iVOD / 160727

Field Value
IVOD_ID 160727
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/160727
日期 2025-04-29
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 2025-04-29T11:35:09+08:00
結束時間 2025-04-29T11:51:10+08:00
影片長度 00:16:01
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/5e3950a5df8d034b6bea219985619159066821ab1e45083e6de342268043fcb60911e5930497b7265ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 吳秉叡
委員發言時間 11:35:09 - 11:51:10
會議時間 2025-04-29T09:00:00+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_01
transcript.pyannote[0].start 9.14346875
transcript.pyannote[0].end 12.83909375
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 13.29471875
transcript.pyannote[1].end 14.76284375
transcript.pyannote[2].speaker SPEAKER_03
transcript.pyannote[2].start 24.26346875
transcript.pyannote[2].end 24.82034375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 25.03971875
transcript.pyannote[3].end 25.81596875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 26.42346875
transcript.pyannote[4].end 27.99284375
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 28.31346875
transcript.pyannote[5].end 30.22034375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 30.37221875
transcript.pyannote[6].end 31.14846875
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 32.21159375
transcript.pyannote[7].end 35.19846875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 36.83534375
transcript.pyannote[8].end 37.20659375
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 37.83096875
transcript.pyannote[9].end 40.86846875
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 41.79659375
transcript.pyannote[10].end 42.30284375
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 43.48409375
transcript.pyannote[11].end 45.20534375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 45.96471875
transcript.pyannote[12].end 49.17096875
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 49.62659375
transcript.pyannote[13].end 53.94659375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 54.33471875
transcript.pyannote[14].end 55.76909375
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 56.51159375
transcript.pyannote[15].end 59.39721875
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 60.10596875
transcript.pyannote[16].end 64.52721875
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 64.83096875
transcript.pyannote[17].end 66.95721875
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 67.34534375
transcript.pyannote[18].end 68.98221875
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 69.62346875
transcript.pyannote[19].end 70.04534375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 71.61471875
transcript.pyannote[20].end 74.06159375
transcript.pyannote[21].speaker SPEAKER_03
transcript.pyannote[21].start 75.47909375
transcript.pyannote[21].end 80.08596875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 79.61346875
transcript.pyannote[22].end 85.14846875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 85.35096875
transcript.pyannote[23].end 86.26221875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 86.58284375
transcript.pyannote[24].end 87.46034375
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 87.49409375
transcript.pyannote[25].end 90.04221875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 90.61596875
transcript.pyannote[26].end 99.07034375
transcript.pyannote[27].speaker SPEAKER_03
transcript.pyannote[27].start 98.98596875
transcript.pyannote[27].end 100.96034375
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 102.39471875
transcript.pyannote[28].end 103.84596875
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 104.41971875
transcript.pyannote[29].end 105.46596875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 106.42784375
transcript.pyannote[30].end 107.57534375
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 108.30096875
transcript.pyannote[31].end 109.88721875
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 110.34284375
transcript.pyannote[32].end 112.55346875
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 113.19471875
transcript.pyannote[33].end 117.02534375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 117.51471875
transcript.pyannote[34].end 119.89409375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 119.92784375
transcript.pyannote[35].end 120.02909375
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 120.07971875
transcript.pyannote[36].end 121.21034375
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 121.88534375
transcript.pyannote[37].end 123.65721875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 124.29846875
transcript.pyannote[38].end 126.05346875
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 126.67784375
