript.pyannote[301].speaker SPEAKER_02
transcript.pyannote[301].start 709.18596875
transcript.pyannote[301].end 710.82284375
transcript.pyannote[302].speaker SPEAKER_02
transcript.pyannote[302].start 711.41346875
transcript.pyannote[302].end 712.81409375
transcript.pyannote[303].speaker SPEAKER_01
transcript.pyannote[303].start 713.37096875
transcript.pyannote[303].end 717.45471875
transcript.pyannote[304].speaker SPEAKER_02
transcript.pyannote[304].start 713.45534375
transcript.pyannote[304].end 713.89409375
transcript.pyannote[305].speaker SPEAKER_02
transcript.pyannote[305].start 715.48034375
transcript.pyannote[305].end 715.76721875
transcript.pyannote[306].speaker SPEAKER_01
transcript.pyannote[306].start 718.09596875
transcript.pyannote[306].end 722.41596875
transcript.pyannote[307].speaker SPEAKER_02
transcript.pyannote[307].start 722.82096875
transcript.pyannote[307].end 724.72784375
transcript.pyannote[308].speaker SPEAKER_01
transcript.pyannote[308].start 723.02346875
transcript.pyannote[308].end 723.61409375
transcript.pyannote[309].speaker SPEAKER_02
transcript.pyannote[309].start 725.35221875
transcript.pyannote[309].end 730.98846875
transcript.pyannote[310].speaker SPEAKER_02
transcript.pyannote[310].start 732.16971875
transcript.pyannote[310].end 733.30034375
transcript.pyannote[311].speaker SPEAKER_01
transcript.pyannote[311].start 732.47346875
transcript.pyannote[311].end 732.69284375
transcript.pyannote[312].speaker SPEAKER_02
transcript.pyannote[312].start 733.55346875
transcript.pyannote[312].end 735.51096875
transcript.pyannote[313].speaker SPEAKER_01
transcript.pyannote[313].start 735.51096875
transcript.pyannote[313].end 735.56159375
transcript.pyannote[314].speaker SPEAKER_02
transcript.pyannote[314].start 735.71346875
transcript.pyannote[314].end 736.03409375
transcript.pyannote[315].speaker SPEAKER_01
transcript.pyannote[315].start 736.03409375
transcript.pyannote[315].end 741.07971875
transcript.pyannote[316].speaker SPEAKER_01
transcript.pyannote[316].start 741.21471875
transcript.pyannote[316].end 746.10846875
transcript.pyannote[317].speaker SPEAKER_02
transcript.pyannote[317].start 746.22659375
transcript.pyannote[317].end 748.94346875
transcript.pyannote[318].speaker SPEAKER_02
transcript.pyannote[318].start 749.51721875
transcript.pyannote[318].end 751.05284375
transcript.pyannote[319].speaker SPEAKER_02
transcript.pyannote[319].start 751.33971875
transcript.pyannote[319].end 753.43221875
transcript.pyannote[320].speaker SPEAKER_02
transcript.pyannote[320].start 753.85409375
transcript.pyannote[320].end 754.95096875
transcript.pyannote[321].speaker SPEAKER_02
transcript.pyannote[321].start 755.33909375
transcript.pyannote[321].end 755.98034375
transcript.pyannote[322].speaker SPEAKER_02
transcript.pyannote[322].start 756.26721875
transcript.pyannote[322].end 759.01784375
transcript.pyannote[323].speaker SPEAKER_02
transcript.pyannote[323].start 760.03034375
transcript.pyannote[323].end 767.75909375
transcript.pyannote[324].speaker SPEAKER_02
transcript.pyannote[324].start 768.34971875
transcript.pyannote[324].end 770.10471875
transcript.pyannote[325].speaker SPEAKER_01
transcript.pyannote[325].start 770.59409375
transcript.pyannote[325].end 781.83284375
transcript.pyannote[326].speaker SPEAKER_02
transcript.pyannote[326].start 776.80409375
transcript.pyannote[326].end 777.68159375
transcript.pyannote[327].speaker SPEAKER_02
transcript.pyannote[327].start 778.06971875
transcript.pyannote[327].end 778.59284375
transcript.pyannote[328].speaker SPEAKER_02
transcript.pyannote[328].start 781.10721875
transcript.pyannote[328].end 783.90846875
transcript.pyannote[329].speaker SPEAKER_01
transcript.pyannote[329].start 782.13659375
transcript.pyannote[329].end 782.17034375
transcript.pyannote[330].speaker SPEAKER_01
transcript.pyannote[330].start 782.18721875
transcript.pyannote[330].end 782.23784375
transcript.pyannote[331].speaker SPEAKER_02
transcript.pyannote[331].start 784.73534375
transcript.pyannote[331].end 787.26659375
transcript.pyannote[332].speaker SPEAKER_02
transcript.pyannote[332].start 787.57034375
transcript.pyannote[332].end 788.39721875
transcript.pyannote[333].speaker SPEAKER_02
transcript.pyannote[333].start 788.78534375
transcript.pyannote[333].end 789.51096875
transcript.pyannote[334].speaker SPEAKER_02
transcript.pyannote[334].start 789.89909375
transcript.pyannote[334].end 790.62471875
transcript.pyannote[335].speaker SPEAKER_02
transcript.pyannote[335].start 791.16471875
transcript.pyannote[335].end 794.15159375
transcript.pyannote[336].speaker SPEAKER_02
transcript.pyannote[336].start 794.40471875
transcript.pyannote[336].end 798.60659375
transcript.pyannote[337].speaker SPEAKER_02
transcript.pyannote[337].start 798.96096875
transcript.pyannote[337].end 799.90596875
transcript.pyannote[338].speaker SPEAKER_02
transcript.pyannote[338].start 800.64846875
transcript.pyannote[338].end 802.45409375
transcript.pyannote[339].speaker SPEAKER_02
transcript.pyannote[339].start 803.19659375
transcript.pyannote[339].end 805.03596875
transcript.pyannote[340].speaker SPEAKER_02
transcript.pyannote[340].start 805.60971875
transcript.pyannote[340].end 808.63034375
transcript.pyannote[341].speaker SPEAKER_02
transcript.pyannote[341].start 809.98034375
transcript.pyannote[341].end 810.38534375
transcript.pyannote[342].speaker SPEAKER_02
transcript.pyannote[342].start 811.16159375
transcript.pyannote[342].end 811.85346875
transcript.pyannote[343].speaker SPEAKER_02
transcript.pyannote[343].start 812.73096875
transcript.pyannote[343].end 815.48159375
transcript.pyannote[344].speaker SPEAKER_02
transcript.pyannote[344].start 815.88659375
transcript.pyannote[344].end 817.97909375
transcript.pyannote[345].speaker SPEAKER_02
transcript.pyannote[345].start 818.50221875
transcript.pyannote[345].end 819.51471875
transcript.pyannote[346].speaker SPEAKER_02
transcript.pyannote[346].start 820.57784375
transcript.pyannote[346].end 821.10096875
transcript.pyannote[347].speaker SPEAKER_02
transcript.pyannote[347].start 821.57346875
transcript.pyannote[347].end 822.58596875
transcript.pyannote[348].speaker SPEAKER_02
transcript.pyannote[348].start 826.04534375
transcript.pyannote[348].end 828.01971875
transcript.pyannote[349].speaker SPEAKER_02
transcript.pyannote[349].start 828.23909375
transcript.pyannote[349].end 829.40346875
transcript.pyannote[350].speaker SPEAKER_02
transcript.pyannote[350].start 830.09534375
transcript.pyannote[350].end 832.52534375
transcript.pyannote[351].speaker SPEAKER_02
transcript.pyannote[351].start 833.40284375
transcript.pyannote[351].end 836.06909375
transcript.pyannote[352].speaker SPEAKER_02
transcript.pyannote[352].start 836.89596875
transcript.pyannote[352].end 838.81971875
transcript.pyannote[353].speaker SPEAKER_02
transcript.pyannote[353].start 839.93346875
