iVOD / 164718

Field Value
IVOD_ID 164718
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164718
日期 2025-10-23
會議資料.會議代碼 委員會-11-4-20-4
會議資料.會議代碼:str 第11屆第4會期財政委員會第4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 4
會議資料.種類 委員會
會議資料.委員會代碼[0] 20
會議資料.委員會代碼:str[0] 財政委員會
會議資料.標題 第11屆第4會期財政委員會第4次全體委員會議
影片種類 Clip
開始時間 2025-10-23T09:23:44+08:00
結束時間 2025-10-23T09:34:31+08:00
影片長度 00:10:47
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/e3c6c6412082f242b65e22d5fd7b62dc48629de9594d8cbef117ba332e8a767fe766b101dd82558b5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 吳秉叡
委員發言時間 09:23:44 - 09:34:31
會議時間 2025-10-23T09:00:00+08:00
會議名稱 立法院第11屆第4會期財政委員會第4次全體委員會議(事由:邀請中央銀行楊總裁金龍率所屬單位主管暨財金資訊股份有限公司董事長列席業務報告,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 13.12596875
transcript.pyannote[0].end 14.18909375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 16.41659375
transcript.pyannote[1].end 19.63971875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 24.21284375
transcript.pyannote[2].end 26.18721875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 26.35596875
transcript.pyannote[3].end 26.99721875
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 27.40221875
transcript.pyannote[4].end 29.14034375
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 29.46096875
transcript.pyannote[5].end 30.72659375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 31.26659375
transcript.pyannote[6].end 34.30409375
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 34.69221875
transcript.pyannote[7].end 34.72596875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 34.72596875
transcript.pyannote[8].end 34.84409375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 34.84409375
transcript.pyannote[9].end 34.86096875
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 34.86096875
transcript.pyannote[10].end 35.02971875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 35.02971875
transcript.pyannote[11].end 35.04659375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 35.04659375
transcript.pyannote[12].end 35.06346875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 35.06346875
transcript.pyannote[13].end 53.17034375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 49.28909375
transcript.pyannote[14].end 49.91346875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 51.11159375
transcript.pyannote[15].end 51.46596875
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 52.30971875
transcript.pyannote[16].end 52.79909375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 53.57534375
transcript.pyannote[17].end 58.11471875
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 55.17846875
transcript.pyannote[18].end 55.27971875
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 57.28784375
transcript.pyannote[19].end 58.21596875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 58.21596875
transcript.pyannote[20].end 58.31721875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 58.31721875
transcript.pyannote[21].end 59.11034375
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 58.68846875
transcript.pyannote[22].end 63.00846875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 61.20284375
transcript.pyannote[23].end 62.16471875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 63.00846875
transcript.pyannote[24].end 67.80096875
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 63.05909375
transcript.pyannote[25].end 63.29534375
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 68.30721875
transcript.pyannote[26].end 71.98596875
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 71.98596875
transcript.pyannote[27].end 72.34034375
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 72.34034375
transcript.pyannote[28].end 79.64721875
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 72.35721875
transcript.pyannote[29].end 72.39096875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 78.55034375
transcript.pyannote[30].end 78.78659375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 79.73159375
transcript.pyannote[31].end 82.22909375
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 80.77784375
transcript.pyannote[32].end 81.11534375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 82.53284375
transcript.pyannote[33].end 83.61284375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 82.63409375