transcript.pyannote[39].end 128.19659375
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 128.68596875
transcript.pyannote[40].end 129.76596875
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 130.37346875
transcript.pyannote[41].end 131.26784375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 131.48721875
transcript.pyannote[42].end 132.33096875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 132.82034375
transcript.pyannote[43].end 135.04784375
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 135.35159375
transcript.pyannote[44].end 136.60034375
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 136.66784375
transcript.pyannote[45].end 144.46409375
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 145.08846875
transcript.pyannote[46].end 146.97846875
transcript.pyannote[47].speaker SPEAKER_03
transcript.pyannote[47].start 146.45534375
transcript.pyannote[47].end 155.39909375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 155.78721875
transcript.pyannote[48].end 165.57471875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 166.36784375
transcript.pyannote[49].end 182.07846875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 182.50034375
transcript.pyannote[50].end 187.02284375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 188.17034375
transcript.pyannote[51].end 189.35159375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 189.85784375
transcript.pyannote[52].end 191.73096875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 192.08534375
transcript.pyannote[53].end 194.86971875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 195.20721875
transcript.pyannote[54].end 197.89034375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 198.22784375
transcript.pyannote[55].end 198.68346875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 199.74659375
transcript.pyannote[56].end 204.84284375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 204.89346875
transcript.pyannote[57].end 212.63909375
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 211.30596875
transcript.pyannote[58].end 214.32659375
transcript.pyannote[59].speaker SPEAKER_03
transcript.pyannote[59].start 214.39409375
transcript.pyannote[59].end 216.04784375
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 216.09846875
transcript.pyannote[60].end 217.56659375
transcript.pyannote[61].speaker SPEAKER_03
transcript.pyannote[61].start 217.87034375
transcript.pyannote[61].end 223.55721875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 223.55721875
transcript.pyannote[62].end 223.84409375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 224.13096875
transcript.pyannote[63].end 226.34159375
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 226.66221875
transcript.pyannote[64].end 229.05846875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 229.68284375
transcript.pyannote[65].end 239.01471875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 239.63909375
transcript.pyannote[66].end 241.73159375
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 242.22096875
transcript.pyannote[67].end 244.51596875
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 245.19096875
transcript.pyannote[68].end 245.52846875
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 246.55784375
transcript.pyannote[69].end 247.01346875
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 247.16534375
transcript.pyannote[70].end 247.85721875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 248.34659375
transcript.pyannote[71].end 249.78096875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 250.54034375
transcript.pyannote[72].end 251.83971875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 252.00846875
transcript.pyannote[73].end 254.11784375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 254.74221875
transcript.pyannote[74].end 257.86409375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 259.02846875
transcript.pyannote[75].end 261.03659375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 261.72846875
transcript.pyannote[76].end 267.93846875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 268.49534375
transcript.pyannote[77].end 270.01409375
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 270.41909375
transcript.pyannote[78].end 272.35971875
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 273.38909375
transcript.pyannote[79].end 274.84034375
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 275.54909375
transcript.pyannote[80].end 276.27471875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 276.54471875
transcript.pyannote[81].end 277.43909375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 278.78909375
transcript.pyannote[82].end 279.37971875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 279.83534375
