iVOD / 168031

Field Value
IVOD_ID 168031
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/168031
日期 2026-03-30
會議資料.會議代碼 委員會-11-5-20-6
會議資料.會議代碼:str 第11屆第5會期財政委員會第6次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 6
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5會期財政委員會第6次全體委員會議
影片種類 Clip
開始時間 2026-03-30T11:24:51+08:00
結束時間 2026-03-30T11:36:36+08:00
影片長度 00:11:45
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/d0265d86f2f18c67f3319f33d7b2cf215334e86b5f84e1acb7080941cab810cc6175e7c94f56e9555ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 羅明才
委員發言時間 11:24:51 - 11:36:36
會議時間 2026-03-30T09:00:00+08:00
會議名稱 立法院第11屆第5會期財政委員會第6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 0.52034375
transcript.pyannote[0].end 1.51596875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 1.61721875
transcript.pyannote[1].end 3.23721875
transcript.pyannote[2].speaker SPEAKER_01
transcript.pyannote[2].start 2.00534375
transcript.pyannote[2].end 3.08534375
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 3.92909375
transcript.pyannote[3].end 5.85284375
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 4.09784375
transcript.pyannote[4].end 4.50284375
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 6.15659375
transcript.pyannote[5].end 7.16909375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 8.21534375
transcript.pyannote[6].end 10.89846875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 12.68721875
transcript.pyannote[7].end 14.10471875
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 14.76284375
transcript.pyannote[8].end 15.42096875
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 15.53909375
transcript.pyannote[9].end 16.07909375
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 16.56846875
transcript.pyannote[10].end 17.31096875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 18.03659375
transcript.pyannote[11].end 19.30221875
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 19.30221875
transcript.pyannote[12].end 19.62284375
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 21.41159375
transcript.pyannote[13].end 22.00221875
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 22.40721875
transcript.pyannote[14].end 24.39846875
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 22.93034375
transcript.pyannote[15].end 23.53784375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 24.78659375
transcript.pyannote[16].end 25.32659375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 25.42784375
transcript.pyannote[17].end 27.41909375
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 27.67221875
transcript.pyannote[18].end 28.56659375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 28.95471875
transcript.pyannote[19].end 33.08909375
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 29.34284375
transcript.pyannote[20].end 31.01346875
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 33.08909375
transcript.pyannote[21].end 33.76409375
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 33.76409375
transcript.pyannote[22].end 34.77659375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 34.79346875
transcript.pyannote[23].end 37.39221875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 37.47659375
transcript.pyannote[24].end 37.49346875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 37.49346875
transcript.pyannote[25].end 37.81409375
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 37.96596875
transcript.pyannote[26].end 38.92784375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 39.23159375
transcript.pyannote[27].end 39.87284375
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 40.19346875
transcript.pyannote[28].end 40.41284375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 40.96971875
transcript.pyannote[29].end 42.35346875
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 43.63596875
transcript.pyannote[30].end 45.10409375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 45.59346875
transcript.pyannote[31].end 46.52159375
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 48.64784375
transcript.pyannote[32].end 49.37346875
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 50.13284375
transcript.pyannote[33].end 60.61221875
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 61.59096875
transcript.pyannote[34].end 66.60284375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 67.48034375
transcript.pyannote[35].end 72.94784375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 73.50471875
transcript.pyannote[36].end 76.62659375
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 74.02784375
transcript.pyannote[37].end 74.31471875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 74.95596875
transcript.pyannote[38].end 75.31034375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 75.59721875
transcript.pyannote[39].end 75.79971875
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 76.62659375