transcript.pyannote[353].end 842.80221875
transcript.pyannote[354].speaker SPEAKER_02
transcript.pyannote[354].start 843.30846875
transcript.pyannote[354].end 845.65409375
transcript.pyannote[355].speaker SPEAKER_02
transcript.pyannote[355].start 846.07596875
transcript.pyannote[355].end 846.68346875
transcript.pyannote[356].speaker SPEAKER_02
transcript.pyannote[356].start 847.34159375
transcript.pyannote[356].end 849.67034375
transcript.pyannote[357].speaker SPEAKER_02
transcript.pyannote[357].start 850.17659375
transcript.pyannote[357].end 852.43784375
transcript.pyannote[358].speaker SPEAKER_02
transcript.pyannote[358].start 852.64034375
transcript.pyannote[358].end 853.26471875
transcript.pyannote[359].speaker SPEAKER_02
transcript.pyannote[359].start 853.73721875
transcript.pyannote[359].end 855.49221875
transcript.pyannote[360].speaker SPEAKER_02
transcript.pyannote[360].start 856.57221875
transcript.pyannote[360].end 857.83784375
transcript.pyannote[361].speaker SPEAKER_02
transcript.pyannote[361].start 858.76596875
transcript.pyannote[361].end 859.08659375
transcript.pyannote[362].speaker SPEAKER_02
transcript.pyannote[362].start 859.42409375
transcript.pyannote[362].end 860.23409375
transcript.pyannote[363].speaker SPEAKER_02
transcript.pyannote[363].start 860.75721875
transcript.pyannote[363].end 862.42784375
transcript.pyannote[364].speaker SPEAKER_02
transcript.pyannote[364].start 863.47409375
transcript.pyannote[364].end 864.50346875
transcript.pyannote[365].speaker SPEAKER_02
transcript.pyannote[365].start 865.46534375
transcript.pyannote[365].end 865.87034375
transcript.pyannote[366].speaker SPEAKER_02
transcript.pyannote[366].start 866.66346875
transcript.pyannote[366].end 867.16971875
transcript.pyannote[367].speaker SPEAKER_02
transcript.pyannote[367].start 867.40596875
transcript.pyannote[367].end 868.95846875
transcript.pyannote[368].speaker SPEAKER_02
transcript.pyannote[368].start 869.11034375
transcript.pyannote[368].end 870.17346875
transcript.pyannote[369].speaker SPEAKER_02
transcript.pyannote[369].start 870.49409375
transcript.pyannote[369].end 872.18159375
transcript.pyannote[370].speaker SPEAKER_02
transcript.pyannote[370].start 873.04221875
transcript.pyannote[370].end 873.53159375
transcript.pyannote[371].speaker SPEAKER_02
transcript.pyannote[371].start 874.22346875
transcript.pyannote[371].end 876.18096875
transcript.pyannote[372].speaker SPEAKER_02
transcript.pyannote[372].start 877.31159375
transcript.pyannote[372].end 877.96971875
transcript.pyannote[373].speaker SPEAKER_02
transcript.pyannote[373].start 879.01596875
transcript.pyannote[373].end 880.50096875
transcript.pyannote[374].speaker SPEAKER_02
transcript.pyannote[374].start 880.63596875
transcript.pyannote[374].end 882.05346875
transcript.pyannote[375].speaker SPEAKER_02
transcript.pyannote[375].start 882.13784375
transcript.pyannote[375].end 882.86346875
transcript.pyannote[376].speaker SPEAKER_02
transcript.pyannote[376].start 883.40346875
transcript.pyannote[376].end 884.56784375
transcript.pyannote[377].speaker SPEAKER_02
transcript.pyannote[377].start 885.02346875
transcript.pyannote[377].end 885.96846875
transcript.pyannote[378].speaker SPEAKER_01
transcript.pyannote[378].start 885.96846875
transcript.pyannote[378].end 886.00221875
transcript.pyannote[379].speaker SPEAKER_01
transcript.pyannote[379].start 886.33971875
transcript.pyannote[379].end 890.08596875
transcript.pyannote[380].speaker SPEAKER_01
transcript.pyannote[380].start 890.40659375
transcript.pyannote[380].end 894.06846875
transcript.pyannote[381].speaker SPEAKER_02
transcript.pyannote[381].start 893.69721875
transcript.pyannote[381].end 893.96721875
transcript.pyannote[382].speaker SPEAKER_02
transcript.pyannote[382].start 894.06846875
transcript.pyannote[382].end 895.08096875
transcript.pyannote[383].speaker SPEAKER_02
transcript.pyannote[383].start 895.19909375
transcript.pyannote[383].end 905.62784375
transcript.pyannote[384].speaker SPEAKER_02
transcript.pyannote[384].start 906.04971875
transcript.pyannote[384].end 914.77409375
transcript.pyannote[385].speaker SPEAKER_02
transcript.pyannote[385].start 915.19596875
transcript.pyannote[385].end 917.35596875
transcript.pyannote[386].speaker SPEAKER_02
transcript.pyannote[386].start 917.54159375
transcript.pyannote[386].end 920.91659375
transcript.pyannote[387].speaker SPEAKER_02
transcript.pyannote[387].start 921.52409375
transcript.pyannote[387].end 923.26221875
transcript.pyannote[388].speaker SPEAKER_02
transcript.pyannote[388].start 924.08909375
transcript.pyannote[388].end 930.23159375
transcript.pyannote[389].speaker SPEAKER_02
transcript.pyannote[389].start 930.90659375
transcript.pyannote[389].end 936.96471875
transcript.pyannote[390].speaker SPEAKER_01
transcript.pyannote[390].start 936.96471875
transcript.pyannote[390].end 938.36534375
transcript.pyannote[391].speaker SPEAKER_01
transcript.pyannote[391].start 938.65221875
transcript.pyannote[391].end 941.85846875
transcript.pyannote[392].speaker SPEAKER_01
transcript.pyannote[392].start 942.26346875
transcript.pyannote[392].end 951.73034375
transcript.pyannote[393].speaker SPEAKER_02
transcript.pyannote[393].start 949.43534375
transcript.pyannote[393].end 949.95846875
transcript.pyannote[394].speaker SPEAKER_02
transcript.pyannote[394].start 950.90346875
transcript.pyannote[394].end 951.81471875
transcript.pyannote[395].speaker SPEAKER_01
transcript.pyannote[395].start 951.81471875
transcript.pyannote[395].end 951.91596875
transcript.pyannote[396].speaker SPEAKER_01
transcript.pyannote[396].start 952.25346875
transcript.pyannote[396].end 952.28721875
transcript.pyannote[397].speaker SPEAKER_03
transcript.pyannote[397].start 952.28721875
transcript.pyannote[397].end 952.48971875
transcript.pyannote[398].speaker SPEAKER_02
transcript.pyannote[398].start 952.48971875
transcript.pyannote[398].end 952.55721875
transcript.pyannote[399].speaker SPEAKER_03
transcript.pyannote[399].start 952.55721875
transcript.pyannote[399].end 952.86096875
transcript.pyannote[400].speaker SPEAKER_02
transcript.pyannote[400].start 952.86096875
transcript.pyannote[400].end 952.96221875
transcript.pyannote[401].speaker SPEAKER_03
transcript.pyannote[401].start 952.96221875
transcript.pyannote[401].end 953.02971875
transcript.pyannote[402].speaker SPEAKER_02
transcript.pyannote[402].start 953.02971875
transcript.pyannote[402].end 953.09721875
transcript.pyannote[403].speaker SPEAKER_03
transcript.pyannote[403].start 953.09721875
transcript.pyannote[403].end 954.02534375
transcript.pyannote[404].speaker SPEAKER_02
transcript.pyannote[404].start 954.02534375
transcript.pyannote[404].end 954.97034375
transcript.pyannote[405].speaker SPEAKER_03
transcript.pyannote[405].start 954.97034375
transcript.pyannote[405].end 954.98721875
transcript.pyannote[406].speaker SPEAKER_02