transcript.pyannote[83].end 281.18534375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 281.57346875
transcript.pyannote[84].end 282.40034375
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 282.53534375
transcript.pyannote[85].end 285.10034375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 285.72471875
transcript.pyannote[86].end 288.72846875
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 289.40346875
transcript.pyannote[87].end 290.29784375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 290.66909375
transcript.pyannote[88].end 291.71534375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 292.79534375
transcript.pyannote[89].end 295.25909375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 295.86659375
transcript.pyannote[90].end 298.63409375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 299.96721875
transcript.pyannote[91].end 305.68784375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 306.71721875
transcript.pyannote[92].end 314.54721875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 315.42471875
transcript.pyannote[93].end 318.19221875
transcript.pyannote[94].speaker SPEAKER_03
transcript.pyannote[94].start 318.46221875
transcript.pyannote[94].end 323.76096875
transcript.pyannote[95].speaker SPEAKER_03
transcript.pyannote[95].start 324.08159375
transcript.pyannote[95].end 325.09409375
transcript.pyannote[96].speaker SPEAKER_03
transcript.pyannote[96].start 325.31346875
transcript.pyannote[96].end 327.25409375
transcript.pyannote[97].speaker SPEAKER_03
transcript.pyannote[97].start 327.55784375
transcript.pyannote[97].end 330.13971875
transcript.pyannote[98].speaker SPEAKER_03
transcript.pyannote[98].start 330.76409375
transcript.pyannote[98].end 332.92409375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 333.93659375
transcript.pyannote[99].end 340.61909375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 341.00721875
transcript.pyannote[100].end 342.23909375
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 343.04909375
transcript.pyannote[101].end 355.48596875
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 351.38534375
transcript.pyannote[102].end 351.82409375
transcript.pyannote[103].speaker SPEAKER_03
transcript.pyannote[103].start 351.82409375
transcript.pyannote[103].end 351.85784375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 351.85784375
transcript.pyannote[104].end 351.89159375
transcript.pyannote[105].speaker SPEAKER_03
transcript.pyannote[105].start 351.89159375
transcript.pyannote[105].end 352.19534375
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 352.19534375
transcript.pyannote[106].end 352.29659375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 356.00909375
transcript.pyannote[107].end 359.46846875
transcript.pyannote[108].speaker SPEAKER_03
transcript.pyannote[108].start 359.46846875
transcript.pyannote[108].end 360.07596875
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 360.24471875
transcript.pyannote[109].end 369.17159375
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 369.12096875
transcript.pyannote[110].end 369.15471875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 369.17159375
transcript.pyannote[111].end 372.61409375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 372.04034375
transcript.pyannote[112].end 377.65971875
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 377.96346875
transcript.pyannote[113].end 401.79096875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 400.18784375
transcript.pyannote[114].end 400.76159375
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 401.80784375
transcript.pyannote[115].end 401.82471875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 401.82471875
transcript.pyannote[116].end 408.11909375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 403.56284375
transcript.pyannote[117].end 404.60909375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 408.37221875
transcript.pyannote[118].end 409.41846875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 409.53659375
transcript.pyannote[119].end 413.72159375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 413.82284375
transcript.pyannote[120].end 415.15596875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 415.98284375
transcript.pyannote[121].end 418.10909375
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 418.37909375
transcript.pyannote[122].end 419.81346875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 420.65721875
transcript.pyannote[123].end 423.18846875
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 424.31909375
transcript.pyannote[124].end 424.45409375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 424.45409375
transcript.pyannote[125].end 428.48721875
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 429.43221875
