iVOD / 166045

Field Value
IVOD_ID 166045
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/166045
日期 2025-12-01
會議資料.會議代碼 委員會-11-4-19-13
會議資料.會議代碼:str 第11屆第4會期經濟委員會第13次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 13
會議資料.種類 委員會
會議資料.委員會代碼[0] 19
會議資料.委員會代碼:str[0] 經濟委員會
會議資料.標題 第11屆第4會期經濟委員會第13次全體委員會議
影片種類 Clip
開始時間 2025-12-01T09:56:29+08:00
結束時間 2025-12-01T10:08:00+08:00
影片長度 00:11:31
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/3f8163f3efc01af795960db1329912fbb28663f7a8bd1180b07b1c5d8e9378773eca6ea80bfd1def5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 謝衣鳯
委員發言時間 09:56:29 - 10:08:00
會議時間 2025-12-01T09:00:00+08:00
會議名稱 立法院第11屆第4會期經濟委員會第13次全體委員會議(事由:邀請經濟部部長、國家發展委員會主任委員、行政院經貿談判辦公室首長、外交部首長及國家安全局首長就「台美關稅協議之談判方針、進度、爭議事項、雙方可能承諾及台灣產業之影響評估」進行報告,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_03
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 0.43596875
transcript.pyannote[1].speaker SPEAKER_03
transcript.pyannote[1].start 8.65409375
transcript.pyannote[1].end 9.14346875
transcript.pyannote[2].speaker SPEAKER_03
transcript.pyannote[2].start 9.73409375
transcript.pyannote[2].end 11.21909375
transcript.pyannote[3].speaker SPEAKER_03
transcript.pyannote[3].start 12.67034375
transcript.pyannote[3].end 14.08784375
transcript.pyannote[4].speaker SPEAKER_03
transcript.pyannote[4].start 15.18471875
transcript.pyannote[4].end 16.45034375
transcript.pyannote[5].speaker SPEAKER_03
transcript.pyannote[5].start 16.73721875
transcript.pyannote[5].end 22.49159375
transcript.pyannote[6].speaker SPEAKER_03
transcript.pyannote[6].start 28.73534375
transcript.pyannote[6].end 29.86596875
transcript.pyannote[7].speaker SPEAKER_03
transcript.pyannote[7].start 31.85721875
transcript.pyannote[7].end 32.98784375
transcript.pyannote[8].speaker SPEAKER_03
transcript.pyannote[8].start 33.24096875
transcript.pyannote[8].end 34.84409375
transcript.pyannote[9].speaker SPEAKER_03
transcript.pyannote[9].start 35.38409375
transcript.pyannote[9].end 41.29034375
transcript.pyannote[10].speaker SPEAKER_03
transcript.pyannote[10].start 41.86409375
transcript.pyannote[10].end 48.37784375
transcript.pyannote[11].speaker SPEAKER_03
transcript.pyannote[11].start 48.96846875
transcript.pyannote[11].end 55.27971875
transcript.pyannote[12].speaker SPEAKER_03
transcript.pyannote[12].start 55.66784375
transcript.pyannote[12].end 57.62534375
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 58.87409375
transcript.pyannote[13].end 63.54846875
transcript.pyannote[14].speaker SPEAKER_03
transcript.pyannote[14].start 64.45971875
transcript.pyannote[14].end 64.93221875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 65.79284375
transcript.pyannote[15].end 76.28909375
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 76.52534375
transcript.pyannote[16].end 77.11596875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 77.21721875
transcript.pyannote[17].end 82.09409375
transcript.pyannote[18].speaker SPEAKER_03
transcript.pyannote[18].start 82.31346875
transcript.pyannote[18].end 82.33034375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 82.33034375
transcript.pyannote[19].end 83.20784375
transcript.pyannote[20].speaker SPEAKER_03
transcript.pyannote[20].start 83.20784375
transcript.pyannote[20].end 83.30909375
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 83.66346875