transcript.pyannote[406].start 955.51034375
transcript.pyannote[406].end 956.23596875
transcript.pyannote[407].speaker SPEAKER_03
transcript.pyannote[407].start 956.42159375
transcript.pyannote[407].end 956.45534375
transcript.pyannote[408].speaker SPEAKER_02
transcript.pyannote[408].start 956.45534375
transcript.pyannote[408].end 957.61971875
transcript.pyannote[409].speaker SPEAKER_02
transcript.pyannote[409].start 958.14284375
transcript.pyannote[409].end 961.72034375
transcript.pyannote[410].speaker SPEAKER_02
transcript.pyannote[410].start 962.22659375
transcript.pyannote[410].end 966.93471875
transcript.pyannote[411].speaker SPEAKER_02
transcript.pyannote[411].start 967.66034375
transcript.pyannote[411].end 970.79909375
transcript.pyannote[412].speaker SPEAKER_02
transcript.pyannote[412].start 971.77784375
transcript.pyannote[412].end 972.58784375
transcript.pyannote[413].speaker SPEAKER_02
transcript.pyannote[413].start 973.54971875
transcript.pyannote[413].end 974.49471875
transcript.pyannote[414].speaker SPEAKER_02
transcript.pyannote[414].start 975.45659375
transcript.pyannote[414].end 976.26659375
transcript.pyannote[415].speaker SPEAKER_02
transcript.pyannote[415].start 976.48596875
transcript.pyannote[415].end 977.04284375
transcript.pyannote[416].speaker SPEAKER_02
transcript.pyannote[416].start 977.27909375
transcript.pyannote[416].end 978.93284375
transcript.pyannote[417].speaker SPEAKER_02
transcript.pyannote[417].start 979.75971875
transcript.pyannote[417].end 980.11409375
transcript.pyannote[418].speaker SPEAKER_02
transcript.pyannote[418].start 980.26596875
transcript.pyannote[418].end 983.50596875
transcript.pyannote[419].speaker SPEAKER_02
transcript.pyannote[419].start 983.75909375
transcript.pyannote[419].end 985.27784375
transcript.pyannote[420].speaker SPEAKER_02
transcript.pyannote[420].start 986.74596875
transcript.pyannote[420].end 990.44159375
transcript.pyannote[421].speaker SPEAKER_02
transcript.pyannote[421].start 990.94784375
transcript.pyannote[421].end 992.90534375
transcript.pyannote[422].speaker SPEAKER_02
transcript.pyannote[422].start 994.06971875
transcript.pyannote[422].end 997.29284375
transcript.pyannote[423].speaker SPEAKER_02
transcript.pyannote[423].start 998.05221875
transcript.pyannote[423].end 1001.32596875
transcript.pyannote[424].speaker SPEAKER_02
transcript.pyannote[424].start 1002.43971875
transcript.pyannote[424].end 1003.82346875
transcript.pyannote[425].speaker SPEAKER_02
transcript.pyannote[425].start 1004.36346875
transcript.pyannote[425].end 1005.74721875
transcript.pyannote[426].speaker SPEAKER_02
transcript.pyannote[426].start 1005.91596875
transcript.pyannote[426].end 1008.91971875
transcript.pyannote[427].speaker SPEAKER_02
transcript.pyannote[427].start 1009.30784375
transcript.pyannote[427].end 1011.19784375
transcript.pyannote[428].speaker SPEAKER_02
transcript.pyannote[428].start 1012.32846875
transcript.pyannote[428].end 1015.93971875
transcript.pyannote[429].speaker SPEAKER_01
transcript.pyannote[429].start 1014.10034375
transcript.pyannote[429].end 1031.46471875
transcript.pyannote[430].speaker SPEAKER_03
transcript.pyannote[430].start 1015.93971875
transcript.pyannote[430].end 1018.97721875
transcript.pyannote[431].speaker SPEAKER_02
transcript.pyannote[431].start 1018.97721875
transcript.pyannote[431].end 1019.11221875
transcript.pyannote[432].speaker SPEAKER_03
transcript.pyannote[432].start 1019.11221875
transcript.pyannote[432].end 1019.63534375
transcript.pyannote[433].speaker SPEAKER_02
transcript.pyannote[433].start 1027.48221875
transcript.pyannote[433].end 1027.53284375
transcript.pyannote[434].speaker SPEAKER_02
transcript.pyannote[434].start 1027.80284375
transcript.pyannote[434].end 1028.61284375
transcript.pyannote[435].speaker SPEAKER_02
transcript.pyannote[435].start 1030.09784375
transcript.pyannote[435].end 1030.19909375
transcript.pyannote[436].speaker SPEAKER_02
transcript.pyannote[436].start 1030.36784375
transcript.pyannote[436].end 1030.62096875
transcript.pyannote[437].speaker SPEAKER_02
transcript.pyannote[437].start 1030.67159375
transcript.pyannote[437].end 1030.90784375
transcript.pyannote[438].speaker SPEAKER_02
transcript.pyannote[438].start 1031.46471875
transcript.pyannote[438].end 1031.49846875
transcript.pyannote[439].speaker SPEAKER_01
transcript.pyannote[439].start 1031.49846875
transcript.pyannote[439].end 1031.53221875
transcript.pyannote[440].speaker SPEAKER_02
transcript.pyannote[440].start 1031.81909375
transcript.pyannote[440].end 1033.99596875
transcript.pyannote[441].speaker SPEAKER_02
transcript.pyannote[441].start 1034.41784375
transcript.pyannote[441].end 1039.21034375
transcript.pyannote[442].speaker SPEAKER_02
transcript.pyannote[442].start 1039.96971875
transcript.pyannote[442].end 1041.64034375
transcript.pyannote[443].speaker SPEAKER_02
transcript.pyannote[443].start 1042.04534375
transcript.pyannote[443].end 1042.85534375
transcript.pyannote[444].speaker SPEAKER_02
transcript.pyannote[444].start 1043.41221875
transcript.pyannote[444].end 1044.98159375
transcript.pyannote[445].speaker SPEAKER_02
transcript.pyannote[445].start 1045.04909375
transcript.pyannote[445].end 1046.51721875
transcript.pyannote[446].speaker SPEAKER_02
transcript.pyannote[446].start 1046.78721875
transcript.pyannote[446].end 1048.96409375
transcript.pyannote[447].speaker SPEAKER_02
transcript.pyannote[447].start 1049.03159375
transcript.pyannote[447].end 1049.06534375
transcript.pyannote[448].speaker SPEAKER_02
transcript.pyannote[448].start 1049.08221875
transcript.pyannote[448].end 1050.09471875
transcript.pyannote[449].speaker SPEAKER_02
transcript.pyannote[449].start 1050.22971875
transcript.pyannote[449].end 1052.47409375
transcript.pyannote[450].speaker SPEAKER_02
transcript.pyannote[450].start 1052.99721875
transcript.pyannote[450].end 1057.16534375
transcript.pyannote[451].speaker SPEAKER_01
transcript.pyannote[451].start 1056.15284375
transcript.pyannote[451].end 1060.99596875
transcript.pyannote[452].speaker SPEAKER_03
transcript.pyannote[452].start 1057.16534375
transcript.pyannote[452].end 1057.21596875
transcript.pyannote[453].speaker SPEAKER_02
transcript.pyannote[453].start 1057.21596875
transcript.pyannote[453].end 1057.35096875
transcript.pyannote[454].speaker SPEAKER_03
transcript.pyannote[454].start 1057.35096875
transcript.pyannote[454].end 1058.11034375
transcript.pyannote[455].speaker SPEAKER_03
transcript.pyannote[455].start 1060.99596875
transcript.pyannote[455].end 1069.19721875
transcript.pyannote[456].speaker SPEAKER_03
transcript.pyannote[456].start 1070.07471875
transcript.pyannote[456].end 1071.00284375
transcript.pyannote[457].speaker SPEAKER_03
transcript.pyannote[457].start 1071.61034375
transcript.pyannote[457].end 1073.09534375
transcript.pyannote[458].speaker SPEAKER_03