transcript.pyannote[34].end 82.83659375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 84.77721875
transcript.pyannote[35].end 86.73471875
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 87.56159375
transcript.pyannote[36].end 98.90159375
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 91.67909375
transcript.pyannote[37].end 92.06721875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 98.95221875
transcript.pyannote[38].end 98.96909375
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 99.12096875
transcript.pyannote[39].end 128.46659375
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 105.12846875
transcript.pyannote[40].end 105.61784375
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 108.11534375
transcript.pyannote[41].end 108.77346875
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 114.34221875
transcript.pyannote[42].end 114.49409375
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 128.90534375
transcript.pyannote[43].end 134.37284375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 134.64284375
transcript.pyannote[44].end 137.79846875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 137.91659375
transcript.pyannote[45].end 139.95846875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 138.30471875
transcript.pyannote[46].end 138.33846875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 140.07659375
transcript.pyannote[47].end 145.72971875
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 140.26221875
transcript.pyannote[48].end 140.38034375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 146.28659375
transcript.pyannote[49].end 156.42846875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 148.90221875
transcript.pyannote[50].end 148.95284375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 149.40846875
transcript.pyannote[51].end 149.52659375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 151.28159375
transcript.pyannote[52].end 151.50096875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 153.99846875
transcript.pyannote[53].end 154.20096875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 156.09096875
transcript.pyannote[54].end 156.12471875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 157.20471875
transcript.pyannote[55].end 173.42159375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 159.26346875
transcript.pyannote[56].end 159.53346875
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 161.74409375
transcript.pyannote[57].end 162.14909375
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 163.65096875
transcript.pyannote[58].end 163.85346875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 167.95409375
transcript.pyannote[59].end 169.74284375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 173.42159375
transcript.pyannote[60].end 173.53971875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 173.91096875
transcript.pyannote[61].end 173.97846875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 173.97846875
transcript.pyannote[62].end 192.32159375
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 187.71471875
transcript.pyannote[63].end 191.62971875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 191.86596875
transcript.pyannote[64].end 191.98409375
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 192.59159375
transcript.pyannote[65].end 193.06409375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 192.74346875
transcript.pyannote[66].end 196.96221875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 196.96221875
transcript.pyannote[67].end 227.03346875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 227.03346875
transcript.pyannote[68].end 233.96909375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 233.56409375
transcript.pyannote[69].end 234.20534375
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 234.20534375
transcript.pyannote[70].end 274.55346875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 234.22221875
transcript.pyannote[71].end 234.39096875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 241.46159375
transcript.pyannote[72].end 241.88346875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 244.24596875
transcript.pyannote[73].end 244.38096875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 248.21159375