transcript.pyannote[21].end 83.68034375
transcript.pyannote[22].speaker SPEAKER_03
transcript.pyannote[22].start 83.68034375
transcript.pyannote[22].end 83.69721875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 83.69721875
transcript.pyannote[23].end 84.03471875
transcript.pyannote[24].speaker SPEAKER_03
transcript.pyannote[24].start 84.03471875
transcript.pyannote[24].end 84.45659375
transcript.pyannote[25].speaker SPEAKER_03
transcript.pyannote[25].start 84.70971875
transcript.pyannote[25].end 87.69659375
transcript.pyannote[26].speaker SPEAKER_03
transcript.pyannote[26].start 88.33784375
transcript.pyannote[26].end 98.81721875
transcript.pyannote[27].speaker SPEAKER_03
transcript.pyannote[27].start 99.42471875
transcript.pyannote[27].end 104.18346875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 105.17909375
transcript.pyannote[28].end 124.45034375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 115.94534375
transcript.pyannote[29].end 116.46846875
transcript.pyannote[30].speaker SPEAKER_03
transcript.pyannote[30].start 124.45034375
transcript.pyannote[30].end 124.51784375
transcript.pyannote[31].speaker SPEAKER_03
transcript.pyannote[31].start 124.75409375
transcript.pyannote[31].end 124.80471875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 124.80471875
transcript.pyannote[32].end 124.97346875
transcript.pyannote[33].speaker SPEAKER_03
transcript.pyannote[33].start 124.97346875
transcript.pyannote[33].end 126.62721875
transcript.pyannote[34].speaker SPEAKER_03
transcript.pyannote[34].start 126.81284375
transcript.pyannote[34].end 127.20096875
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 128.09534375
transcript.pyannote[35].end 134.23784375
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 133.63034375
transcript.pyannote[36].end 137.19096875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 135.38534375
transcript.pyannote[37].end 137.22471875
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 137.22471875
transcript.pyannote[38].end 154.28534375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 155.39909375
transcript.pyannote[39].end 157.25534375
transcript.pyannote[40].speaker SPEAKER_03
transcript.pyannote[40].start 157.62659375
transcript.pyannote[40].end 161.45721875
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 160.25909375
transcript.pyannote[41].end 162.08159375
transcript.pyannote[42].speaker SPEAKER_03
transcript.pyannote[42].start 161.92971875
transcript.pyannote[42].end 188.01846875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 188.01846875
transcript.pyannote[43].end 188.52471875
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 188.82846875
transcript.pyannote[44].end 192.45659375
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 192.91221875
transcript.pyannote[45].end 196.05096875
transcript.pyannote[46].speaker SPEAKER_03
transcript.pyannote[46].start 196.25346875
transcript.pyannote[46].end 197.99159375
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 199.17284375
transcript.pyannote[47].end 199.99971875
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 200.57346875
transcript.pyannote[48].end 202.02471875
transcript.pyannote[49].speaker SPEAKER_03
transcript.pyannote[49].start 201.67034375