transcript.pyannote[40].end 76.64346875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 77.13284375
transcript.pyannote[41].end 77.74034375
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 78.09471875
transcript.pyannote[42].end 80.72721875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 80.59221875
transcript.pyannote[43].end 81.21659375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 80.98034375
transcript.pyannote[44].end 82.75221875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 82.78596875
transcript.pyannote[45].end 83.07284375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 83.74784375
transcript.pyannote[46].end 85.04721875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 85.09784375
transcript.pyannote[47].end 85.57034375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 86.32971875
transcript.pyannote[48].end 87.40971875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 87.66284375
transcript.pyannote[49].end 87.89909375
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 88.27034375
transcript.pyannote[50].end 89.23221875
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 89.68784375
transcript.pyannote[51].end 91.13909375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 91.66221875
transcript.pyannote[52].end 92.28659375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 92.60721875
transcript.pyannote[53].end 93.78846875
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 93.87284375
transcript.pyannote[54].end 95.07096875
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 95.94846875
transcript.pyannote[55].end 99.01971875
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 100.01534375
transcript.pyannote[56].end 100.69034375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 100.70721875
transcript.pyannote[57].end 102.42846875
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 103.50846875
transcript.pyannote[58].end 104.03159375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 104.11596875
transcript.pyannote[59].end 104.70659375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 104.92596875
transcript.pyannote[60].end 105.46596875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 106.02284375
transcript.pyannote[61].end 106.29284375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 106.81596875
transcript.pyannote[62].end 107.64284375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 107.84534375
transcript.pyannote[63].end 108.33471875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 108.58784375
transcript.pyannote[64].end 115.27034375
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 115.40534375
transcript.pyannote[65].end 116.06346875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 116.55284375
transcript.pyannote[66].end 117.64971875
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 117.68346875
transcript.pyannote[67].end 118.25721875
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 118.84784375
transcript.pyannote[68].end 119.80971875
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 120.18096875
transcript.pyannote[69].end 120.87284375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 120.87284375
transcript.pyannote[70].end 124.55159375
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 123.15096875
transcript.pyannote[71].end 126.03659375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 125.66534375
transcript.pyannote[72].end 128.97284375
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 128.83784375
transcript.pyannote[73].end 129.59721875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 129.37784375
transcript.pyannote[74].end 139.77284375
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 131.94284375
transcript.pyannote[75].end 132.39846875
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 140.12721875
transcript.pyannote[76].end 142.28721875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 143.26596875
transcript.pyannote[77].end 145.13909375
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 145.62846875
transcript.pyannote[78].end 145.66221875
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 145.66221875
transcript.pyannote[79].end 149.47596875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 145.69596875
transcript.pyannote[80].end 145.79721875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 149.69534375
transcript.pyannote[81].end 151.43346875
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 151.61909375
transcript.pyannote[82].end 153.88034375
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 153.10409375
transcript.pyannote[83].end 154.35284375
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 154.50471875
transcript.pyannote[84].end 155.51721875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 156.04034375
transcript.pyannote[85].end 156.85034375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 158.01471875
transcript.pyannote[86].end 158.48721875