transcript.pyannote[74].end 248.26221875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 256.37909375
transcript.pyannote[75].end 257.69534375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 263.17971875
transcript.pyannote[76].end 263.26409375
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 263.38221875
transcript.pyannote[77].end 263.51721875
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 270.38534375
transcript.pyannote[78].end 270.70596875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 274.60409375
transcript.pyannote[79].end 276.34221875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 274.67159375
transcript.pyannote[80].end 274.92471875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 276.91596875
transcript.pyannote[81].end 303.39284375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 279.85221875
transcript.pyannote[82].end 279.98721875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 280.10534375
transcript.pyannote[83].end 280.22346875
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 282.60284375
transcript.pyannote[84].end 282.75471875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 293.08221875
transcript.pyannote[85].end 293.11596875
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 293.36909375
transcript.pyannote[86].end 293.41971875
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 303.46034375
transcript.pyannote[87].end 311.61096875
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 303.81471875
transcript.pyannote[88].end 304.48971875
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 304.72596875
transcript.pyannote[89].end 304.74284375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 304.91159375
transcript.pyannote[90].end 305.65409375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 306.05909375
transcript.pyannote[91].end 306.56534375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 308.05034375
transcript.pyannote[92].end 308.13471875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 308.55659375
transcript.pyannote[93].end 308.59034375
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 311.61096875
transcript.pyannote[94].end 312.03284375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 312.47159375
transcript.pyannote[95].end 315.37409375
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 315.37409375
transcript.pyannote[96].end 316.85909375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 316.21784375
transcript.pyannote[97].end 327.87846875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 317.36534375
transcript.pyannote[98].end 317.60159375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 323.52471875
transcript.pyannote[99].end 323.60909375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 326.49471875
transcript.pyannote[100].end 326.76471875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 328.11471875
transcript.pyannote[101].end 332.56971875
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 331.42221875
transcript.pyannote[102].end 331.96221875
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 332.58659375
transcript.pyannote[103].end 335.06721875
transcript.pyannote[104].speaker SPEAKER_01
transcript.pyannote[104].start 332.67096875
transcript.pyannote[104].end 332.97471875
transcript.pyannote[105].speaker SPEAKER_00
transcript.pyannote[105].start 335.16846875
transcript.pyannote[105].end 345.69846875
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 335.79284375
transcript.pyannote[106].end 336.19784375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 338.76284375
transcript.pyannote[107].end 339.21846875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 345.69846875
transcript.pyannote[108].end 345.91784375
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 345.91784375
transcript.pyannote[109].end 348.41534375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 349.02284375
transcript.pyannote[110].end 350.25471875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 350.27159375
transcript.pyannote[111].end 350.67659375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 350.60909375
transcript.pyannote[112].end 359.99159375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 357.44346875
transcript.pyannote[113].end 357.93284375
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 360.05909375