transcript.pyannote[458].start 1073.95596875
transcript.pyannote[458].end 1075.35659375
transcript.pyannote[459].speaker SPEAKER_01
transcript.pyannote[459].start 1074.00659375
transcript.pyannote[459].end 1077.28034375
transcript.pyannote[460].speaker SPEAKER_01
transcript.pyannote[460].start 1077.43221875
transcript.pyannote[460].end 1081.09409375
transcript.pyannote[461].speaker SPEAKER_03
transcript.pyannote[461].start 1080.16596875
transcript.pyannote[461].end 1086.96659375
transcript.pyannote[462].speaker SPEAKER_01
transcript.pyannote[462].start 1083.18659375
transcript.pyannote[462].end 1083.74346875
transcript.pyannote[463].speaker SPEAKER_02
transcript.pyannote[463].start 1086.96659375
transcript.pyannote[463].end 1093.76721875
transcript.pyannote[464].speaker SPEAKER_02
transcript.pyannote[464].start 1093.95284375
transcript.pyannote[464].end 1097.02409375
transcript.pyannote[465].speaker SPEAKER_01
transcript.pyannote[465].start 1097.02409375
transcript.pyannote[465].end 1097.58096875
transcript.pyannote[466].speaker SPEAKER_01
transcript.pyannote[466].start 1098.10409375
transcript.pyannote[466].end 1099.89284375
transcript.pyannote[467].speaker SPEAKER_01
transcript.pyannote[467].start 1100.02784375
transcript.pyannote[467].end 1103.41971875
transcript.pyannote[468].speaker SPEAKER_03
transcript.pyannote[468].start 1103.41971875
transcript.pyannote[468].end 1111.72221875
transcript.pyannote[469].speaker SPEAKER_01
transcript.pyannote[469].start 1108.76909375
transcript.pyannote[469].end 1126.18409375
transcript.pyannote[470].speaker SPEAKER_03
transcript.pyannote[470].start 1113.51096875
transcript.pyannote[470].end 1113.83159375
transcript.pyannote[471].speaker SPEAKER_03
transcript.pyannote[471].start 1115.65409375
transcript.pyannote[471].end 1117.08846875
transcript.pyannote[472].speaker SPEAKER_01
transcript.pyannote[472].start 1126.58909375
transcript.pyannote[472].end 1129.33971875
transcript.pyannote[473].speaker SPEAKER_01
transcript.pyannote[473].start 1129.79534375
transcript.pyannote[473].end 1131.19596875
transcript.pyannote[474].speaker SPEAKER_01
transcript.pyannote[474].start 1131.39846875
transcript.pyannote[474].end 1135.27971875
transcript.pyannote[475].speaker SPEAKER_01
transcript.pyannote[475].start 1135.51596875
transcript.pyannote[475].end 1136.30909375
transcript.pyannote[476].speaker SPEAKER_01
transcript.pyannote[476].start 1136.98409375
transcript.pyannote[476].end 1137.67596875
transcript.pyannote[477].speaker SPEAKER_02
transcript.pyannote[477].start 1137.67596875
transcript.pyannote[477].end 1137.69284375
transcript.pyannote[478].speaker SPEAKER_01
transcript.pyannote[478].start 1138.38471875
transcript.pyannote[478].end 1139.02596875
transcript.pyannote[479].speaker SPEAKER_02
transcript.pyannote[479].start 1139.02596875
transcript.pyannote[479].end 1140.56159375
transcript.pyannote[480].speaker SPEAKER_02
transcript.pyannote[480].start 1140.98346875
transcript.pyannote[480].end 1142.24909375
transcript.pyannote[481].speaker SPEAKER_02
transcript.pyannote[481].start 1142.94096875
transcript.pyannote[481].end 1143.93659375
transcript.pyannote[482].speaker SPEAKER_02
transcript.pyannote[482].start 1145.48909375
transcript.pyannote[482].end 1146.09659375
transcript.pyannote[483].speaker SPEAKER_02
transcript.pyannote[483].start 1147.07534375
transcript.pyannote[483].end 1147.75034375
transcript.pyannote[484].speaker SPEAKER_02
transcript.pyannote[484].start 1148.44221875
transcript.pyannote[484].end 1149.85971875
transcript.pyannote[485].speaker SPEAKER_02
transcript.pyannote[485].start 1151.09159375
transcript.pyannote[485].end 1152.42471875
transcript.pyannote[486].speaker SPEAKER_02
transcript.pyannote[486].start 1153.30221875
transcript.pyannote[486].end 1155.73221875
transcript.pyannote[487].speaker SPEAKER_02
transcript.pyannote[487].start 1156.00221875
transcript.pyannote[487].end 1157.28471875
transcript.pyannote[488].speaker SPEAKER_02
transcript.pyannote[488].start 1157.52096875
transcript.pyannote[488].end 1158.93846875
transcript.pyannote[489].speaker SPEAKER_02
transcript.pyannote[489].start 1159.36034375
transcript.pyannote[489].end 1162.14471875
transcript.pyannote[490].speaker SPEAKER_03
transcript.pyannote[490].start 1163.95034375
transcript.pyannote[490].end 1164.13596875
transcript.pyannote[491].speaker SPEAKER_00
transcript.pyannote[491].start 1194.94971875
transcript.pyannote[491].end 1195.42221875
transcript.pyannote[492].speaker SPEAKER_00
transcript.pyannote[492].start 1195.82721875
transcript.pyannote[492].end 1198.42596875
transcript.whisperx[0].start 9.59
transcript.whisperx[0].end 26.917
transcript.whisperx[0].text 謝謝這個主持人韓院長以及我們的卓院長以及各位先進有請卓院長但是要先拜託主席可不可以時間給我暫停我有權力問題但是要請院長能夠上來麻煩請卓院長備詢
transcript.whisperx[1].start 36.877
transcript.whisperx[1].end 45.022
transcript.whisperx[1].text 向兩位院長報告我之所以提權宜問題啊這是第二次我來總諮詢經濟部長不來第二次我們的韓院長宅心仁厚太好了
transcript.whisperx[2].start 53.26
transcript.whisperx[2].end 67.438
transcript.whisperx[2].text 請問主院長你知道我們郭志輝這個部長他的行程嗎跟委員致歉 不過郭部長今早應與總統有重要的行程我秀給你看 來
transcript.whisperx[3].start 69.574
transcript.whisperx[3].end 78.326
transcript.whisperx[3].text 早上他九點出席與傳統產業作者座談會這個講得過去因為要關心傳統產業受關稅的影響可是下午咧
transcript.whisperx[4].start 85.376
transcript.whisperx[4].end 105.092
transcript.whisperx[4].text 現在我跟他一點關係都沒有這個賴總統的行程是114年國家政務研究班第16期的什麼高階領導研究班開訓典禮跟他一點關係都沒有所以現在顧部長能在哪裡躲在家裡睡覺啊
transcript.whisperx[5].start 106.172
transcript.whisperx[5].end 121.622
transcript.whisperx[5].text 跟他一個關係都沒有啊總院長你被你的屬下欺騙啊他早上請假我覺得我可以接受可是下午他還請假我不能接受他不到另外今天經濟組很重要的
transcript.whisperx[6].start 123.123
transcript.whisperx[6].end 150.604
transcript.whisperx[6].text 國家發展委員會 國科會國科會的主委他生病這個情有可原但是老實講這兩位重要的部長這個重要的部會首長居然在國會殿堂兩次 這已經第二次了我不知道為什麼郭部長每次要執行就不在為什麼每次執行就不在我就拜託這個韓院長以後下一次對於我們郭部長他的請假設施可以更嚴格一點
transcript.whisperx[7].start 151.377
transcript.whisperx[7].end 179.304
transcript.whisperx[7].text 委員 容許我跟您報告事事事 請跟左院長一併報告 跟那個官員各位新聞界廣大的台灣人民報告一下伊利法院執行法第26條規定行政院院長及各部會首長應該親自出席伊利法院的院會並被質詢如果因故不能出席則應該檢訟行政院院長批准之請假書今天兩位首長沒有到是左院長行政院有批准這第一第二
transcript.whisperx[8].start 180.011
transcript.whisperx[8].end 204.55
transcript.whisperx[8].text 再次重申要基於對憲法的尊重以及重視本院委員的質詢要特別拜託左院長針對各部會首長除非出國獲得特別重要且迫切的公務要親自處理的情況之下才能予以同意另外後續的質詢各首長列席的情況也特別要拜託左院長能夠尊切
transcript.whisperx[9].start 205.168
transcript.whisperx[9].end 224.229
transcript.whisperx[9].text 我們能夠確實來進行處理 好嗎 這樣我想謝謝 謝謝韓院長我希望卓院長能夠確實約束啦他早上請假 我剛剛說過因為要聽業主的聲音 我可以接受但是下午 他跑去胡攏區啦 不知道去哪裡啦
transcript.whisperx[10].start 225.011
transcript.whisperx[10].end 252.269
transcript.whisperx[10].text 那還是有其他東西 謝謝但是我每次我都要約束他 我覺得你不可以放縱他郭志輝部長像泥鳅一樣啊 會閃啊早上請假效果就溜掉了 不好啦我選你啦我選你啦每次在會期要開始之前在行政院院會都再三的要求委員長要以親自出席院會的議程為優先他看你沒啊 我替你出氣啊你要知道 我替你講話啊
transcript.whisperx[11].start 255.671
transcript.whisperx[11].end 281.903
transcript.whisperx[11].text 我相信你一定同意賴慶德總統說的AI就是國力我們國家全力發展AI台灣什麼人才資訊人才誰誰叫結果我一看人家排名叫AI人才集中度
transcript.whisperx[12].start 282.984
transcript.whisperx[12].end 292.586