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 158.18346875
transcript.pyannote[87].end 162.73971875
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 162.85784375
transcript.pyannote[88].end 164.49471875
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 165.40596875
transcript.pyannote[89].end 166.26659375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 166.26659375
transcript.pyannote[90].end 166.58721875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 166.90784375
transcript.pyannote[91].end 168.69659375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 169.42221875
transcript.pyannote[92].end 175.31159375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 174.95721875
transcript.pyannote[93].end 176.17221875
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 176.07096875
transcript.pyannote[94].end 194.14409375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 194.80221875
transcript.pyannote[95].end 199.30784375
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 199.94909375
transcript.pyannote[96].end 201.50159375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 201.94034375
transcript.pyannote[97].end 202.88534375
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 204.10034375
transcript.pyannote[98].end 213.70221875
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 214.42784375
transcript.pyannote[99].end 218.34284375
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 214.73159375
transcript.pyannote[100].end 215.00159375
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 218.96721875
transcript.pyannote[101].end 222.46034375
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 222.94971875
transcript.pyannote[102].end 224.41784375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 224.87346875
transcript.pyannote[103].end 234.61034375
transcript.pyannote[104].speaker SPEAKER_01
transcript.pyannote[104].start 234.88034375
transcript.pyannote[104].end 240.48284375
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 241.00596875
transcript.pyannote[105].end 242.05221875
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 242.05221875
transcript.pyannote[106].end 245.59596875
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 245.66346875
transcript.pyannote[107].end 248.07659375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 247.57034375
transcript.pyannote[108].end 250.48971875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 250.37159375
transcript.pyannote[109].end 259.66971875
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 251.28284375
transcript.pyannote[110].end 252.95346875
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 259.68659375
transcript.pyannote[111].end 265.03596875
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 265.77846875
transcript.pyannote[112].end 270.03096875
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 270.25034375
transcript.pyannote[113].end 271.02659375
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 271.33034375
transcript.pyannote[114].end 273.16971875
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 271.71846875
transcript.pyannote[115].end 272.34284375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 273.45659375
transcript.pyannote[116].end 274.16534375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 274.48596875
transcript.pyannote[117].end 277.38846875
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 274.95846875
transcript.pyannote[118].end 275.17784375
transcript.pyannote[119].speaker SPEAKER_00
transcript.pyannote[119].start 277.87784375
transcript.pyannote[119].end 281.79284375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 281.96159375
transcript.pyannote[120].end 284.08784375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 284.54346875
transcript.pyannote[121].end 288.96471875
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 284.61096875
transcript.pyannote[122].end 286.21409375
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 289.01534375
transcript.pyannote[123].end 291.47909375
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 291.59721875
transcript.pyannote[124].end 293.23409375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 291.64784375
transcript.pyannote[125].end 305.31659375
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 297.82409375
transcript.pyannote[126].end 299.47784375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 305.82284375
transcript.pyannote[127].end 308.53971875
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 305.85659375
transcript.pyannote[128].end 307.24034375
transcript.pyannote[129].speaker SPEAKER_00
transcript.pyannote[129].start 308.01659375
transcript.pyannote[129].end 310.02471875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 310.27784375
transcript.pyannote[130].end 337.39596875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 326.27534375
transcript.pyannote[131].end 326.88284375
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 336.43409375