transcript.pyannote[126].end 434.03909375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 434.39346875
transcript.pyannote[127].end 437.02596875
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 437.38034375
transcript.pyannote[128].end 438.56159375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 439.20284375
transcript.pyannote[129].end 448.26471875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 448.85534375
transcript.pyannote[130].end 451.06596875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 451.96034375
transcript.pyannote[131].end 452.73659375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 453.39471875
transcript.pyannote[132].end 456.39846875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 456.78659375
transcript.pyannote[133].end 460.98846875
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 461.39346875
transcript.pyannote[134].end 482.57159375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 482.57159375
transcript.pyannote[135].end 492.34221875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 493.62471875
transcript.pyannote[136].end 500.44221875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 501.04971875
transcript.pyannote[137].end 504.88034375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 505.45409375
transcript.pyannote[138].end 509.85846875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 510.93846875
transcript.pyannote[139].end 516.77721875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 517.65471875
transcript.pyannote[140].end 519.84846875
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 520.50659375
transcript.pyannote[141].end 529.43346875
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 530.32784375
transcript.pyannote[142].end 540.23346875
transcript.pyannote[143].speaker SPEAKER_03
transcript.pyannote[143].start 540.63846875
transcript.pyannote[143].end 543.65909375
transcript.pyannote[144].speaker SPEAKER_03
transcript.pyannote[144].start 544.08096875
transcript.pyannote[144].end 547.13534375
transcript.pyannote[145].speaker SPEAKER_03
transcript.pyannote[145].start 547.32096875
transcript.pyannote[145].end 549.36284375
transcript.pyannote[146].speaker SPEAKER_03
transcript.pyannote[146].start 549.70034375
transcript.pyannote[146].end 552.34971875
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 550.76346875
transcript.pyannote[147].end 551.53971875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 551.70846875
transcript.pyannote[148].end 554.96534375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 555.47159375
transcript.pyannote[149].end 564.43221875
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 564.63471875
transcript.pyannote[150].end 567.50346875
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 568.61721875
transcript.pyannote[151].end 571.16534375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 571.60409375
transcript.pyannote[152].end 573.76409375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 574.62471875
transcript.pyannote[153].end 575.21534375
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 576.37971875
transcript.pyannote[154].end 578.30346875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 578.47221875
transcript.pyannote[155].end 579.11346875
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 579.97409375
transcript.pyannote[156].end 580.81784375
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 581.59409375
transcript.pyannote[157].end 583.63596875
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 584.04096875
transcript.pyannote[158].end 585.12096875
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 585.47534375
transcript.pyannote[159].end 587.28096875
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 587.61846875
transcript.pyannote[160].end 588.49596875
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 589.28909375
transcript.pyannote[161].end 590.47034375
transcript.pyannote[162].speaker SPEAKER_01
transcript.pyannote[162].start 590.90909375
transcript.pyannote[162].end 592.78221875
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 593.57534375
transcript.pyannote[163].end 593.92971875
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 594.19971875
transcript.pyannote[164].end 595.00971875
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 595.26284375
transcript.pyannote[165].end 596.59596875
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 597.00096875
transcript.pyannote[166].end 598.99221875
transcript.pyannote[167].speaker SPEAKER_01
transcript.pyannote[167].start 599.71784375
transcript.pyannote[167].end 601.28721875
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 601.60784375
transcript.pyannote[168].end 603.95346875
transcript.pyannote[169].speaker SPEAKER_01