transcript.pyannote[49].end 204.03284375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 204.03284375
transcript.pyannote[50].end 208.97721875
transcript.pyannote[51].speaker SPEAKER_03
transcript.pyannote[51].start 207.74534375
transcript.pyannote[51].end 208.65659375
transcript.pyannote[52].speaker SPEAKER_03
transcript.pyannote[52].start 208.97721875
transcript.pyannote[52].end 209.02784375
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 209.02784375
transcript.pyannote[53].end 209.23034375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 209.66909375
transcript.pyannote[54].end 213.22971875
transcript.pyannote[55].speaker SPEAKER_03
transcript.pyannote[55].start 209.68596875
transcript.pyannote[55].end 211.54221875
transcript.pyannote[56].speaker SPEAKER_03
transcript.pyannote[56].start 213.41534375
transcript.pyannote[56].end 216.40221875
transcript.pyannote[57].speaker SPEAKER_03
transcript.pyannote[57].start 216.97596875
transcript.pyannote[57].end 217.92096875
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 218.76471875
transcript.pyannote[58].end 220.19909375
transcript.pyannote[59].speaker SPEAKER_03
transcript.pyannote[59].start 220.40159375
transcript.pyannote[59].end 222.54471875
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 222.84846875
transcript.pyannote[60].end 226.39221875
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 226.84784375
transcript.pyannote[61].end 237.61409375
transcript.pyannote[62].speaker SPEAKER_03
transcript.pyannote[62].start 236.24721875
transcript.pyannote[62].end 236.51721875
transcript.pyannote[63].speaker SPEAKER_03
transcript.pyannote[63].start 237.56346875
transcript.pyannote[63].end 239.18346875
transcript.pyannote[64].speaker SPEAKER_03
transcript.pyannote[64].start 239.62221875
transcript.pyannote[64].end 239.68971875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 239.68971875
transcript.pyannote[65].end 239.90909375
transcript.pyannote[66].speaker SPEAKER_03
transcript.pyannote[66].start 239.90909375
transcript.pyannote[66].end 258.04971875
transcript.pyannote[67].speaker SPEAKER_03
transcript.pyannote[67].start 258.11721875
transcript.pyannote[67].end 265.86284375
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 266.47034375
transcript.pyannote[68].end 277.03409375
transcript.pyannote[69].speaker SPEAKER_03
transcript.pyannote[69].start 277.03409375
transcript.pyannote[69].end 287.76659375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 287.34471875
transcript.pyannote[70].end 289.08284375
transcript.pyannote[71].speaker SPEAKER_03
transcript.pyannote[71].start 289.16721875
transcript.pyannote[71].end 289.99409375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 289.99409375
transcript.pyannote[72].end 290.01096875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 290.97284375
transcript.pyannote[73].end 293.23409375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 293.62221875
transcript.pyannote[74].end 296.25471875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 296.54159375
transcript.pyannote[75].end 301.51971875
transcript.pyannote[76].speaker SPEAKER_03
transcript.pyannote[76].start 301.51971875
transcript.pyannote[76].end 301.55346875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 302.36346875
transcript.pyannote[77].end 302.97096875