transcript.pyannote[132].end 339.31971875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 340.04534375
transcript.pyannote[133].end 341.51346875
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 341.71596875
transcript.pyannote[134].end 342.34034375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 342.34034375
transcript.pyannote[135].end 346.84596875
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 343.06596875
transcript.pyannote[136].end 346.98096875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 347.08221875
transcript.pyannote[137].end 351.31784375
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 351.16596875
transcript.pyannote[138].end 351.50346875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 351.50346875
transcript.pyannote[139].end 354.43971875
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 352.04346875
transcript.pyannote[140].end 356.31284375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 356.71784375
transcript.pyannote[141].end 358.57409375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 358.79346875
transcript.pyannote[142].end 361.03784375
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 361.56096875
transcript.pyannote[143].end 366.16784375
transcript.pyannote[144].speaker SPEAKER_01
transcript.pyannote[144].start 366.42096875
transcript.pyannote[144].end 372.17534375
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 372.41159375
transcript.pyannote[145].end 384.73034375
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 385.42221875
transcript.pyannote[146].end 388.49346875
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 389.35409375
transcript.pyannote[147].end 399.36096875
transcript.pyannote[148].speaker SPEAKER_00
transcript.pyannote[148].start 398.92221875
transcript.pyannote[148].end 400.32284375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 400.25534375
transcript.pyannote[149].end 402.51659375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 402.48284375
transcript.pyannote[150].end 404.15346875
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 404.33909375
transcript.pyannote[151].end 407.27534375
transcript.pyannote[152].speaker SPEAKER_00
transcript.pyannote[152].start 405.67221875
transcript.pyannote[152].end 408.82784375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 408.33846875
transcript.pyannote[153].end 417.02909375
transcript.pyannote[154].speaker SPEAKER_00
transcript.pyannote[154].start 417.16409375
transcript.pyannote[154].end 420.48846875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 417.92346875
transcript.pyannote[155].end 421.48409375
transcript.pyannote[156].speaker SPEAKER_00
transcript.pyannote[156].start 420.87659375
transcript.pyannote[156].end 421.78784375
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 422.09159375
transcript.pyannote[157].end 428.68971875
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 428.80784375
transcript.pyannote[158].end 436.36784375
transcript.pyannote[159].speaker SPEAKER_00
transcript.pyannote[159].start 433.00971875
transcript.pyannote[159].end 434.20784375
transcript.pyannote[160].speaker SPEAKER_00
transcript.pyannote[160].start 434.73096875
transcript.pyannote[160].end 437.61659375
transcript.pyannote[161].speaker SPEAKER_00
transcript.pyannote[161].start 437.78534375
transcript.pyannote[161].end 443.69159375
transcript.pyannote[162].speaker SPEAKER_00
transcript.pyannote[162].start 444.18096875
transcript.pyannote[162].end 445.37909375
transcript.pyannote[163].speaker SPEAKER_00
transcript.pyannote[163].start 445.95284375
transcript.pyannote[163].end 449.09159375
transcript.pyannote[164].speaker SPEAKER_00
transcript.pyannote[164].start 449.73284375
transcript.pyannote[164].end 451.03221875
transcript.pyannote[165].speaker SPEAKER_00
transcript.pyannote[165].start 452.11221875
transcript.pyannote[165].end 453.71534375
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 452.29784375
transcript.pyannote[166].end 481.10346875
transcript.pyannote[167].speaker SPEAKER_00
transcript.pyannote[167].start 457.66409375
transcript.pyannote[167].end 458.27159375
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 481.82909375
transcript.pyannote[168].end 487.16159375
transcript.pyannote[169].speaker SPEAKER_00
transcript.pyannote[169].start 484.68096875
transcript.pyannote[169].end 484.79909375
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 487.41471875
transcript.pyannote[170].end 492.42659375
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 493.18596875
transcript.pyannote[171].end 494.28284375
transcript.pyannote[172].speaker SPEAKER_00
transcript.pyannote[172].start 494.55284375
transcript.pyannote[172].end 495.10971875
transcript.pyannote[173].speaker SPEAKER_00
transcript.pyannote[173].start 495.44721875
transcript.pyannote[173].end 497.10096875
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 497.33721875
transcript.pyannote[174].end 498.40034375