transcript.pyannote[169].start 604.40909375
transcript.pyannote[169].end 605.62409375
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 605.94471875
transcript.pyannote[170].end 611.00721875
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 611.26034375
transcript.pyannote[171].end 612.91409375
transcript.pyannote[172].speaker SPEAKER_03
transcript.pyannote[172].start 613.18409375
transcript.pyannote[172].end 615.04034375
transcript.pyannote[173].speaker SPEAKER_01
transcript.pyannote[173].start 615.36096875
transcript.pyannote[173].end 617.82471875
transcript.pyannote[174].speaker SPEAKER_01
transcript.pyannote[174].start 618.16221875
transcript.pyannote[174].end 647.59221875
transcript.pyannote[175].speaker SPEAKER_01
transcript.pyannote[175].start 648.41909375
transcript.pyannote[175].end 653.09346875
transcript.pyannote[176].speaker SPEAKER_03
transcript.pyannote[176].start 653.21159375
transcript.pyannote[176].end 657.12659375
transcript.pyannote[177].speaker SPEAKER_03
transcript.pyannote[177].start 657.22784375
transcript.pyannote[177].end 658.25721875
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 658.25721875
transcript.pyannote[178].end 670.81221875
transcript.pyannote[179].speaker SPEAKER_03
transcript.pyannote[179].start 661.78409375
transcript.pyannote[179].end 663.92721875
transcript.pyannote[180].speaker SPEAKER_03
transcript.pyannote[180].start 668.90534375
transcript.pyannote[180].end 677.49471875
transcript.pyannote[181].speaker SPEAKER_01
transcript.pyannote[181].start 678.76034375
transcript.pyannote[181].end 686.48909375
transcript.pyannote[182].speaker SPEAKER_01
transcript.pyannote[182].start 687.60284375
transcript.pyannote[182].end 688.90221875
transcript.pyannote[183].speaker SPEAKER_01
transcript.pyannote[183].start 689.29034375
transcript.pyannote[183].end 690.28596875
transcript.pyannote[184].speaker SPEAKER_01
transcript.pyannote[184].start 690.87659375
transcript.pyannote[184].end 692.31096875
transcript.pyannote[185].speaker SPEAKER_01
transcript.pyannote[185].start 692.81721875
transcript.pyannote[185].end 693.54284375
transcript.pyannote[186].speaker SPEAKER_01
transcript.pyannote[186].start 693.86346875
transcript.pyannote[186].end 695.06159375
transcript.pyannote[187].speaker SPEAKER_01
transcript.pyannote[187].start 695.26409375
transcript.pyannote[187].end 696.64784375
transcript.pyannote[188].speaker SPEAKER_00
transcript.pyannote[188].start 695.63534375
transcript.pyannote[188].end 695.75346875
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 695.80409375
transcript.pyannote[189].end 695.93909375
transcript.pyannote[190].speaker SPEAKER_00
transcript.pyannote[190].start 696.12471875
transcript.pyannote[190].end 702.87471875
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 703.17846875
transcript.pyannote[191].end 703.49909375
transcript.pyannote[192].speaker SPEAKER_01
transcript.pyannote[192].start 703.75221875
transcript.pyannote[192].end 705.32159375
transcript.pyannote[193].speaker SPEAKER_01
transcript.pyannote[193].start 706.75596875
transcript.pyannote[193].end 710.11409375
transcript.pyannote[194].speaker SPEAKER_01
transcript.pyannote[194].start 710.70471875
transcript.pyannote[194].end 711.71721875
transcript.pyannote[195].speaker SPEAKER_01
transcript.pyannote[195].start 712.20659375
transcript.pyannote[195].end 713.35409375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 714.09659375
transcript.pyannote[196].end 715.17659375
transcript.pyannote[197].speaker SPEAKER_01
transcript.pyannote[197].start 715.54784375
transcript.pyannote[197].end 716.13846875
transcript.pyannote[198].speaker SPEAKER_01
transcript.pyannote[198].start 717.10034375
transcript.pyannote[198].end 718.45034375
transcript.pyannote[199].speaker SPEAKER_01
transcript.pyannote[199].start 718.97346875
transcript.pyannote[199].end 720.17159375
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 720.62721875
transcript.pyannote[200].end 723.49596875
transcript.pyannote[201].speaker SPEAKER_01
transcript.pyannote[201].start 723.59721875
transcript.pyannote[201].end 726.90471875
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 727.64721875
transcript.pyannote[202].end 733.24971875
transcript.pyannote[203].speaker SPEAKER_01
transcript.pyannote[203].start 733.43534375
transcript.pyannote[203].end 735.84846875
transcript.pyannote[204].speaker SPEAKER_01
transcript.pyannote[204].start 736.82721875
transcript.pyannote[204].end 737.60346875
transcript.pyannote[205].speaker SPEAKER_01
transcript.pyannote[205].start 738.32909375
transcript.pyannote[205].end 745.88909375
transcript.pyannote[206].speaker SPEAKER_01
transcript.pyannote[206].start 746.39534375
transcript.pyannote[206].end 747.99846875
transcript.pyannote[207].speaker SPEAKER_01