transcript.pyannote[78].speaker SPEAKER_03
transcript.pyannote[78].start 302.97096875
transcript.pyannote[78].end 311.03721875
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 311.03721875
transcript.pyannote[79].end 311.56034375
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 312.62346875
transcript.pyannote[80].end 326.83221875
transcript.pyannote[81].speaker SPEAKER_03
transcript.pyannote[81].start 314.17596875
transcript.pyannote[81].end 314.69909375
transcript.pyannote[82].speaker SPEAKER_03
transcript.pyannote[82].start 320.74034375
transcript.pyannote[82].end 321.24659375
transcript.pyannote[83].speaker SPEAKER_03
transcript.pyannote[83].start 324.63846875
transcript.pyannote[83].end 339.85971875
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 339.89346875
transcript.pyannote[84].end 344.51721875
transcript.pyannote[85].speaker SPEAKER_03
transcript.pyannote[85].start 344.51721875
transcript.pyannote[85].end 344.93909375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 344.93909375
transcript.pyannote[86].end 345.96846875
transcript.pyannote[87].speaker SPEAKER_03
transcript.pyannote[87].start 345.42846875
transcript.pyannote[87].end 345.44534375
transcript.pyannote[88].speaker SPEAKER_03
transcript.pyannote[88].start 345.74909375
transcript.pyannote[88].end 357.39284375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 358.74284375
transcript.pyannote[89].end 363.04596875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 363.24846875
transcript.pyannote[90].end 368.20971875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 368.22659375
transcript.pyannote[91].end 368.32784375
transcript.pyannote[92].speaker SPEAKER_03
transcript.pyannote[92].start 368.32784375
transcript.pyannote[92].end 368.42909375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 368.42909375
transcript.pyannote[93].end 371.06159375
transcript.pyannote[94].speaker SPEAKER_03
transcript.pyannote[94].start 368.46284375
transcript.pyannote[94].end 368.59784375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 371.07846875
transcript.pyannote[95].end 371.12909375
transcript.pyannote[96].speaker SPEAKER_03
transcript.pyannote[96].start 371.12909375
transcript.pyannote[96].end 373.00221875
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 373.23846875
transcript.pyannote[97].end 374.36909375
transcript.pyannote[98].speaker SPEAKER_03
transcript.pyannote[98].start 373.82909375
transcript.pyannote[98].end 374.84159375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 374.99346875
transcript.pyannote[99].end 376.84971875
transcript.pyannote[100].speaker SPEAKER_03
transcript.pyannote[100].start 376.44471875
transcript.pyannote[100].end 376.61346875
transcript.pyannote[101].speaker SPEAKER_03
transcript.pyannote[101].start 376.64721875
transcript.pyannote[101].end 381.03471875
transcript.pyannote[102].speaker SPEAKER_03
transcript.pyannote[102].start 381.45659375
transcript.pyannote[102].end 396.40784375
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 396.40784375
transcript.pyannote[103].end 399.61409375
transcript.pyannote[104].speaker SPEAKER_03
transcript.pyannote[104].start 396.42471875
transcript.pyannote[104].end 396.49221875
transcript.pyannote[105].speaker SPEAKER_03
transcript.pyannote[105].start 396.57659375
transcript.pyannote[105].end 397.08284375