transcript.whisperx[12].text 你現在去看大學的科系啊很多那個好的學校他第一支院已經不是台大醫學院了第一支院就台大志工要去念AI了
transcript.whisperx[13].start 293.792
transcript.whisperx[13].end 312.474
transcript.whisperx[13].text 即便醫生也想要弄一點AI這是未來的趨勢 未來的主流結果我們的人才集中度第一名你看全世界有十個國家以色列 新加坡跟亞洲有關係的第十名 韓國沒有台灣啦 沒有中華民國啊看了難過啊
transcript.whisperx[14].start 314.397
transcript.whisperx[14].end 330.278
transcript.whisperx[14].text 院長啊 我看了心酸啊你可不可以在這裡公開跟大家承諾啊 或者國科會的副主委你是國科會副主委是不是市長 何市長 經濟部不是 國科會副主委要國科會副主委還是你們要講都可以
transcript.whisperx[15].start 331.469
transcript.whisperx[15].end 347.673
transcript.whisperx[15].text 你們有沒有企圖心 什麼時候可以紀錄全市民報告委 去年我們在這裡就像國人說過我們國家的高科技製造力是領先的但是軟體設計軟體設計的人才是沒有的所以一年當中我們很難把他趕上這麼多的人才訓練經濟部已經有一個計畫要在四年內訓練20萬的AI人才一部分從國外引進
transcript.whisperx[16].start 359.963
transcript.whisperx[16].end 374.507
transcript.whisperx[16].text 我不知道你能不能做十年沒有時間我沒有時間聽你講我再請教院長因為這是你院長你帶頭你要不要有一點魄力拿出來一年內我要紀錄前十年多少一個月一年內一年內一年人才的培育不是這樣的簡單兩年兩年我們會達到一個數字像三年
transcript.whisperx[17].start 383.494
transcript.whisperx[17].end 412.483
transcript.whisperx[17].text 我都說過 四年內我們會培育20萬的AI人才四年內 那我們現在已經過了一年了 等於是三年了從現在開始 我們從現在開始從現在開始依照我們去年的計畫 四年就是 剩下三年了三年內我們要培育20萬的AI人才好啦 好啦 這題是送你分數 讓你發揮啦結果你發揮的不好啦我以為你要來現靠我讀下去就說賴委你放心
transcript.whisperx[18].start 413.543
transcript.whisperx[18].end 438.171
transcript.whisperx[18].text 我琢磨人在這裡一年內就給他拚到70名教育是百年的大事不是一兩年可以訓練這麼多的人才訓練的人要能夠實用才是重點我在今天很高興看到教授有正道的學生來我在正道當教授包括立法院基調二十年了我知道沒那麼快但是現在幾乎年輕人義和風都有在擠AI
transcript.whisperx[19].start 439.591
transcript.whisperx[19].end 447.12
transcript.whisperx[19].text 所以一年內 老實講 你要有魄力給錢 給資源我告訴你 一年內就可以達到這個10名內了
transcript.whisperx[20].start 450.234
transcript.whisperx[20].end 459.763
transcript.whisperx[20].text 我會努力啊不是會努力 你要承諾啊今天來聽你承諾啊不是會聽你會努力啊對不對 會努力的話被他騙啊不是這樣啊 對不對好啦 我們來看啊第二個 大家很關心的我們跟美國的關稅談判啊什麼時候可以開始談
transcript.whisperx[21].start 471.581
transcript.whisperx[21].end 489.297
transcript.whisperx[21].text 我們第一階段 第一次的視訊會議已經不是啦 對不起 那個叫準備庭啦你不要呼嚨 那個叫準備庭 那就誤裝你叫什麼名字 我叫卓榮泰這個你出生年齡日 我不笑臉喔第一個是準備庭啦不是談判啦 談判還沒有開始談判的五個國家 沒有台灣啦 沒有中華民國啊
transcript.whisperx[22].start 497.964
transcript.whisperx[22].end 523.073
transcript.whisperx[22].text 報告委員第一次的接觸已經過大家都知道第二次的接觸我們爭取最快的時間對於雙方的默契在事情到達之前我們不予追問因為90天時間也快到了啊4月2號90天就三個月而已喔就七月份初七月初就到期現在已經四月底馬上就五月了你該不該在這裡做一個我不要你具體時間這是你談判的機密
transcript.whisperx[23].start 528.436
transcript.whisperx[23].end 546.716
transcript.whisperx[23].text 但是你可以不可以講說你預估五月底以前一定可以抬到台灣敢這樣講嗎 敢不敢這樣講我說我已備妥方案 我們在很快的時間內是這樣子 問你答案問你答案你都給我抓泥鰍 跑掉了 不可以這樣子
transcript.whisperx[24].start 547.585
transcript.whisperx[24].end 571.907
transcript.whisperx[24].text 五月一定可以五月一定可以談 五月一定談喔這是我已經記起來了 全國都聽到了五月底以前 台灣一定可以排到跟美國談好 那我們就看那你具體目標 現在10%啦那你一覺醒來 你不知道要怎麼30% 80%對不對那是在中間你都可以接受嗎
transcript.whisperx[25].start 573.143
transcript.whisperx[25].end 579.907
transcript.whisperx[25].text 如果是這個數字你我都不能滿意我不能滿意啊我們現在你知道現在美國關稅台灣的商品去美國關稅課幾%你知道嗎平均6.53%啦6.5那個實際的啦加起來是3%啦
transcript.whisperx[26].start 601.46
transcript.whisperx[26].end 603.522
transcript.whisperx[26].text 我們是普通的數字如果平均的加起來要更低喔
transcript.whisperx[27].start 618.914
transcript.whisperx[27].end 636.317
transcript.whisperx[27].text 明目上實質就是加權平均之後是3%啦那我們現在是剋10%啦所以現在來講就7%所以就造成很大的影響你也知道我們現在銷到美國是銷1100多億美金去年度的時候
transcript.whisperx[28].start 638.568
transcript.whisperx[28].end 652.635
transcript.whisperx[28].text 7%代表什麼意思7%代表77億美金就幾千億的台幣所以才會有你昨天癢癢灑灑的報告出來我們都很清楚因為確實已經有傳統業受到傷害了原來3%現在10%差7%傳統產業的毛利 毛山道士這個7%都賣掉開始有人擔心這個無薪假來 你看喔
transcript.whisperx[29].start 667.312
transcript.whisperx[29].end 681.318
transcript.whisperx[29].text 勞動部長 勞動部長說全台超過10萬個勞工受影響然後呢 關稅 中經院的推估關稅如果10% 現在是10%我們GDP下降到2.85%如果15%到20% 1.66%如果悲觀的話那就32% 只剩下0.16% 甚至於馬納死
transcript.whisperx[30].start 692.822
transcript.whisperx[30].end 715.882
transcript.whisperx[30].text 所以你談的你心裡行政院長總是應該讓全國人民知道你的企圖心我們希望你剛剛講了21%你不能接受我也不能接受我覺得底線你可不可以講我底線就撐在那裡說最多都希望你10%啦如果這樣我就給你放鞭炮我們有交給我們的談判團隊將來在談判的
transcript.whisperx[31].start 718.337
transcript.whisperx[31].end 730.957
transcript.whisperx[31].text 進行過程當中 一定會堅持一個對我國最有利的方向當然最好更低更好啦齁10% PLUS-3% 我說這個答案是不是講到你心裡的話有沒有
transcript.whisperx[32].start 732.176
transcript.whisperx[32].end 758.319
transcript.whisperx[32].text 或是你的企圖心我今天都做足給你了我都不知道對你這麼好在談判還沒有開始之前講太多這樣的談判的內容容許我們再做多一點點的思考讓我們在談判過程當中有更大的彈性今天是國會議員問你的話你當然要回答啊表示你的態度拿出來對不對我要讓我的所有的全台灣的產業
transcript.whisperx[33].start 760.077
transcript.whisperx[33].end 781.597
transcript.whisperx[33].text 因為我的領導然後大家的傷害降到最低這是一個企圖性的表現這跟性命沒有關係耶老實講 談判又不是你去談我們的目標就是爭取國家最大的利益讓產業在國際間有競爭力所以我希望我們爭取到的不高於跟我們競爭的國家這個是最低最低你說這東西沒說啦 沒關係 繼續來
transcript.whisperx[34].start 784.72
transcript.whisperx[34].end 808.109
transcript.whisperx[34].text 你昨天談了洋洋灑灑4100億啊我們都知道 這一次老實講啊 院長你人實在是不錯啦但是怎麼會 怎麼做這些奇奇怪怪我們一路叫SNEAKY 你知道嗎 SNEAKY用流氓的做法來做這件事情你講 一開始你講八百八齁 再給人家報告啦 給你兩千啦我們 主席啊
transcript.whisperx[35].start 812.902
transcript.whisperx[35].end 819.467
transcript.whisperx[35].text 部隊帶領的時間都很清楚,我們在下部隊最喜歡講一句話,班長你不要把這個這個什麼,這個這個這個你不要把這個好的消息啊把這個幸運當福氣啊客氣當福氣啊,最喜歡講這一句話不要把客氣當福氣啊
transcript.whisperx[36].start 840.074
transcript.whisperx[36].end 864.421
transcript.whisperx[36].text 我們說給你兩千億 結果你現在空四千億真正跟傳統產業有關的只有九百三 原來你八百八加五十億 九百三 都給你 都給你只要跟產業有關的 都給你我個人的意見 都給你一個人都不為難可是你另外跑來兩條很重要的東西一個
transcript.whisperx[37].start 866.718
transcript.whisperx[37].end 874.682
transcript.whisperx[37].text 又說什麼國土安全任性一千五百億另外一個台電一千億請問台電一千億都不看掉你還要
transcript.whisperx[38].start 877.349
transcript.whisperx[38].end 899.977
transcript.whisperx[38].text 你是怎麼樣我看了是很寬鬆的喔我說假如你承諾用核電我就主張一千億給你你敢這樣主張嗎一柱台電的一千億我們在產業的座談當中產業界屢屢都提到希望電價不要再調整那當然啦就用用國家的錢向老百姓的錢貼補他們用電報戶當然他們要高興啊所以這兩個而且談到國安的
transcript.whisperx[39].start 906.339
transcript.whisperx[39].end 923.109
transcript.whisperx[39].text 國土安全韌性一千五百億不管你買什麼感覺像比較像國防預算這個這兩塊要談的切割出來你不要放在這裡一輪十菜蜜混水摸魚就摸進來了而且講個難聽一點啦趁火打劫啊
transcript.whisperx[40].start 924.087
transcript.whisperx[40].end 927.57
transcript.whisperx[40].text 我們 你這個標885 我沒有說要給你2000結果你登彼此上點你要了4100 結果2500億跟這裡面一定關係都沒有院長 不好啦即使沒有關稅調整的這個事件
transcript.whisperx[41].start 942.385
transcript.whisperx[41].end 957.53
transcript.whisperx[41].text 原來我們對今年的稅計剩餘我們也來準備用將近三千億來做這個兩千億啊這兩條這兩條你要另外成立一個特別預算另外一題不應該混在這裡這裡的話你是談到我們是受了關稅的影響所以這兩千五百億剛剛好來給我們一人一萬塊一人一萬塊普發現金請你在看上一頁
transcript.whisperx[42].start 971.82
transcript.whisperx[42].end 1000.902
transcript.whisperx[42].text 你可以看到物價上漲勞工整個來講我相信經濟你也懂經濟的發展除了外銷佔七成我們還有內需啊當時候上一任的總統蔡英文發六千塊主計長朱哲銘說多了就六千塊GDP增加百分之零點三所以如果一萬塊就增加零點五%的GDP
transcript.whisperx[43].start 1002.729
transcript.whisperx[43].end 1010.055
transcript.whisperx[43].text 這個都是數字在這裡人家0.5的GDP為什麼你不要然後你去搞這些就是你要錢要這麼多
transcript.whisperx[44].start 1012.295
transcript.whisperx[44].end 1018.558
transcript.whisperx[44].text 我已經跟你講了你另外提計畫我們給你支持但是不應該在這個Umbrella的地下這個Umbrella是因應
transcript.whisperx[45].start 1040.031
transcript.whisperx[45].end 1063.203
transcript.whisperx[45].text 美國的關稅衝擊對產業對產業的影響對因為產業的影響勞工受到影響無薪假可能他減薪可能他沒有薪水他沒有工作很可憐啦物價要漲那個樣子給人家一人一萬塊我們對弱勢的照顧這部分也希望委員能夠支持那個也可以照顧沒問題但是你為什麼可以讓你增加GDP0.5%
transcript.whisperx[46].start 1070.151
transcript.whisperx[46].end 1097.438
transcript.whisperx[46].text 你為什麼不要呢?你為什麼不要呢?這是我們最弱勢的道路這次也變成170億170億教育跟人才的培訓也變成200億那很遠啦那很遠是在特別條例通過之後我也不會反對但是我跟你講的是這一條安全任性的一千五plus台電的一千剛好兩千五剛剛好一個人一萬塊這個普發現金你反對嗎?你反對普發現金?