transcript.pyannote[175].speaker SPEAKER_00
transcript.pyannote[175].start 499.12596875
transcript.pyannote[175].end 499.75034375
transcript.pyannote[176].speaker SPEAKER_00
transcript.pyannote[176].start 500.25659375
transcript.pyannote[176].end 511.02284375
transcript.pyannote[177].speaker SPEAKER_01
transcript.pyannote[177].start 503.69909375
transcript.pyannote[177].end 506.53409375
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 510.24659375
transcript.pyannote[178].end 515.42721875
transcript.pyannote[179].speaker SPEAKER_00
transcript.pyannote[179].start 511.68096875
transcript.pyannote[179].end 512.42346875
transcript.pyannote[180].speaker SPEAKER_00
transcript.pyannote[180].start 516.03471875
transcript.pyannote[180].end 520.65846875
transcript.pyannote[181].speaker SPEAKER_01
transcript.pyannote[181].start 519.39284375
transcript.pyannote[181].end 519.49409375
transcript.pyannote[182].speaker SPEAKER_01
transcript.pyannote[182].start 519.56159375
transcript.pyannote[182].end 519.62909375
transcript.pyannote[183].speaker SPEAKER_01
transcript.pyannote[183].start 521.35034375
transcript.pyannote[183].end 522.66659375
transcript.pyannote[184].speaker SPEAKER_01
transcript.pyannote[184].start 523.24034375
transcript.pyannote[184].end 524.48909375
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 525.68721875
transcript.pyannote[185].end 526.26096875
transcript.pyannote[186].speaker SPEAKER_01
transcript.pyannote[186].start 526.34534375
transcript.pyannote[186].end 528.74159375
transcript.pyannote[187].speaker SPEAKER_00
transcript.pyannote[187].start 528.74159375
transcript.pyannote[187].end 529.83846875
transcript.pyannote[188].speaker SPEAKER_01
transcript.pyannote[188].start 529.83846875
transcript.pyannote[188].end 530.31096875
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 529.87221875
transcript.pyannote[189].end 534.49596875
transcript.pyannote[190].speaker SPEAKER_01
transcript.pyannote[190].start 532.62284375
transcript.pyannote[190].end 533.36534375
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 534.41159375
transcript.pyannote[191].end 535.28909375
transcript.pyannote[192].speaker SPEAKER_00
transcript.pyannote[192].start 535.01909375
transcript.pyannote[192].end 536.79096875
transcript.pyannote[193].speaker SPEAKER_01
transcript.pyannote[193].start 535.45784375
transcript.pyannote[193].end 536.65596875
transcript.pyannote[194].speaker SPEAKER_01
transcript.pyannote[194].start 536.84159375
transcript.pyannote[194].end 537.16221875
transcript.pyannote[195].speaker SPEAKER_00
transcript.pyannote[195].start 537.16221875
transcript.pyannote[195].end 537.98909375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 537.98909375
transcript.pyannote[196].end 539.74409375
transcript.pyannote[197].speaker SPEAKER_00
transcript.pyannote[197].start 539.54159375
transcript.pyannote[197].end 540.73971875
transcript.pyannote[198].speaker SPEAKER_01
transcript.pyannote[198].start 540.94221875
transcript.pyannote[198].end 541.88721875
transcript.pyannote[199].speaker SPEAKER_00
transcript.pyannote[199].start 542.05596875
transcript.pyannote[199].end 542.54534375
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 542.54534375
transcript.pyannote[200].end 546.30846875
transcript.pyannote[201].speaker SPEAKER_00
transcript.pyannote[201].start 542.59596875
transcript.pyannote[201].end 550.99971875
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 547.18596875
transcript.pyannote[202].end 547.64159375
transcript.pyannote[203].speaker SPEAKER_00
transcript.pyannote[203].start 551.64096875
transcript.pyannote[203].end 553.24409375
transcript.pyannote[204].speaker SPEAKER_00
transcript.pyannote[204].start 554.02034375
transcript.pyannote[204].end 557.66534375
transcript.pyannote[205].speaker SPEAKER_01
transcript.pyannote[205].start 557.53034375
transcript.pyannote[205].end 558.57659375
transcript.pyannote[206].speaker SPEAKER_00
transcript.pyannote[206].start 558.10409375
transcript.pyannote[206].end 559.72409375
transcript.pyannote[207].speaker SPEAKER_00
transcript.pyannote[207].start 559.80846875
transcript.pyannote[207].end 565.25909375
transcript.pyannote[208].speaker SPEAKER_00
transcript.pyannote[208].start 565.29284375
transcript.pyannote[208].end 566.96346875
transcript.pyannote[209].speaker SPEAKER_01
transcript.pyannote[209].start 566.96346875
transcript.pyannote[209].end 572.17784375
transcript.pyannote[210].speaker SPEAKER_00
transcript.pyannote[210].start 568.29659375
transcript.pyannote[210].end 569.29221875
transcript.pyannote[211].speaker SPEAKER_00
transcript.pyannote[211].start 570.77721875
transcript.pyannote[211].end 573.05534375
transcript.pyannote[212].speaker SPEAKER_01
transcript.pyannote[212].start 573.05534375
transcript.pyannote[212].end 592.20846875
transcript.pyannote[213].speaker SPEAKER_00
transcript.pyannote[213].start 574.42221875
transcript.pyannote[213].end 575.43471875
transcript.pyannote[214].speaker SPEAKER_00