transcript.pyannote[106].speaker SPEAKER_03
transcript.pyannote[106].start 399.12471875
transcript.pyannote[106].end 404.05221875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 403.24221875
transcript.pyannote[107].end 408.92909375
transcript.pyannote[108].speaker SPEAKER_03
transcript.pyannote[108].start 408.64221875
transcript.pyannote[108].end 412.79346875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 408.99659375
transcript.pyannote[109].end 409.09784375
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 412.23659375
transcript.pyannote[110].end 413.90721875
transcript.pyannote[111].speaker SPEAKER_03
transcript.pyannote[111].start 414.00846875
transcript.pyannote[111].end 416.67471875
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 416.11784375
transcript.pyannote[112].end 422.98596875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 423.17159375
transcript.pyannote[113].end 426.59721875
transcript.pyannote[114].speaker SPEAKER_03
transcript.pyannote[114].start 426.74909375
transcript.pyannote[114].end 428.84159375
transcript.pyannote[115].speaker SPEAKER_03
transcript.pyannote[115].start 429.36471875
transcript.pyannote[115].end 441.19409375
transcript.pyannote[116].speaker SPEAKER_03
transcript.pyannote[116].start 441.98721875
transcript.pyannote[116].end 471.68721875
transcript.pyannote[117].speaker SPEAKER_03
transcript.pyannote[117].start 472.56471875
transcript.pyannote[117].end 475.19721875
transcript.pyannote[118].speaker SPEAKER_03
transcript.pyannote[118].start 475.60221875
transcript.pyannote[118].end 481.71096875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 483.80346875
transcript.pyannote[119].end 490.63784375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 491.00909375
transcript.pyannote[120].end 492.22409375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 492.37596875
transcript.pyannote[121].end 496.62846875
transcript.pyannote[122].speaker SPEAKER_03
transcript.pyannote[122].start 494.72159375
transcript.pyannote[122].end 511.59659375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 507.12471875
transcript.pyannote[123].end 508.74471875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 510.39846875
transcript.pyannote[124].end 516.13596875
transcript.pyannote[125].speaker SPEAKER_03
transcript.pyannote[125].start 513.45284375
transcript.pyannote[125].end 514.06034375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 516.55784375
transcript.pyannote[126].end 519.44346875
transcript.pyannote[127].speaker SPEAKER_03
transcript.pyannote[127].start 518.44784375
transcript.pyannote[127].end 518.97096875
transcript.pyannote[128].speaker SPEAKER_03
transcript.pyannote[128].start 519.44346875
transcript.pyannote[128].end 525.72096875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 525.85596875
transcript.pyannote[129].end 526.02471875
transcript.pyannote[130].speaker SPEAKER_03
transcript.pyannote[130].start 526.02471875
transcript.pyannote[130].end 530.49659375
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 526.05846875
transcript.pyannote[131].end 526.24409375
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 530.95221875
transcript.pyannote[132].end 538.63034375
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 539.05221875
transcript.pyannote[133].end 542.66346875