transcript.whisperx[47].start 1098.118
transcript.whisperx[47].end 1125.651
transcript.whisperx[47].text 我覺得普發現金是一個最簡單的方式但是不能達到我們現在期待的效果朱正麟的功課可以賺GDP算起來就是0.5%的一個GDP我們國家現在的生命經濟的威脅等等跟關稅貿易秩序的沖繩我們需要依薩成達以一起的力量去對抗我再跟你確定一點啦你反對普發現金一萬就對了 是不是因為普發現金不是最好的方式對我來講也許是最簡單的
transcript.whisperx[48].start 1126.631
transcript.whisperx[48].end 1149.856
transcript.whisperx[48].text 反對普發現金一萬四你講的是不是我覺得他不是好的方向你反對普發現金最簡單不是都不用反對好 還有一個我們來看喔我們現在美國阿拉斯加很北的地方LNG液態天然氣liquid natural gas440億美金
transcript.whisperx[49].start 1153.325
transcript.whisperx[49].end 1156.987
transcript.whisperx[49].text 日本由於韓國標泰要參與這應該得等於蔣介石連就直接叫我們付錢 三個國家付錢啊
transcript.whisperx[50].start 1191.339
transcript.whisperx[50].end 1195.261
transcript.whisperx[50].text 好,謝謝賴氏寶委員質詢
gazette.lineno 15
gazette.blocks[0][0] 賴委員士葆:(14時31分)謝謝主持人韓院長、卓院長,以及各位先進。有請卓院長,但是要先拜託主席可不可以給我時間暫停?我有權宜問題,但是要請院長上來。
gazette.blocks[1][0] 主席:麻煩請卓院長備詢。
gazette.blocks[2][0] 賴委員士葆:向兩位院長報告,我之所以提權宜問題,這是我第二次來總質詢,經濟部長不來。第二次!我們的韓院長宅心仁厚,太好了。請問卓院長,你知道郭智輝部長的行程嗎?
gazette.blocks[3][0] 卓院長榮泰:跟委員致歉,郭部長今早因與總統有重要行程……
gazette.blocks[4][0] 賴委員士葆:好,我show給你看,他早上九點出席「與傳統產業業者座談會」,這個講得過去,因為關心傳統產業受關稅的影響,可是下午跟他一點關係都沒有,下午賴總統的行程是「114年國家政務研究班第16期及高階領導研究班第15期聯合開訓典禮」,跟他一點關係都沒有,所以現在郭部長人在哪裡?躲在家裡睡覺嗎?跟他一點關係都沒有啊!卓院長,你被你的屬下欺騙了。
gazette.blocks[5][0] 卓院長榮泰:我……
gazette.blocks[6][0] 賴委員士葆:他早上請假,我覺得可以接受,可是下午他也請假,我不能接受他不到。另外,今天經濟組很重要的國家發展委員會主委生病,這個情有可原。但是老實講這兩位重要的部會首長,居然在國會殿堂缺席兩次,這已經第二次了,我不知道為什麼每次我質詢郭部長就不在,我拜託韓院長,下一次對郭部長請假是不是可以更嚴格一點?
gazette.blocks[7][0] 主席:委員,容許我跟你報告一下。
gazette.blocks[8][0] 賴委員士葆:是,請。
gazette.blocks[9][0] 主席:跟卓院長一併報告,也跟各位內閣官員、各位新聞界和廣大的臺灣人民報告一下。第一,依立法院職權行使法第二十六條規定,行政院院長及各部會首長應該親自出席立法院院會,並備質詢,因故不能出席者,應該檢送行政院院長批准之請假書。今天兩位首長沒有到,行政院卓院長有批准。第二,再次重申,基於對憲法之尊重,以及重視本院委員的質詢,要特別拜託卓院長,各部會首長除非出國或者有特別重要且迫切的公務要親自處理的情況之下,才能予以同意。另外,後續質詢各首長列席的情況,也特別要拜託卓院長能夠確實進行處理,好嗎?賴委員,這樣我想我也跟您報告了,那我們就正式開始質詢,好嗎?
gazette.blocks[10][0] 卓院長榮泰:謝謝韓院長。
gazette.blocks[11][0] 賴委員士葆:我希望卓院長能夠確實約束,他早上請假,我剛剛說過,因為要聽業者的聲音,我可以接受,但是下午他跑去糊弄,不知道去哪裡了。
gazette.blocks[12][0] 卓院長榮泰:他還是有其他公務行程,但是我每次都……
gazette.blocks[13][0] 賴委員士葆:要約束他,我覺得你不可以放縱他。
gazette.blocks[14][0] 卓院長榮泰:不會。
gazette.blocks[15][0] 賴委員士葆:郭智輝部長像泥鰍一樣啊!會閃啊!早上請假,下午就溜掉了,不好啦!這樣有損你啦!
gazette.blocks[16][0] 卓院長榮泰:跟委員報告,每次在會期要開始之前,我在行政院院會都再三要求部會首長要以親自出席院會的議程為優先。
gazette.blocks[17][0] 賴委員士葆:他看不起你啊!我替你出氣啊!你要知道。
gazette.blocks[18][0] 卓院長榮泰:不會、不會。
gazette.blocks[19][0] 賴委員士葆:我替你講話啊!
gazette.blocks[20][0] 主席:賴委員,現在我們開始進入正式質詢。
gazette.blocks[21][0] 賴委員士葆:好,開始詢答。
gazette.blocks[22][0] 卓院長榮泰:謝謝委員。
gazette.blocks[23][0] 主席:時間開始,請賴委員質詢。
gazette.blocks[24][0] 賴委員士葆:我相信你一定同意賴清德總統所講的AI就是國力,對吧?
gazette.blocks[25][0] 卓院長榮泰:是。
gazette.blocks[26][0] 賴委員士葆:我們國家全力發展AI,臺灣什麼沒有?資訊人才「削削叫」!結果我一看,乖乖,人家的排名叫AI人才集中度,你現在去看大學的科系,很多好的學校,它的第一志願已經不是臺大醫學院了,第一志願是臺大資工,要去唸AI了,即便醫生也想弄一點AI,這是未來的趨勢、未來的主流。結果我們的人才集中度,你看全世界前10個國家,以色列、新加坡,跟亞洲有關係的第10名是韓國,沒有臺灣啦!沒有中華民國啊!看了難過啊!院長,我看了心酸啦!你可不可以在這裡公開跟大家承諾?或者國科會的副主委來,你是國科會副主委是不是?
gazette.blocks[27][0] 卓院長榮泰:是何次長,經濟部。
gazette.blocks[28][0] 賴委員士葆:不是,要國科會副主委。還是你們要講?都可以。
gazette.blocks[29][0] 卓院長榮泰:跟委員報告……
gazette.blocks[30][0] 賴委員士葆:你們有沒有企圖心?什麼時候可以擠入前10名?
gazette.blocks[31][0] 卓院長榮泰:報告委員,去年我們在這裡就向國人說過,我們國家的高科技製造力是領先的,但是我們軟體設計的人才是不足的。
gazette.blocks[32][0] 賴委員士葆:沒有耶!前10名都沒有耶!
gazette.blocks[33][0] 卓院長榮泰:所以一年當中我們很難趕上這麼多的人才訓練,經濟部已經有一個計畫,要在四年內訓練20萬的AI人才……
gazette.blocks[34][0] 賴委員士葆:所以四年才能擠進前10名?
gazette.blocks[35][0] 卓院長榮泰:一部分從國內訓練,一部分從國外引進。
gazette.blocks[36][0] 賴委員士葆:我不知道你能不能做四年!
gazette.blocks[37][0] 高副主任委員仙桂:……
gazette.blocks[38][0] 賴委員士葆:我沒有時間聽你講,我就請教院長,因為這是院長你帶頭,你要不要有一點魄力拿出來,一年內我要擠入前10名,可以嗎?