transcript.pyannote[114].end 367.02846875
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 360.22784375
transcript.pyannote[115].end 360.46409375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 367.21409375
transcript.pyannote[116].end 367.70346875
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 368.02409375
transcript.pyannote[117].end 385.16909375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 381.59159375
transcript.pyannote[118].end 381.65909375
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 381.87846875
transcript.pyannote[119].end 382.03034375
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 385.59096875
transcript.pyannote[120].end 386.78909375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 386.11409375
transcript.pyannote[121].end 386.18159375
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 386.90721875
transcript.pyannote[122].end 390.60284375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 390.46784375
transcript.pyannote[123].end 390.95721875
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 390.65346875
transcript.pyannote[124].end 394.12971875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 393.69096875
transcript.pyannote[125].end 395.83409375
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 396.05346875
transcript.pyannote[126].end 399.49596875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 399.41159375
transcript.pyannote[127].end 399.66471875
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 399.64784375
transcript.pyannote[128].end 401.36909375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 399.69846875
transcript.pyannote[129].end 399.78284375
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 401.23409375
transcript.pyannote[130].end 401.31846875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 401.36909375
transcript.pyannote[131].end 401.60534375
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 401.60534375
transcript.pyannote[132].end 403.12409375
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 403.37721875
transcript.pyannote[133].end 421.38284375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 419.66159375
transcript.pyannote[134].end 420.43784375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 420.85971875
transcript.pyannote[135].end 455.28471875
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 453.49596875
transcript.pyannote[136].end 453.74909375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 455.45346875
transcript.pyannote[137].end 485.25471875
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 485.55846875
transcript.pyannote[138].end 522.97034375
transcript.pyannote[139].speaker SPEAKER_00
transcript.pyannote[139].start 519.66284375
transcript.pyannote[139].end 519.86534375
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 522.97034375
transcript.pyannote[140].end 549.16034375
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 527.37471875
transcript.pyannote[141].end 528.13409375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 536.21721875
transcript.pyannote[142].end 537.02721875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 548.08034375
transcript.pyannote[143].end 561.37784375
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 561.85034375
transcript.pyannote[144].end 584.20971875
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 566.22096875
transcript.pyannote[145].end 566.84534375
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 572.73471875
transcript.pyannote[146].end 573.17346875
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 575.26596875
transcript.pyannote[147].end 575.80596875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 582.55596875
transcript.pyannote[148].end 582.62346875
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 582.79221875
transcript.pyannote[149].end 583.11284375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 584.73284375
transcript.pyannote[150].end 599.04284375
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 588.98534375
transcript.pyannote[151].end 589.86284375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 593.15346875
transcript.pyannote[152].end 593.55846875
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 595.16159375
transcript.pyannote[153].end 595.26284375