transcript.pyannote[134].speaker SPEAKER_03
transcript.pyannote[134].start 541.04346875
transcript.pyannote[134].end 541.46534375
transcript.pyannote[135].speaker SPEAKER_03
transcript.pyannote[135].start 542.66346875
transcript.pyannote[135].end 548.33346875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 547.94534375
transcript.pyannote[136].end 560.39909375
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 560.93909375
transcript.pyannote[137].end 561.20909375
transcript.pyannote[138].speaker SPEAKER_03
transcript.pyannote[138].start 561.20909375
transcript.pyannote[138].end 561.24284375
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 561.24284375
transcript.pyannote[139].end 562.03596875
transcript.pyannote[140].speaker SPEAKER_03
transcript.pyannote[140].start 562.03596875
transcript.pyannote[140].end 563.52096875
transcript.pyannote[141].speaker SPEAKER_03
transcript.pyannote[141].start 564.04409375
transcript.pyannote[141].end 565.02284375
transcript.pyannote[142].speaker SPEAKER_03
transcript.pyannote[142].start 565.64721875
transcript.pyannote[142].end 570.89534375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 571.18221875
transcript.pyannote[143].end 581.29034375
transcript.pyannote[144].speaker SPEAKER_03
transcript.pyannote[144].start 579.85596875
transcript.pyannote[144].end 580.63221875
transcript.pyannote[145].speaker SPEAKER_03
transcript.pyannote[145].start 580.93596875
transcript.pyannote[145].end 584.32784375
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 585.23909375
transcript.pyannote[146].end 586.30221875
transcript.pyannote[147].speaker SPEAKER_03
transcript.pyannote[147].start 586.30221875
transcript.pyannote[147].end 586.43721875
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 587.56784375
transcript.pyannote[148].end 587.58471875
transcript.pyannote[149].speaker SPEAKER_03
transcript.pyannote[149].start 587.58471875
transcript.pyannote[149].end 588.58034375
transcript.pyannote[150].speaker SPEAKER_03
transcript.pyannote[150].start 589.55909375
transcript.pyannote[150].end 595.48221875
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 596.57909375
transcript.pyannote[151].end 606.33284375
transcript.pyannote[152].speaker SPEAKER_03
transcript.pyannote[152].start 606.07971875
transcript.pyannote[152].end 608.56034375
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 609.67409375
transcript.pyannote[153].end 612.03659375
transcript.pyannote[154].speaker SPEAKER_03
transcript.pyannote[154].start 612.86346875
transcript.pyannote[154].end 617.04846875
transcript.pyannote[155].speaker SPEAKER_03
transcript.pyannote[155].start 617.77409375
transcript.pyannote[155].end 620.54159375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 617.90909375
transcript.pyannote[156].end 619.63034375
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 619.93409375
transcript.pyannote[157].end 621.11534375
transcript.pyannote[158].speaker SPEAKER_03
transcript.pyannote[158].start 621.53721875
transcript.pyannote[158].end 624.64221875
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 625.03034375
transcript.pyannote[159].end 637.21409375
transcript.pyannote[160].speaker SPEAKER_03
transcript.pyannote[160].start 637.24784375
transcript.pyannote[160].end 637.53471875
transcript.pyannote[161].speaker SPEAKER_02