transcript.pyannote[207].start 748.60596875
transcript.pyannote[207].end 750.63096875
transcript.pyannote[208].speaker SPEAKER_01
transcript.pyannote[208].start 750.85034375
transcript.pyannote[208].end 756.85784375
transcript.pyannote[209].speaker SPEAKER_02
transcript.pyannote[209].start 757.11096875
transcript.pyannote[209].end 757.78596875
transcript.pyannote[210].speaker SPEAKER_01
transcript.pyannote[210].start 757.48221875
transcript.pyannote[210].end 761.07659375
transcript.pyannote[211].speaker SPEAKER_02
transcript.pyannote[211].start 760.31721875
transcript.pyannote[211].end 760.53659375
transcript.pyannote[212].speaker SPEAKER_02
transcript.pyannote[212].start 761.07659375
transcript.pyannote[212].end 766.15596875
transcript.pyannote[213].speaker SPEAKER_02
transcript.pyannote[213].start 766.56096875
transcript.pyannote[213].end 770.57721875
transcript.pyannote[214].speaker SPEAKER_02
transcript.pyannote[214].start 770.74596875
transcript.pyannote[214].end 771.28596875
transcript.pyannote[215].speaker SPEAKER_02
transcript.pyannote[215].start 771.70784375
transcript.pyannote[215].end 775.11659375
transcript.pyannote[216].speaker SPEAKER_02
transcript.pyannote[216].start 775.53846875
transcript.pyannote[216].end 779.20034375
transcript.pyannote[217].speaker SPEAKER_02
transcript.pyannote[217].start 779.33534375
transcript.pyannote[217].end 783.70596875
transcript.pyannote[218].speaker SPEAKER_01
transcript.pyannote[218].start 782.82846875
transcript.pyannote[218].end 785.44409375
transcript.pyannote[219].speaker SPEAKER_02
transcript.pyannote[219].start 785.44409375
transcript.pyannote[219].end 793.39221875
transcript.pyannote[220].speaker SPEAKER_02
transcript.pyannote[220].start 793.62846875
transcript.pyannote[220].end 797.93159375
transcript.pyannote[221].speaker SPEAKER_02
transcript.pyannote[221].start 798.04971875
transcript.pyannote[221].end 803.75346875
transcript.pyannote[222].speaker SPEAKER_01
transcript.pyannote[222].start 803.78721875
transcript.pyannote[222].end 807.68534375
transcript.pyannote[223].speaker SPEAKER_01
transcript.pyannote[223].start 808.47846875
transcript.pyannote[223].end 815.12721875
transcript.pyannote[224].speaker SPEAKER_01
transcript.pyannote[224].start 815.58284375
transcript.pyannote[224].end 821.69159375
transcript.pyannote[225].speaker SPEAKER_01
transcript.pyannote[225].start 821.94471875
transcript.pyannote[225].end 831.25971875
transcript.pyannote[226].speaker SPEAKER_01
transcript.pyannote[226].start 831.95159375
transcript.pyannote[226].end 834.38159375
transcript.pyannote[227].speaker SPEAKER_01
transcript.pyannote[227].start 834.93846875
transcript.pyannote[227].end 838.12784375
transcript.pyannote[228].speaker SPEAKER_01
transcript.pyannote[228].start 838.36409375
transcript.pyannote[228].end 841.26659375
transcript.pyannote[229].speaker SPEAKER_01
transcript.pyannote[229].start 841.48596875
transcript.pyannote[229].end 843.30846875
transcript.pyannote[230].speaker SPEAKER_01
transcript.pyannote[230].start 843.96659375
transcript.pyannote[230].end 849.92346875
transcript.pyannote[231].speaker SPEAKER_01
transcript.pyannote[231].start 850.49721875
transcript.pyannote[231].end 852.92721875
transcript.pyannote[232].speaker SPEAKER_01
transcript.pyannote[232].start 853.87221875
transcript.pyannote[232].end 857.06159375
transcript.pyannote[233].speaker SPEAKER_01
transcript.pyannote[233].start 857.53409375
transcript.pyannote[233].end 859.59284375
transcript.pyannote[234].speaker SPEAKER_01
transcript.pyannote[234].start 859.84596875
transcript.pyannote[234].end 861.29721875
transcript.pyannote[235].speaker SPEAKER_01
transcript.pyannote[235].start 861.97221875
transcript.pyannote[235].end 862.51221875
transcript.pyannote[236].speaker SPEAKER_01
transcript.pyannote[236].start 863.15346875
transcript.pyannote[236].end 875.25284375
transcript.pyannote[237].speaker SPEAKER_01
transcript.pyannote[237].start 875.92784375
transcript.pyannote[237].end 880.55159375
transcript.pyannote[238].speaker SPEAKER_01
transcript.pyannote[238].start 880.93971875
transcript.pyannote[238].end 881.68221875
transcript.pyannote[239].speaker SPEAKER_01
transcript.pyannote[239].start 881.88471875
transcript.pyannote[239].end 884.21346875
transcript.pyannote[240].speaker SPEAKER_01
transcript.pyannote[240].start 884.78721875
transcript.pyannote[240].end 887.28471875
transcript.pyannote[241].speaker SPEAKER_01
transcript.pyannote[241].start 887.79096875
transcript.pyannote[241].end 890.15346875
transcript.pyannote[242].speaker SPEAKER_01
transcript.pyannote[242].start 890.84534375
transcript.pyannote[242].end 891.48659375
transcript.pyannote[243].speaker SPEAKER_01
transcript.pyannote[243].start 891.90846875
transcript.pyannote[243].end 892.80284375
transcript.pyannote[244].speaker SPEAKER_01