gazette.blocks[39][0] 卓院長榮泰:多少?一個月?
gazette.blocks[40][0] 賴委員士葆:一年內、一年內,一年。
gazette.blocks[41][0] 卓院長榮泰:人才的培育不是這樣的……
gazette.blocks[42][0] 賴委員士葆:兩年?
gazette.blocks[43][0] 卓院長榮泰:兩年我們會達到一個數字,像……
gazette.blocks[44][0] 賴委員士葆:三年?
gazette.blocks[45][0] 卓院長榮泰:我剛剛說過了,四年內我們會培育20萬的AI人才。
gazette.blocks[46][0] 賴委員士葆:院長啊!三年都不敢……
gazette.blocks[47][0] 卓院長榮泰:四年內……那我們現在已經過了一年了,等於是三年啦!
gazette.blocks[48][0] 賴委員士葆:從現在開始,我們從現在開始,從現在開始。
gazette.blocks[49][0] 卓院長榮泰:依照我們去年的計畫四年,就是剩下三年啦!三年內我們要培育20萬的AI人才。
gazette.blocks[50][0] 賴委員士葆:太慢啦!好啦、好啦!這一題是送你分數,讓你發揮啦!結果你也發揮得不好啦!我以為你會拍胸脯說:賴委員你放心,我卓某人在這裡一年內就給它拼到前10名。這樣才是我要的啦!
gazette.blocks[51][0] 卓院長榮泰:教育是百年的大事,不是一兩年可以訓練這麼多的人才。
gazette.blocks[52][0] 賴委員士葆:我知道啦!
gazette.blocks[53][0] 卓院長榮泰:而且訓練的人要能夠實用才是重點啦!
gazette.blocks[54][0] 賴委員士葆:今天很高興看到有政大的學生來,我在政大當教授,包括立法院借調,20年了啦!我知道沒那麼快,但是現在幾乎年輕人一窩蜂的在擠AI啦!所以一年內老實講你要有魄力,給錢、給資源,我告訴你,一年內就可以達到10名內啦!
gazette.blocks[55][0] 卓院長榮泰:我們會努力。
gazette.blocks[56][0] 賴委員士葆:不是會努力,你要承諾啊!今天來聽你承諾啊!不是聽你說會努力啊!對不對?會努力就是討價還價,就不是這樣啊!對不對?
gazette.blocks[56][1] 好啦!我們來看一兩個大家很關心的,我們跟美國的關稅談判,什麼時候可以開始談?
gazette.blocks[57][0] 卓院長榮泰:我們第一階段第一次的視訊會議,已經在4月11號……
gazette.blocks[58][0] 賴委員士葆:那個不是啦!對不起,那個叫「準備庭」啦!你不要糊弄,那個叫準備庭,那是問你叫什麼名字?我叫卓榮泰;你的出生年月日?很年輕耶!第一個是準備庭啦!那不是談判,談判還沒有開始,談判的5個國家沒有臺灣啦!沒有中華民國啊!
gazette.blocks[59][0] 卓院長榮泰:報告委員,第一次的接觸大家都知道,第二次的接觸,我們會爭取最快的時間……
gazette.blocks[60][0] 賴委員士葆:什麼時候嘛?
gazette.blocks[61][0] 卓院長榮泰:依雙方的默契,在事情最後到達之前,我們不宜對外說明。
gazette.blocks[62][0] 賴委員士葆:我知道,但是你總是……因為90天時間也快到了,4月2號說的,90天就三個月而已喔!7月初就到期,現在已經4月底,馬上就5月了……
gazette.blocks[63][0] 卓院長榮泰:我方已備妥方案。
gazette.blocks[64][0] 賴委員士葆:你可不可以在這裡做一個……我不要你具體時間,這是你談判的機密,我尊重,但是你可不可以預估5月底以前一定可以排到臺灣,你敢這樣講嗎?敢不敢這樣講?
gazette.blocks[65][0] 卓院長榮泰:我是說我已備妥方案,我們在很快的時間內可以……
gazette.blocks[66][0] 賴委員士葆:怎麼還是這樣子!我問你答案,你都給我裝泥鰍跑掉了,不可以這樣子啦!
gazette.blocks[67][0] 卓院長榮泰:5月一定可以。
gazette.blocks[68][0] 賴委員士葆:院長,5月一定可以談,5月一定談喔!這事我已經記起來了,全國都聽到了,5月底以前臺灣一定可以排到跟美國談。好,我們就看你的具體目標,現在是10%,你一覺醒來就不知道該怎麼辦,因為變成32%了,對不對?那在中間的話,你都可以接受嗎?比如說,不然就是「殘殘豆乾切五角」,直接切一半,10%加32%,42%除以2就是21%,21%你滿意嗎?
gazette.blocks[69][0] 卓院長榮泰:如果是這個數字,你我都不能滿意啊!
gazette.blocks[70][0] 賴委員士葆:不能滿意啊!你知道我們臺灣的商品現在去美國的關稅是課百分之幾嗎?
gazette.blocks[71][0] 卓院長榮泰:平均6.5%。
gazette.blocks[72][0] 賴委員士葆:3%啦,怎麼是6.5%?
gazette.blocks[73][0] 卓院長榮泰:平均啦!
gazette.blocks[74][0] 賴委員士葆:要看實際的啦,加權下來是3%啦,你那個是nominal(名目)6.5%,實質是3%,對吧?那個經濟部次長……
gazette.blocks[75][0] 卓院長榮泰:是平均……
gazette.blocks[76][0] 賴委員士葆:是3%,不是6.5%。
gazette.blocks[77][0] 卓院長榮泰:平均的還要更低。
gazette.blocks[78][0] 賴委員士葆:3%啦!
gazette.blocks[79][0] 卓院長榮泰:我們是普通的數字,如果是平均的加起來還會更低。
gazette.blocks[80][0] 賴委員士葆:名目上……實質就是加權平均之後是3%啦!好,我們現在是課10%,所以現在差7%,就會造成很大的影響。你也知道我們去年度銷到美國的有一千一百多億美金,所以7%代表什麼意思?7%代表77億美金,就是幾千億臺幣,所以才會有你昨天洋洋灑灑的報告出來。我們都很清楚,因為確實已經有傳統產業受到傷害了,原來是3%,現在是10%,差了7%,傳統產業的毛利只有「毛三到四」,一次多7%,真的是承受不了,開始有人擔心無薪假了。
gazette.blocks[80][1] 你看,勞動部長說,全臺超過10萬個勞工受影響,然後中經院的推估,關稅如果是10%,現在就是10%,我們的GDP就會下修到2.85%,如果是15%到20%,就是1.66%,如果悲觀的話,課32%就只剩0.16%,甚至是minus,對不對?所以你心裡……行政院長總是要讓全國人民知道你的企圖心,我們希望就像你剛剛講的,21%你不能接受,我也不能接受,我覺得底線……你可不可以講,我的底線就是撐在那裡,最多就是給你10%啦!如果這樣,我就給你放鞭炮。
gazette.blocks[81][0] 卓院長榮泰:底線我有交給我們的談判團隊,將來在談判進行的過程當中,我們會堅持一個對我國最有利的方向。
gazette.blocks[82][0] 賴委員士葆:當然是愈低愈好啦!10%plus、minus3%可不可以?我說的這個答案,是不是有講到你心裡的話,有沒有?否則你的企圖心呢?我今天都一直在做球給你耶,都不知道我對你這麼好!
gazette.blocks[83][0] 卓院長榮泰:在談判還沒有開始之前,講太多這樣的談判內容……容許我們再做多一點點的思考,讓我們在談判的過程當中會有更大的彈性。
gazette.blocks[84][0] 賴委員士葆:今天是國會議員問你,你當然要回答啊!
gazette.blocks[85][0] 卓院長榮泰:就是因為這個地方……
gazette.blocks[86][0] 賴委員士葆:把你的態度拿出來,對不對?我要讓全臺灣所有的產業因為我的領導,把大家的傷害降到最低,這是一個企圖心的表現,這跟洩密沒有關係。老實講,談判也不是你去談。
gazette.blocks[87][0] 卓院長榮泰:我們的目標就是爭取國家最大的利益,讓產業在國際之間有競爭力,所以我希望爭取到的高於跟我們競爭的國家,這個最低最低的……
gazette.blocks[88][0] 賴委員士葆:你講這個等於沒講,不要緊,繼續來。你昨天談了洋洋灑灑的4,100億,我們都知道這一次……老實講,院長,你的人實在是不錯啦!但是怎麼會做這些奇奇怪怪的事,在英文這就叫做sneaky,你知道sneaky嗎?用溜的做法來做這個事情。
gazette.blocks[88][1] 一開始你講880億,在野黨說不夠,給你2,000億啦!我們主席在部隊待了一段時間都很清楚,我們下部隊,班長就會先講一句話:對於這個好的消息,你要把幸運當福氣、把客氣當福氣。他們最喜歡講這一句話:不要把客氣當福氣啦!我們說給你2,000億,結果你現在匡列4,000億,真正跟傳統產業有關的只有930億,原來880億加50億是930億,也都給你,只要跟產業有關的都給你,我個人的意見都給你,一點都不為難!可是你另外又加了兩條很重要的預算,一個叫做國土安全韌性1,500億,另外一個是台電1,000億。台電的1,000億都被砍掉了,你還要?你是怎麼樣?我個人是很寬鬆的喔,我說假如你承諾使用核電,我就主張1,000億給你,你敢這樣主張嗎?