transcript.pyannote[161].start 637.53471875
transcript.pyannote[161].end 639.03659375
transcript.pyannote[162].speaker SPEAKER_03
transcript.pyannote[162].start 639.03659375
transcript.pyannote[162].end 639.94784375
transcript.pyannote[163].speaker SPEAKER_03
transcript.pyannote[163].start 640.15034375
transcript.pyannote[163].end 658.45971875
transcript.pyannote[164].speaker SPEAKER_03
transcript.pyannote[164].start 658.72971875
transcript.pyannote[164].end 663.21846875
transcript.pyannote[165].speaker SPEAKER_03
transcript.pyannote[165].start 663.25221875
transcript.pyannote[165].end 663.85971875
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 664.83846875
transcript.pyannote[166].end 684.29534375
transcript.pyannote[167].speaker SPEAKER_03
transcript.pyannote[167].start 685.84784375
transcript.pyannote[167].end 687.99096875
transcript.pyannote[168].speaker SPEAKER_03
transcript.pyannote[168].start 689.96534375
transcript.pyannote[168].end 691.07909375
transcript.whisperx[0].start 8.729
transcript.whisperx[0].end 21.172
transcript.whisperx[0].text 好 謝謝主席給龔部長喝一口水好 我們請楊代表 龔部長還有我們國發會的葉主委好 我們請三位 謝謝各位早安謝委員好
transcript.whisperx[1].start 31.889
transcript.whisperx[1].end 53.359
transcript.whisperx[1].text 我們卓院長他已經證實了台美目前在交換文件的這個階段了那我們知道國人都在意的是我們有沒有比日本韓國更好的條件那日本韓國他們分別都已經承諾投資5500億跟3500億那台灣到底投資多少
transcript.whisperx[2].start 58.976
transcript.whisperx[2].end 87.265
transcript.whisperx[2].text 是有什么具体的数字可以跟国人报告一下吗杨代表报告委员我想日本跟韩国跟我们的情形不一样我们的投资模式是依照我们的经济发展产业结构跟业者的需求所定出来的至于金额的部分因为还在议定当中也不便细节对外宣布所以是不是要把我们科学园区
transcript.whisperx[3].start 88.445
transcript.whisperx[3].end 103.725
transcript.whisperx[3].text 整個在美國再複製一個是這個概念嗎那如果這樣子的話除了台積電有多少的科學園區的廠商也要共同到美國去投資
transcript.whisperx[4].start 105.253
transcript.whisperx[4].end 126.9
transcript.whisperx[4].text 報告委員 我們是說我們的內科學園區的經驗跟美國來交換意見協助我們的業者在當地能夠設立產業園區或是產業記錄不是把我們的科學園區搬到美國去我覺得這一部分跟委員做一個澄清那如果台積電去 整個供應鏈要不要去 部長
transcript.whisperx[5].start 128.117
transcript.whisperx[5].end 154.179
transcript.whisperx[5].text 沒有啊 現在台積電的這個亞利桑那廠已經開始量產但是供應鏈還是沒有去啊很多都去了 很多都去了而且現在預估到美國投資的台灣廠商科技業而言就要他的對美的投資建一個廠比台灣的投資是要增加五到七倍喔
transcript.whisperx[6].start 155.981
transcript.whisperx[6].end 184.501
transcript.whisperx[6].text 這個數字你們有沒有掌握應該沒有那麼高沒有 你們掌握的沒那麼高是不是你們覺得沒有那麼高是不是那因為美國的生產的條件以及法令的這個跟台灣是有非常大的差異以及他們如何跟美國建立這樣子的一個就是說相關的能夠在台灣就是說有這樣相關的法令的
transcript.whisperx[7].start 185.241
transcript.whisperx[7].end 197.167
transcript.whisperx[7].text 這個可及性在美國並沒有啊是不是這也就是為什麼我們要居獨居就是說台灣政府跟美國政府要有一個比較好的溝通沒有5到7倍 幾倍
transcript.whisperx[8].start 199.229
transcript.whisperx[8].end 226.124
transcript.whisperx[8].text 那這個是企業界的這個營業的秘密這個要台積電來說明啦我們不方便這個是他業者的秘密啦所以現在投資的金額還沒有確定嗎投資的金額你說台積電嗎不是 楊代表楊代表有答案啦
transcript.whisperx[9].start 227.352
transcript.whisperx[9].end 241.882
transcript.whisperx[9].text 報告委員我剛剛已經說明了我們現在的投資金額尚未議定在談判前不便對外說明因為我們要爭取對我業者最有利的條件所以還沒有確定還沒有確定那是不是
transcript.whisperx[10].start 242.702
transcript.whisperx[10].end 265.675
transcript.whisperx[10].text 要以我們整個產硬鏈到美國去增加他們半導體的產出那請問我們是不是變成要幫美國的企業來培養就是他們的就是勞力勞動力在半導體相關製造的勞動力是不是這是不是談的條件之一
transcript.whisperx[11].start 266.935
transcript.whisperx[11].end 289.783
transcript.whisperx[11].text 報告委員我們沒有答應美國說要幫他訓練技術人員我想業者他們在做投資的時候依照他們的需求但是但是美國如果要求台灣的企業到赴美投資的時候他其實有要求我們要用當地的勞動力是不是多大比例
transcript.whisperx[12].start 293.696
transcript.whisperx[12].end 311.423
transcript.whisperx[12].text 沒有談這個但是從對外投資來講當然要用當地的勞工那我們是不是以這樣子就是對於美國半導體製造業技術人力的訓練代替了巨額的資金投入