transcript.pyannote[244].start 893.47784375
transcript.pyannote[244].end 895.40159375
transcript.pyannote[245].speaker SPEAKER_02
transcript.pyannote[245].start 894.91221875
transcript.pyannote[245].end 903.87284375
transcript.pyannote[246].speaker SPEAKER_01
transcript.pyannote[246].start 903.87284375
transcript.pyannote[246].end 904.44659375
transcript.pyannote[247].speaker SPEAKER_02
transcript.pyannote[247].start 903.90659375
transcript.pyannote[247].end 903.97409375
transcript.pyannote[248].speaker SPEAKER_01
transcript.pyannote[248].start 904.49721875
transcript.pyannote[248].end 914.18346875
transcript.pyannote[249].speaker SPEAKER_02
transcript.pyannote[249].start 904.91909375
transcript.pyannote[249].end 905.37471875
transcript.pyannote[250].speaker SPEAKER_01
transcript.pyannote[250].start 914.62221875
transcript.pyannote[250].end 924.00471875
transcript.pyannote[251].speaker SPEAKER_02
transcript.pyannote[251].start 921.64221875
transcript.pyannote[251].end 927.27846875
transcript.pyannote[252].speaker SPEAKER_01
transcript.pyannote[252].start 927.27846875
transcript.pyannote[252].end 927.71721875
transcript.pyannote[253].speaker SPEAKER_02
transcript.pyannote[253].start 927.43034375
transcript.pyannote[253].end 927.51471875
transcript.pyannote[254].speaker SPEAKER_02
transcript.pyannote[254].start 951.07221875
transcript.pyannote[254].end 955.56096875
transcript.pyannote[255].speaker SPEAKER_02
transcript.pyannote[255].start 956.45534375
transcript.pyannote[255].end 960.97784375
transcript.whisperx[0].start 9.301
transcript.whisperx[0].end 14.804
transcript.whisperx[0].text 主席韓院長麻煩請行政院左院長麻煩再請左院長備詢現在因為這個美國的關稅問題所以我認為這個是美中貿易戰爭裡面的一個一個
transcript.whisperx[1].start 37.867
transcript.whisperx[1].end 56.983
transcript.whisperx[1].text 延伸然後現在是進入緊鑼密鼓的階段但是延伸到台灣這邊來的話我覺得我們跟台美的關稅最重要的問題其實不是在關稅的本身我個人認為是在解決貿易順差是一個很大的課題但是這個貿易順差的這個數字
transcript.whisperx[2].start 60.168
transcript.whisperx[2].end 73.758
transcript.whisperx[2].text 美國的統計跟我們台灣的統計好像不太一樣一邊是749億一邊是600多億的美金那這個您知道這個中間這個數據的差距它的原因是什麼嗎
transcript.whisperx[3].start 75.526
transcript.whisperx[3].end 100.727
transcript.whisperx[3].text 他算出來是1114億美方的數字是1114億我是意思說美方的統計我們對台灣對他的貿易順差是749去年但是台灣自己本身原來的統計是600多那中間將近落差了100多億那100多億這個數字上面美國的看法跟我們的看法不一樣他要產生這個差距的原因是在哪裡多少有一些計算的項目的不同
transcript.whisperx[4].start 102.755
transcript.whisperx[4].end 128.918
transcript.whisperx[4].text 還有一些可能是轉口的問題我覺得這裡面國際貿易的原理其實國際貿易原理它是追求平衡所以我們如果是對人家順差很大的國家他如果想辦法去解決貿易之間順差的問題上一次我有跟您提過加大對美國的採購然後包括天然氣
transcript.whisperx[5].start 130.441
transcript.whisperx[5].end 155.32
transcript.whisperx[5].text 原油啊 還包括這個大宗物資 黃小玉然後再加上可能再加上我們的軍事採購總是這個可以減少貿易順差的部分吧上次提過我想這個目前也台灣也目前也是正在這樣做大採購跟投資以及談判關稅這個都是目前雙方在進行磋商的重要的內容
transcript.whisperx[6].start 156.051
transcript.whisperx[6].end 165.107
transcript.whisperx[6].text 對 那我覺得這個才是真正解決問題的重要核心那當然賴總統所提的說如果台灣的廠商可以的話去
transcript.whisperx[7].start 166.653
transcript.whisperx[7].end 186.485
transcript.whisperx[7].text 自己算起來覺得可以的話希望能有去美國這個投資的機會那這個當然會接觸到這個金融帳上面的另外一個問題是說我們如果美國另外一個希望那是希望製造業能夠回到美國那我們如果台灣的廠商去美國投資在美國產生的這個
transcript.whisperx[8].start 188.36
transcript.whisperx[8].end 198.527
transcript.whisperx[8].text 製造業的聚落跟台灣這邊的廠商搭配這是一個不錯的看法將來在對美國的順差上面有可能可以
transcript.whisperx[9].start 199.793
transcript.whisperx[9].end 227.11
transcript.whisperx[9].text 可以比較減少因為我們就不用輸出全部的成品我們辦成品或是零件然後在美國這邊的製造商在那邊投資在那邊製造在美國銷售所以那個差距會有一些在美國投資在美國設廠市場就是以美國那在台灣的設廠台灣的製造就是以全世界為市場這樣能不能取代關稅上的一些衝擊對然後我就是要現在要跟你談一個我認為蠻重要的問題
transcript.whisperx[10].start 229.747
transcript.whisperx[10].end 255.466
transcript.whisperx[10].text 就是因為現在美國對於中國不遵守國際貿易規則所以到現在對於中國的產品他加了很高的關稅另外一點他要嚴防各地幫中國的產品洗產地我了解美國的定義只要你的原料半成品有35%是從中國來的他就認為你這是中國的產品
transcript.whisperx[11].start 259.073
transcript.whisperx[11].end 283.098
transcript.whisperx[11].text 那問題是台灣本身對於台灣製造的定義是這樣喔我無論原料從哪裡來我只要在台灣加值超過35%我就認為這是Made in Taiwan那你不覺得這中間有一種中途嗎我舉一個例子如果當然這個例子是比較極端我的原料跟零件50%從中國來
transcript.whisperx[12].start 286.159
transcript.whisperx[12].end 313.86
transcript.whisperx[12].text 台灣製造價值50%這個產品出口到美國在美國的定義這是中國的產品但台灣本身的定義這個是made in Taiwan所以這正好就進入了美國說那你台灣就是在幫中國洗產地所以關於美國對於中國製造以及台灣對台灣製造非中國製造這中間的定義要如何調和
transcript.whisperx[13].start 315.489
transcript.whisperx[13].end 341.718
transcript.whisperx[13].text 我覺得這是一個很大的課題這不知道你有什麼看法將來在談判過程當中我們都要提出這樣的數據來紀律力爭以國內的市場的行為跟美國的認知來做一個和平我希望能夠以我們現在國內的狀況來當作我們談判的起點那問題是因為美國這個35%中國的原料跟零件他是對全世界的標準不是只有對台灣
transcript.whisperx[14].start 343.103
transcript.whisperx[14].end 356.578
transcript.whisperx[14].text 那你台灣在這個標準上沒有去跟人家談說我的台灣的價值現在是35那假設你要往上抬美國要求你往上抬你說40 45這個都不符合美國現在對中國製產品的這個定義
transcript.whisperx[15].start 360.742
transcript.whisperx[15].end 387.704
transcript.whisperx[15].text 說明一下委員確實這個部分要注意這個問題然後剛剛院長已經說在談判的時候會提出來這個另外呢我們現在在談判的過程中已經談到這個了嗎另外還有一個就是因為進口的原產地在進口的時候是由進口國的海關來認定所以他們有它相關的一些規定那在我們這邊部分我們經濟部會跟美方去談之外還有一個就是有一個預審機制
transcript.whisperx[16].start 388.965
transcript.whisperx[16].end 414.435