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 595.27971875
transcript.pyannote[154].end 595.49909375
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 597.89534375
transcript.pyannote[155].end 598.62096875
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 599.04284375
transcript.pyannote[156].end 605.67471875
transcript.pyannote[157].speaker SPEAKER_00
transcript.pyannote[157].start 599.17784375
transcript.pyannote[157].end 599.85284375
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 602.33346875
transcript.pyannote[158].end 622.19534375
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 607.29471875
transcript.pyannote[159].end 607.31159375
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 610.26471875
transcript.pyannote[160].end 611.10846875
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 612.12096875
transcript.pyannote[161].end 613.09971875
transcript.pyannote[162].speaker SPEAKER_01
transcript.pyannote[162].start 616.67721875
transcript.pyannote[162].end 617.13284375
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 618.39846875
transcript.pyannote[163].end 619.32659375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 620.64284375
transcript.pyannote[164].end 621.11534375
transcript.pyannote[165].speaker SPEAKER_00
transcript.pyannote[165].start 622.93784375
transcript.pyannote[165].end 632.37096875
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 629.67096875
transcript.pyannote[166].end 629.99159375
transcript.pyannote[167].speaker SPEAKER_01
transcript.pyannote[167].start 632.37096875
transcript.pyannote[167].end 632.38784375
transcript.pyannote[168].speaker SPEAKER_00
transcript.pyannote[168].start 632.38784375
transcript.pyannote[168].end 632.80971875
transcript.pyannote[169].speaker SPEAKER_01
transcript.pyannote[169].start 632.50596875
transcript.pyannote[169].end 632.74221875
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 632.80971875
transcript.pyannote[170].end 641.95596875
transcript.pyannote[171].speaker SPEAKER_00
transcript.pyannote[171].start 633.23159375
transcript.pyannote[171].end 633.50159375
transcript.pyannote[172].speaker SPEAKER_00
transcript.pyannote[172].start 633.65346875
transcript.pyannote[172].end 634.83471875
transcript.pyannote[173].speaker SPEAKER_00
transcript.pyannote[173].start 639.47534375
transcript.pyannote[173].end 639.88034375
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 639.93096875
transcript.pyannote[174].end 640.03221875
transcript.pyannote[175].speaker SPEAKER_00
transcript.pyannote[175].start 640.80846875
transcript.pyannote[175].end 643.82909375
transcript.pyannote[176].speaker SPEAKER_01
transcript.pyannote[176].start 643.23846875
transcript.pyannote[176].end 646.90034375
transcript.pyannote[177].speaker SPEAKER_00
transcript.pyannote[177].start 644.55471875
transcript.pyannote[177].end 644.77409375
transcript.pyannote[178].speaker SPEAKER_00
transcript.pyannote[178].start 645.14534375
transcript.pyannote[178].end 645.26346875
transcript.whisperx[0].start 16.482
transcript.whisperx[0].end 18.367
transcript.whisperx[0].text 主席 麻煩請中央銀行楊總裁好 請楊總裁
transcript.whisperx[1].start 24.589
transcript.whisperx[1].end 50.636
transcript.whisperx[1].text 吳委員早早喔是這個看到你的報告裡面提到今年上半年的經濟成長率是GDP是6.75是那因為上半年已經結束所以這是確定的對沒有錯然後你們的預估是下半年是2.51是所以全年現在預估是4.55是那當然你剛剛有講說12月的時候你們還會再開一個會然後看看是不是調整
transcript.whisperx[2].start 50.996
transcript.whisperx[2].end 71.586
transcript.whisperx[2].text 但是我提醒你第三季我們的出口仍然更超越以往更破紀錄所以我看這個明顯的2.5億這個預估應該是會要調高我想我們會仔細的去研究裡面一個很重要的原因就是我們的出口
transcript.whisperx[3].start 72.406
transcript.whisperx[3].end 80.577
transcript.whisperx[3].text 尤其是電子跟AI產品的出口這個訂單持續在增加今年對美國的粗糙你認為應該會有多少金額
transcript.whisperx[4].start 87.631
transcript.whisperx[4].end 112.918
transcript.whisperx[4].text 我有一個數據跟委員報告我們是也有做預估大概會1200億左右去年我們台灣看自己的報告是600多億的順差但是美國是說是700多億因為可能轉口什麼計算的標準不是很一致差距不大
transcript.whisperx[5].start 115.299
transcript.whisperx[5].end 133.912
transcript.whisperx[5].text 這700多億的這個順差在美國來講就已經是他前幾名的這個順差國家所以站在國際貿易的角度你認為這個應該要如何平衡我們有時候講談政治也好談國家跟國家之好一地而處
transcript.whisperx[6].start 134.953
transcript.whisperx[6].end 155.527
transcript.whisperx[6].text 今天如果有一個國家對台灣的粗糙是這麼的多的時候那你覺得台灣政府不應該要拿出一些對策嗎那如果用這樣的想法相對的美國政府也對我們提出很多的對策嘛包括他要跟你關稅談判啊然後希望你要多進口美國的東西啊要平衡貿易啊
transcript.whisperx[7].start 157.568
transcript.whisperx[7].end 172.575