gazette.blocks[89][0] 卓院長榮泰:挹注台電的1,000億是我們在跟產業界的座談當中,產業界屢屢都提到,希望電價不要再調漲,我們希望……
gazette.blocks[90][0] 賴委員士葆:那當然啊!就用國家的錢、小老百姓的錢來貼補他們用電大戶,當然他們要高興啊!是不是?
gazette.blocks[91][0] 卓院長榮泰:為了能夠健全台電的財政……
gazette.blocks[92][0] 賴委員士葆:再談到國安的國土安全韌性1,500億,不管你買什麼,感覺比較像國防預算,這兩塊要談的話,請切割出來,不要放在這裡面像「什錦麵」,混水摸魚就摸進來了,而且講個難聽一點,趁火打劫啊!
gazette.blocks[93][0] 卓院長榮泰:報告委員,並非如此。
gazette.blocks[94][0] 賴委員士葆:你要880億,我們說要給你2,000億,結果你蹬鼻子上臉,要了4,100億,結果2,500億跟這裡面一點關係都沒有。
gazette.blocks[95][0] 卓院長榮泰:在日前跟今天都有說過……
gazette.blocks[96][0] 賴委員士葆:院長,不好啦!
gazette.blocks[97][0] 卓院長榮泰:即使沒有關稅調整的這個事件……
gazette.blocks[98][0] 賴委員士葆:這樣不好啦!
gazette.blocks[99][0] 卓院長榮泰:原本我們對今年的歲計賸餘,也準備用將近3,000億來做特別條例、特別預算的……
gazette.blocks[100][0] 賴委員士葆:用這2,000億來做這兩條!這兩條你要,就另外成立一個特別預算,另外去提,不應該混在這裡……
gazette.blocks[101][0] 卓院長榮泰:特別預算……
gazette.blocks[102][0] 賴委員士葆:你是談到我們受了關稅的影響,所以這2,500億剛剛好可以普發現金給我們一人1萬元。你可以看到物價上漲,對勞工整個來講……我相信經濟你也懂,經濟的發展,除了外銷占7成,我們還有內需啦!上一任的總統蔡英文普發6,000元,時任主計長朱澤民說:多了這6,000元,GDP增加了0.3%。所以如果普發1萬元就增加0.5%的GDP,數字都在這裡,增加0.5%的GDP,為什麼你不要,而是去搞這些,要這麼多錢?
gazette.blocks[103][0] 卓院長榮泰:報告委員,關稅……
gazette.blocks[104][0] 賴委員士葆:趁火打劫,不好啦!院長。
gazette.blocks[105][0] 卓院長榮泰:在新關稅之下,全球的貿易秩序在重整,而且在地緣政治下,臺灣面臨了很多新的威脅,我們希望國家的力量能夠集中在這裡,以聚沙成塔的方式去面對直接威脅的風暴。
gazette.blocks[106][0] 賴委員士葆:我已經跟你講了,你另外提計畫,我們給你支持,但是不應該在這個umbrella底下,這umbrella是因應美國的關稅衝擊對產業的影響,也因為產業的影響,導致勞工也受到影響,像是可能放無薪假、被減薪、沒有薪水、沒有工作,很可憐啦!物價又漲的那個樣子,給他們一人1萬元。
gazette.blocks[107][0] 卓院長榮泰:我們對產業界的損失、對弱勢的照顧,這部分也希望委員能夠支持。
gazette.blocks[108][0] 賴委員士葆:那個可以照顧,這沒問題。
gazette.blocks[109][0] 卓院長榮泰:對弱勢的照顧、為人才的培育,我們都有編啊!
gazette.blocks[110][0] 賴委員士葆:但是明明可以讓你增加0.5%的GDP,你為什麼不要呢?你為什麼不要呢?這是主計長提到的。
gazette.blocks[111][0] 卓院長榮泰:我們對弱勢的照顧,在這次編了170億。
gazette.blocks[112][0] 賴委員士葆:170億?
gazette.blocks[113][0] 卓院長榮泰:教育跟人才的培訓也編了200億。
gazette.blocks[114][0] 賴委員士葆:那很遠啦!
gazette.blocks[115][0] 卓院長榮泰:當然都是在特別條例通過之後……
gazette.blocks[116][0] 賴委員士葆:那個我也不會反對,但是我跟你講的是國土安全韌性的1,500億plus台電的1,000億,總共2,500億,剛剛好一個人1萬元,就是普發現金,你反對嗎?你反對普發現金?
gazette.blocks[117][0] 卓院長榮泰:我覺得普發現金是一個最簡單的方式,但是無法達到我們現在期待的效果。
gazette.blocks[118][0] 賴委員士葆:前主計長朱澤民說,算起來可以增加0.5%的GDP,不得了了,0.5%GDP很了不起耶!
gazette.blocks[119][0] 卓院長榮泰:我們國家現在面臨新的威脅跟關稅貿易秩序的重整,我們需要聚沙成塔,用大家的力量一起去面對它。
gazette.blocks[120][0] 賴委員士葆:好啦!我再跟你確定一點,你反對普發現金1萬就對了,是不是?
gazette.blocks[121][0] 卓院長榮泰:普發現金不是最好的方式,對政府來講也許是最簡單的。
gazette.blocks[122][0] 賴委員士葆:你回答我,反對普發現金1萬是你講的,是不是?
gazette.blocks[123][0] 卓院長榮泰:我覺得它不是好的方向……
gazette.blocks[124][0] 賴委員士葆:就你反對嘛!
gazette.blocks[125][0] 卓院長榮泰:對政府來講,普發現金最簡單,什麼都不用煩惱……
gazette.blocks[126][0] 賴委員士葆:好。另外一個,我們來看,現在美國阿拉斯加(在很北的地方)LNG(液態天然氣Liquefied Natural Gas)案耗資440億美金,日本猶豫,韓國表態要參與,這個東西講難聽點就是直接叫我們三個國家付錢,這個我們要不要付?我們要不要參與?
gazette.blocks[127][0] 卓院長榮泰:對美的投資與採購,我們都審慎進行當中,會以國家的利益為重。
gazette.blocks[128][0] 賴委員士葆:所以就是參與就對了?
gazette.blocks[129][0] 卓院長榮泰:我們再評估對國家最大的利益。
gazette.blocks[130][0] 賴委員士葆:什麼時候可以出來?
gazette.blocks[131][0] 卓院長榮泰:現在我沒有時間表。
gazette.blocks[132][0] 賴委員士葆:這個很重要喔!這個耗資440億美金,如果我們全部參與的話,等於川普要我們吐出來的錢就全部吐出來了,還要370億吐給他,440億就夠了啊!
gazette.blocks[133][0] 主席:謝謝賴士葆委員質詢,謝謝卓院長、各部會首長的備詢,謝謝。
gazette.blocks[133][1] 報告院會,現在議場二樓是來自國立臺灣大學法律系的同學,未來臺灣的棟梁、人才,我們掌聲歡迎!
gazette.blocks[133][2] 接下來下面登記的蔡其昌委員、鍾佳濱委員、沈發惠委員、徐富癸委員、蔡易餘委員等之質詢,均以書面提出,請行政院書面答復,並列入紀錄,刊登公報。
gazette.agenda.page_end 98
gazette.agenda.meet_id 院會-11-3-9
gazette.agenda.speakers[0] 韓國瑜
gazette.agenda.speakers[1] 黃國昌
gazette.agenda.speakers[2] 黃珊珊
gazette.agenda.speakers[3] 王定宇
gazette.agenda.speakers[4] 陳素月
gazette.agenda.speakers[5] 葛如鈞
gazette.agenda.speakers[6] 許宇甄
gazette.agenda.speakers[7] 吳琪銘
gazette.agenda.speakers[8] 賴士葆
gazette.agenda.speakers[9] 蔡其昌
gazette.agenda.speakers[10] 鍾佳濱
gazette.agenda.speakers[11] 沈發惠
gazette.agenda.speakers[12] 陳菁徽
gazette.agenda.speakers[13] 羅明才
gazette.agenda.speakers[14] 吳宗憲
gazette.agenda.speakers[15] 陳超明
gazette.agenda.speakers[16] 黃建賓
gazette.agenda.speakers[17] 張宏陸
gazette.agenda.speakers[18] 丁學忠
gazette.agenda.page_start 30
gazette.agenda.meetingDate[0] 2025-04-25
gazette.agenda.gazette_id 1143901
gazette.agenda.agenda_lcidc_ids[0] 1143901_00002
gazette.agenda.agenda_lcidc_ids[1] 1143901_00003
gazette.agenda.meet_name 立法院第11屆第3會期第9次會議紀錄
gazette.agenda.content 施政質詢 對行政院院長提出施政方針及施政報告繼續質詢─ 繼續質詢─
gazette.agenda.agenda_id 1143901_00003