transcript.whisperx[16].text 也就是說我們這邊的出口廠商可以向美方的海關申請預審也就是說我這邊出口MIT的標示是不是符合你這邊的符合他們可以認定這個是台灣是原產地這是一個預審機制進入個案的認定部長你這個講法在委員會都談過了但是我不能夠滿意的地方在哪裡呢你這個就是我就要舉一個例子啊我台灣的廠商假設我是一個遵守台灣法令的廠商我的價值
transcript.whisperx[17].start 416.001
transcript.whisperx[17].end 428.229
transcript.whisperx[17].text 在台灣的價值就超過50%啊所以依照我的定義完全依照法令來我就是Made in Taiwan啊那我假設我這個Made in Taiwan的產品我出口到美國去
transcript.whisperx[18].start 429.431
transcript.whisperx[18].end 449.84
transcript.whisperx[18].text 那美國國家的定義對全世界是一樣的啊他認為你這個是中國的產品啊那這不就是我剛剛講的正好熱入說就確切的認定就是台灣在幫中國洗產地嗎那你說我這個預審我個案那個是要繳多少稅金的問題啊我現在是跟你講說這個定義
transcript.whisperx[19].start 452.011
transcript.whisperx[19].end 458.555
transcript.whisperx[19].text 如果我們跟美國之間的利益是有這麼大的差距的話我們很容易落入這樣子的一個情境這樣一個狀況
transcript.whisperx[20].start 482.651
transcript.whisperx[20].end 508.517
transcript.whisperx[20].text 所以有可能我一個台灣的廠商我做一樣的東西我的原料來源一樣我出口的對象如果不是美國是made in Taiwan我出口的對象如果是美國的話變成made in China那請問我們如果建立台灣made in Taiwan MIT的這樣子的在國際之間的我們要打品牌要讓人家知道我們這是高價值的產品啊我跟你說川普總統我一再講他就是要改變這個貿易規則嘛
transcript.whisperx[21].start 511.124
transcript.whisperx[21].end 529.025
transcript.whisperx[21].text 你一直跟我講說拿這個世界的貿易規則就是35%的價值就可以算那一國的產品你沒有辦法拿這個標準去要求美國啊所以我現在是問你說美國跟這個這樣子中間的落差跟台灣中間的這個落差如果不趕快調整的話我覺得台灣很危險耶
transcript.whisperx[22].start 530.353
transcript.whisperx[22].end 535.157
transcript.whisperx[22].text 所以我們就是透過談判的機制希望把雙方不同的標準數據能夠把它做一個對齊或者是做一個如何的改進我剛剛的意思是說WTO的那個標準
transcript.whisperx[23].start 555.509
transcript.whisperx[23].end 578.776
transcript.whisperx[23].text 因為美國要對付中國中國不遵守WTO的規範在很多地方啦所以美國要改變那個貿易規則啦現在川普就是擺明了在改變這個貿易規則啊所以我們台灣要怎麼樣子處理這個是我覺得這是很重要的一環另外像越南這一次也是一個美國要
transcript.whisperx[24].start 580.217
transcript.whisperx[24].end 590.221
transcript.whisperx[24].text 處理的一個幫中國洗產地的一個很大的目標國家就越南前兩天就公佈了他要求整個供應鏈製造產品的供應鏈的履歷
transcript.whisperx[25].start 593.618
transcript.whisperx[25].end 612.363
transcript.whisperx[25].text 要清楚的呈現出來我覺得他山之石可以說錯台灣要不要要求這些零件原料的履歷讓這個商品到底他是從哪一些國家來的多少成分如何組成的也清清楚楚這個你們有可以考慮嗎
transcript.whisperx[26].start 613.263
transcript.whisperx[26].end 632.497
transcript.whisperx[26].text 我們也要求提供產地證明等等這只有產地證明 它是產品的履歷所有的產品的履歷我們現在農產品有履歷嘛 對不對哪一個農民在哪一塊地上面種出來有履歷嘛它現在越南為了要避免美國對付它越南現在採取要求所有它的產品
transcript.whisperx[27].start 633.157
transcript.whisperx[27].end 647.364
transcript.whisperx[27].text 都要有履歷包括哪一個零件假設他的零件是從台灣的哪一個廠商來的啊這個裡面搞不好他這個產品總共有幾十樣零件他每一樣零件從哪裡來從哪一個工廠製造出來他都要求喔
transcript.whisperx[28].start 648.442
transcript.whisperx[28].end 677.151
transcript.whisperx[28].text 他要求這麼嚴喔 他很怕美國很高的關稅對付他我們對違規轉運的 我們設了幾道關卡做得很不好 我也問過他啦六年來喔 在整個加工貿易在自由貿易區 總共境內關外的 總共才查了幾件從海關到經濟部 以前做得不夠嚴謹 現在我們一定強烈的要求否則我們沒有辦法在這波世界貿易重組當中 台灣站得住腳
transcript.whisperx[29].start 678.806
transcript.whisperx[29].end 704.706
transcript.whisperx[29].text 所以你說能夠加強什麼呢到時候你就是拿出成績給我們看吧我相信台灣有很多產品我個人相信是你過去稽查上面沒有不夠嚴謹產生漏洞的應該是會有一些我們這次會更加強的而且有相關的經濟措施那也會提高在自貿港區裡面的一些扒環那再延伸的問題
transcript.whisperx[30].start 706.823
transcript.whisperx[30].end 735.56
transcript.whisperx[30].text 就是說中國跟美國之間這樣子的狀況之下中國的經濟是非常的嚴峻那台灣過去銀行都有統計曝險嘛有一套標準但是那個曝險的統計都是有統計到國有銀行包括公營的跟民營的但是是有一些漏洩統計的因為那個曝險的金額遠不止這樣舉個例子國有銀行在中國的紙行
transcript.whisperx[31].start 736.874
transcript.whisperx[31].end 756.385
transcript.whisperx[31].text 沒有統計再來就是有一些影子銀行租賃公司或是做一些分級付款買賣等等所謂的曝險以前的定義比較狹窄中國的經濟日益嚴峻我們要確確的掌握詳細的數字之後才會有辦法擬定我們的政策對不對
transcript.whisperx[32].start 757.325
transcript.whisperx[32].end 785.178
transcript.whisperx[32].text 這部分請金管會主委說明一下如何加強其實我們對紙行是有掌控的資料都有只是說我們過去在計算曝險的時候是從法律關係來計算我們已經開始從實質的曝險的角度去調整我們計算的方式我想這細節部分可以跟委員再做說明我想這個我們都有全盤的掌握那什麼時候可以提供比較完整的資料
transcript.whisperx[33].start 785.598
transcript.whisperx[33].end 807.341
transcript.whisperx[33].text 就是我們對外因為牽涉到法令的部分我們對外還是一樣比如公佈的這個曝險比例還是按照我們現有的法規的內容但是呢我們有針對實質的比如說它的實質的曝險我們用更換一套計算的公式再重新來審視這件事情我想會更精準的看到這些內容主委我想齁我要提這件事情是為了要預先
transcript.whisperx[34].start 808.522
transcript.whisperx[34].end 833.913
transcript.whisperx[34].text 大家要掌握詳細的資料將來的政策擬定上才不會比較能夠比較接近我們需要達到的目的如果我們統計的數據跟實質的差距差很大的話那個統計意義就不大所以希望這方面能夠加強你願意能夠加強的話那是很好那我們就來努力但是我要提醒一點我認為香港是不是也要把它計算進來
transcript.whisperx[35].start 834.997
transcript.whisperx[35].end 861.066
transcript.whisperx[35].text 因為這一次美國對中國的貿易裡面他沒有把香港單獨作為一個關稅領域他就直接把它算到中國裡面來所以香港現在的國際地位在美國現在的政策上面它已經是中國的一個城市所以我們去計算普選的時候我們要知道你過去的計算方法只有中國不包括香港 香港你是把它獨立出來假設美國的政策
transcript.whisperx[36].start 862.148
transcript.whisperx[36].end 889.843
transcript.whisperx[36].text 是這樣他對關稅的部分是這樣他未來其他的部分也慢慢會跟進這個其實我以前的咨詢就已經談過了說因為香港最嚴重的地方是可能會被踢出這個貨幣換算的機制那現在一步一步來了切香腸一刀一刀再切最後會出現結論嘛所以對香港的曝險你如果沒有改弦更張還是把它跟中國分開計算的話我覺得
transcript.whisperx[37].start 892.417
transcript.whisperx[37].end 908.843
transcript.whisperx[37].text 這個在變動的數據上可能會跟不上這個跟委員說明一下其實我們港澳跟大陸地區都有分開都有完整的數據這沒有問題我知道美國的政策你聽美國的政策把香港當作中國的一個城市嘛
transcript.whisperx[38].start 909.463
transcript.whisperx[38].end 926.305
transcript.whisperx[38].text 如果我們把香港也當作中國一個城市假設我們跟著美國的政策走的時候你那個對中國的普選的資料數字就會天差地啊搞不好你銀行規定那個禁止的百分之百有沒有辦法能不能遵守這個都不清楚啊其實我們這個都有在按照那個
transcript.whisperx[39].start 951.104
transcript.whisperx[39].end 955.287
transcript.whisperx[39].text 好,谢谢吴秉瑞委员的资讯,谢谢卓院长,各部会首长的备选,谢谢。