transcript.whisperx[7].text 這個目標不僅達不成如果照你剛剛預估數目今年的順差會達到1200多億那我覺得你未來的問題可能面對的要很嚴峻那總裁你的想法如何平衡台灣跟美國之間的國際貿易呢
transcript.whisperx[8].start 174.436
transcript.whisperx[8].end 188.465
transcript.whisperx[8].text 我想報告委員剛剛你所講的就是說我們對美國的增加對他的一個採購這個是一個方式不管就是說是在國防後面還有其他應該
transcript.whisperx[9].start 192.848
transcript.whisperx[9].end 196.849
transcript.whisperx[9].text 人家讓我們賺了這麼多錢我們如果合理的就是要跟人家買是所以就是說現在我們要把我們就是說台灣的一個經驗要到美國去設廠我想如果說我們台積電在那邊設廠還有周遭的一些相關的一個產業鏈也能夠過去的話
transcript.whisperx[10].start 217.256
transcript.whisperx[10].end 219.257
transcript.whisperx[10].text 這個我覺得我在猜想這個也是我們平衡我們中美貿易的一個很好的方式這個方式是這樣子的因為現在美國川普總統他們政府的政策就是要製造業重回美國
transcript.whisperx[11].start 234.364
transcript.whisperx[11].end 260.547
transcript.whisperx[11].text 那製造業重回美國當然非常多的面向其中包括AI跟電子產業裡面台灣扮演重要的角色那在造船方面韓國扮演重要的角色在其他的領域日本又扮演重要的角色等等所以這是一個國際之間如何跟美國在全世界建構的貿易再平衡然後配合美國的政策的一個重要指標那因為美國的勞動界就是說他們的
transcript.whisperx[12].start 262.367
transcript.whisperx[12].end 275.872
transcript.whisperx[12].text 這個工人他的工作習慣跟台灣的文化是不一樣的另外台灣因為中小企業是很龐大所以我們是一個整個產業群組整個聚落所以我們譬如說我在台灣
transcript.whisperx[13].start 277.031
transcript.whisperx[13].end 302.412
transcript.whisperx[13].text 做的是一部分然後大家打群架嘛才會做出最終端的好產品那美國基本上他們現在的製造業沒有這樣的概念所以才說要去美國複製科學園區的概念是這樣子的觀念那問題是這個是去美國投資是只有平衡這個金融帳啊我們去那邊投資弄了很多美金去美國投資但那還是台灣的錢啊
transcript.whisperx[14].start 303.593
transcript.whisperx[14].end 327.531
transcript.whisperx[14].text 那台湾的企业到美国投资目的也是要赚更多的钱当然在美国会有制造会有工作机会但是那个只是一部分对啦没有错啦所以其实我是觉得政府的政策跟目前谈判的方向跟美国的政策是整个是一贯的啦这个对美贸易谈判我常常做一个比喻
transcript.whisperx[15].start 328.331
transcript.whisperx[15].end 347.63
transcript.whisperx[15].text 是吃西餐的套餐啦是一攬子的不能光挑裡面的一樣出來比啦那老師要比說那現在韓國是15%那台灣20%比較高問題是你韓國大家一定要投資美國4千多億的美金啊那現在李在民回到韓國說
transcript.whisperx[16].start 349.073
transcript.whisperx[16].end 365.284
transcript.whisperx[16].text 沒有辦法兌現啦因為他說如果兌現的話韓國可能會產生新的金融危機因為韓國的外匯存底跟比不上台灣嘛他自己基本上也沒有4000多億美金可以拿出來去做投資嘛那被打臉了之後現在美國政府回過頭來會怎麼對付韓國我們還在看啦
transcript.whisperx[17].start 368.18
transcript.whisperx[17].end 394.935
transcript.whisperx[17].text 那當然因為美國也有很多的問題啊譬如說他的最高法院最近也在對這個貿易談判的這個關稅問題在打法律官司在跟美國政府之間有人在跟美國政府之間打法律官司嘛所以這個10月底才會見真章嘛所以我覺得我們做一個公允的論證比較是一攬子的比較而不是只單一項目的比較沒有錯啦 是沒有錯
transcript.whisperx[18].start 396.107
transcript.whisperx[18].end 413.904
transcript.whisperx[18].text 那再來我要問你一個就是會對你產生的問題因為粗糙這麼多台灣又一直被列在外匯操縱的觀察名單那因為粗糙樹木是三大指標裡面的一個很重要的指標所以你如何來面對下面
transcript.whisperx[19].start 415.186
transcript.whisperx[19].end 426.442
transcript.whisperx[19].text 這個國家大好但是你央行在這一方面你要面對考驗那你跟我們回答一下你要如何委員講得沒有錯基本上美國財政部的匯率報告它三項的指標
transcript.whisperx[20].start 431.169
transcript.whisperx[20].end 436.815
transcript.whisperx[20].text 那第一項跟第二項就是經常漲的順差對GDP還有就對美國的一個順差的金額這兩項我們從以前到現在都一直存在的那如果說第三項的話第三項如果我們又觸及到它的時候呢就如同委員說的我們就變成操縱了
transcript.whisperx[21].start 455.503
transcript.whisperx[21].end 459.326
transcript.whisperx[21].text 那操縱的話呢在現在呢這個關稅談判的過程當中呢如果我們又被他抓住這個把柄的話就是說我們台灣呢是操縱匯率的話那這個呢就會變成一個很大的一個事件所以基本上呢我們央行也非常的注意他所以呢但是呢我想呢我們有兩個目標第一個目標呢我們是盡量的
transcript.whisperx[22].start 485.703
transcript.whisperx[22].end 500.997
transcript.whisperx[22].text 要维持我们汇率的稳定让我们的进出口厂商它的报价能够稳定它的营运能够顺畅这是第一个我们的目标这个我觉得最重要是是是第二个目标呢我们呢
transcript.whisperx[23].start 502.819
transcript.whisperx[23].end 506.082
transcript.whisperx[23].text 在因為我們跟美國之間財政部的一個在討論的過程當中我們彼此之間的一個關係也蠻良好的也蠻良好的溝通順暢溝通非常順暢但是即使是順暢但是我們還是不要去踩到他的紅線
transcript.whisperx[24].start 523.058
transcript.whisperx[24].end 543.286
transcript.whisperx[24].text 是但是總裁我現在是講你前面剛剛講那兩樣是我們台灣一直存在沒有錯但是去年存在的客觀現實是對美順超700多億美金但是今年你已經預估到1200多億所以前面那個不利的因素在累加你不能夠說我出超700多億的時候跟出超1200多億的時候是一樣的看待
transcript.whisperx[25].start 546.067
transcript.whisperx[25].end 549.052
transcript.whisperx[25].text 我覺得美國不一定會這樣看待你我們不能一廂情願不過我也跟委員報告在目前的情況之下我們也要認為事實上美國在AI的方面它也是非常依賴我們台灣
transcript.whisperx[26].start 562.054
transcript.whisperx[26].end 583.444
transcript.whisperx[26].text 當然我覺得技術上面還有製造上面我們跟美國是互補如果是未來的高科技產業所謂的電子高科技產業AI這一方面我覺得美國跟台灣的合作會是未來世界的先驅我們已經知道好的位置當然希望繼續維持下去但是我是覺得說
transcript.whisperx[27].start 585.25
transcript.whisperx[27].end 602.359
transcript.whisperx[27].text 這個方面如何跟我們跟美國之間的匯率等等這些問題當然最重要是要維持穩定因為台灣的市場小你如果太多的美金進到台灣投資這些股市然後來來去去會造成幣值的不穩定沒有錯 委員也是觀察得非常的仔細
transcript.whisperx[28].start 603.8
transcript.whisperx[28].end 618.736
transcript.whisperx[28].text 最後一個小問題就是你的新台幣改版你說要向公眾提出徵詢那我先表達我的意見給你聽我是希望未來的新台幣不要再把政治人物放到上面去當這個頭像其實那個時代已經過去了早足以
transcript.whisperx[29].start 623.839
transcript.whisperx[29].end 635.189
transcript.whisperx[29].text 這彰顯台灣的特色 台灣的東西把它放到這上面來這是我的建議 無論是哪一個政治人物都不要再放上去委員的建議 我想我們會納入參考好 謝謝 加油你的這個責任很重是 謝謝 謝謝委員主席謝謝吳秉仁委員