transcript.whisperx[13].start 312.874
transcript.whisperx[13].end 339.263
transcript.whisperx[13].text 因為你一個廠在那邊 會不會一個廠在那邊要運作基本的這個人力上的這個基本條件還是要存在啊要不然他的廠沒有辦法運作啊 對所以他們本身台積電就會有一些職能訓練但是現在目前就是說在建廠階段他仰賴的是我們台灣的就是說台積電的員工赴美去建廠那甚至開始投入量產嘛
transcript.whisperx[14].start 340.283
transcript.whisperx[14].end 357.182
transcript.whisperx[14].text 那很多建廠的人員已經回來了有一些已經回來了部分啦部分啦那還是最大部分還是仰賴台灣的嗎那他們現在希望說我們能夠訓練這個相關的部分嗎那個葉主委知不知道
transcript.whisperx[15].start 359.026
transcript.whisperx[15].end 374.574
transcript.whisperx[15].text 這個部分的話就台積電自己本身他會有自己的判斷因為畢竟就是說他整個廠在那邊營運的話那到底要怎樣去做人力的安排然後是不是有一些員工要送回來台灣那他們要求多大的比例在地員工
transcript.whisperx[16].start 376.194
transcript.whisperx[16].end 396.062
transcript.whisperx[16].text 所以如果我們不是超越美超越日韓這樣子的投資金額是不是以我們目前來訓練當地的半導體生產的技術人員那來成為我們關稅談判的一個條件之一呢
transcript.whisperx[17].start 397.762
transcript.whisperx[17].end 413.668
transcript.whisperx[17].text 這個應該不會是談判條件兩代表都沒說你們兩個怎麼就在前面講報告委員他都是我們在副院長領導之下最好的談判夥伴所以他們兩個講的代表你們談判的內容嗎我們都一起的
transcript.whisperx[18].start 414.108
transcript.whisperx[18].end 440.616
transcript.whisperx[18].text 所以代表你們談判內容嗎是不是他們剛剛已經表述了這個金額議定而且並沒有說訓練他的勞工室談判關稅減讓的一部分我們現在沒有談到這些好那我再問工部長就是目前我們對於關稅衝擊的這個四大措施就是外銷貸款的保證就是說保證加碼
transcript.whisperx[19].start 442.031
transcript.whisperx[19].end 456.921
transcript.whisperx[19].text 那我發現加碼的荷寶只有10.8億還有中小微企業發展貸款加碼身貸是628件61.4億研發轉型865件那爭取海外訂單549件代表了我們過去認為因應關稅衝擊就是說創造出來的這些方案
transcript.whisperx[20].start 472.612
transcript.whisperx[20].end 481.52
transcript.whisperx[20].text 目前為止 好像效率 成數都不高是不是 那是不是代表我們這些方案的作用呢
transcript.whisperx[21].start 484.857
transcript.whisperx[21].end 509.622
transcript.whisperx[21].text 這樣加起來有兩千多件還是有很多那我們還是要加強宣導因為有些企業可能沒有收到這樣的訊息那所以我們為什麼要因為我們給他四百六十億的特別預算的貸款身貸額度那是四百六十億喔那他其實身貸的還沒有含就是說已經合則的身貸只有六十一億
transcript.whisperx[22].start 511.583
transcript.whisperx[22].end 529.777
transcript.whisperx[22].text 這個執行期間要兩年多所以還有很多的時間可能需要直接經費不是要一次就用完我再問一下楊代表一個事情好不好楊代表我們關稅什麼時候可以抵定啊你知道嗎財政部的出口數字都沒有辦法算
transcript.whisperx[23].start 531.344
transcript.whisperx[23].end 559.939
transcript.whisperx[23].text 報告委員剛剛已經講了我們如果對等二向澳這個供應鏈一談妥的話對等的貴稅率我們一定要調降而且不疊加我們會緊述的依照國人的所以我們期待的是232跟對等關稅一起談嗎是不是這個剛剛我在報告裡面有講美國的我的產業的結構非常特殊是因為半導體還有電子產品造成最大的逆差所以這是兩個協定是一起談的
transcript.whisperx[24].start 561.019
transcript.whisperx[24].end 586.226
transcript.whisperx[24].text 那一起談的情況下對於未來關稅可能下降的這樣的機率有多大你說一下我想政府院長您對領導的團隊有信心我們一定要爭取往下對等條件而且要不疊加這對我們業者才有機率啊楊代表我問一下嘛機率有多高機率非常的高
transcript.whisperx[25].start 587.588
transcript.whisperx[25].end 608.332
transcript.whisperx[25].text 那70% 80%還是90%還是低於70%四個答案嘛 選擇題我想那個底線談判沒有經過核定的話我們不能講到100%但是這是我們最大的期盼我們也有很高的信心可以爭取到那是70% 80%還是90%我還是不做這個比率的評斷機率啊 機率啊 這不是那個機率吧
transcript.whisperx[26].start 617.833
transcript.whisperx[26].end 624.379
transcript.whisperx[26].text 我沒有說妳會百分之百嘛基因非常的高那是多少啊70%以上還是以下
transcript.whisperx[27].start 625.376
transcript.whisperx[27].end 647.473
transcript.whisperx[27].text 我們一定要爭取二三奧供應鏈最好的稅率之下我們才會結束這個談判所以這個談判一結束對等也會調降這是我們最大的期盼機率還是非常的高你都沒有講我跟你講現在全台灣所有的製造業所有的高科技所有都在等你們
transcript.whisperx[28].start 649.655
transcript.whisperx[28].end 663.552
transcript.whisperx[28].text 連財政部政府部門所有明年的稅收預估的數字都沒有辦法出來耶因為不知道明年的出口如何啊是不是但在這個情況下你總要透露給大家一點點那個吧是不是
transcript.whisperx[29].start 665.138
transcript.whisperx[29].end 684.108
transcript.whisperx[29].text 報告委員我還是要講機率真的非常高這是我們努力的一個目標因為任何一個協定沒有談完之後細項一公佈之後可能會影響到我們最好的結果所以我會跟委員報告我們會努力而且機率非常非常的高好 謝謝好 謝謝謝一鋒委員 謝謝我們接下來請