transcript.pyannote[214].start 583.33221875
transcript.pyannote[214].end 585.62721875
transcript.pyannote[215].speaker SPEAKER_00
transcript.pyannote[215].start 586.87596875
transcript.pyannote[215].end 588.19221875
transcript.pyannote[216].speaker SPEAKER_00
transcript.pyannote[216].start 589.06971875
transcript.pyannote[216].end 590.28471875
transcript.pyannote[217].speaker SPEAKER_01
transcript.pyannote[217].start 592.68096875
transcript.pyannote[217].end 595.07721875
transcript.pyannote[218].speaker SPEAKER_01
transcript.pyannote[218].start 595.34721875
transcript.pyannote[218].end 595.38096875
transcript.pyannote[219].speaker SPEAKER_00
transcript.pyannote[219].start 595.38096875
transcript.pyannote[219].end 595.49909375
transcript.pyannote[220].speaker SPEAKER_01
transcript.pyannote[220].start 595.49909375
transcript.pyannote[220].end 595.58346875
transcript.pyannote[221].speaker SPEAKER_00
transcript.pyannote[221].start 595.58346875
transcript.pyannote[221].end 595.92096875
transcript.pyannote[222].speaker SPEAKER_01
transcript.pyannote[222].start 595.92096875
transcript.pyannote[222].end 596.66346875
transcript.pyannote[223].speaker SPEAKER_00
transcript.pyannote[223].start 596.66346875
transcript.pyannote[223].end 597.22034375
transcript.pyannote[224].speaker SPEAKER_00
transcript.pyannote[224].start 598.03034375
transcript.pyannote[224].end 604.34159375
transcript.pyannote[225].speaker SPEAKER_01
transcript.pyannote[225].start 599.32971875
transcript.pyannote[225].end 600.10596875
transcript.pyannote[226].speaker SPEAKER_01
transcript.pyannote[226].start 602.13096875
transcript.pyannote[226].end 602.14784375
transcript.pyannote[227].speaker SPEAKER_00
transcript.pyannote[227].start 604.62846875
transcript.pyannote[227].end 605.21909375
transcript.pyannote[228].speaker SPEAKER_00
transcript.pyannote[228].start 605.82659375
transcript.pyannote[228].end 606.40034375
transcript.pyannote[229].speaker SPEAKER_01
transcript.pyannote[229].start 606.55221875
transcript.pyannote[229].end 606.82221875
transcript.pyannote[230].speaker SPEAKER_00
transcript.pyannote[230].start 607.05846875
transcript.pyannote[230].end 607.12596875
transcript.pyannote[231].speaker SPEAKER_00
transcript.pyannote[231].start 607.90221875
transcript.pyannote[231].end 610.46721875
transcript.pyannote[232].speaker SPEAKER_00
transcript.pyannote[232].start 611.00721875
transcript.pyannote[232].end 612.13784375
transcript.pyannote[233].speaker SPEAKER_00
transcript.pyannote[233].start 612.20534375
transcript.pyannote[233].end 612.25596875
transcript.pyannote[234].speaker SPEAKER_01
transcript.pyannote[234].start 612.25596875
transcript.pyannote[234].end 612.88034375
transcript.pyannote[235].speaker SPEAKER_00
transcript.pyannote[235].start 612.88034375
transcript.pyannote[235].end 612.89721875
transcript.pyannote[236].speaker SPEAKER_01
transcript.pyannote[236].start 612.89721875
transcript.pyannote[236].end 612.93096875
transcript.pyannote[237].speaker SPEAKER_00
transcript.pyannote[237].start 613.13346875
transcript.pyannote[237].end 613.92659375
transcript.pyannote[238].speaker SPEAKER_01
transcript.pyannote[238].start 614.28096875
transcript.pyannote[238].end 615.14159375
transcript.pyannote[239].speaker SPEAKER_00
transcript.pyannote[239].start 615.27659375
transcript.pyannote[239].end 616.39034375
transcript.pyannote[240].speaker SPEAKER_01
transcript.pyannote[240].start 616.39034375
transcript.pyannote[240].end 618.22971875
transcript.pyannote[241].speaker SPEAKER_00
transcript.pyannote[241].start 618.22971875
transcript.pyannote[241].end 620.65971875
transcript.pyannote[242].speaker SPEAKER_01
transcript.pyannote[242].start 619.44471875
transcript.pyannote[242].end 622.48221875
transcript.pyannote[243].speaker SPEAKER_00
transcript.pyannote[243].start 622.66784375
transcript.pyannote[243].end 628.10159375
transcript.pyannote[244].speaker SPEAKER_01
transcript.pyannote[244].start 627.59534375
transcript.pyannote[244].end 628.84409375
transcript.pyannote[245].speaker SPEAKER_00
transcript.pyannote[245].start 628.43909375
transcript.pyannote[245].end 628.69221875
transcript.pyannote[246].speaker SPEAKER_00
transcript.pyannote[246].start 628.84409375
transcript.pyannote[246].end 629.94096875
transcript.pyannote[247].speaker SPEAKER_01
transcript.pyannote[247].start 629.94096875
transcript.pyannote[247].end 631.40909375
transcript.pyannote[248].speaker SPEAKER_00
transcript.pyannote[248].start 630.68346875
transcript.pyannote[248].end 633.07971875
transcript.pyannote[249].speaker SPEAKER_01
transcript.pyannote[249].start 631.81409375
transcript.pyannote[249].end 632.37096875
transcript.pyannote[250].speaker SPEAKER_01
transcript.pyannote[250].start 633.07971875
transcript.pyannote[250].end 636.70784375
transcript.pyannote[251].speaker SPEAKER_00
transcript.pyannote[251].start 637.01159375
transcript.pyannote[251].end 647.84534375
transcript.pyannote[252].speaker SPEAKER_01
transcript.pyannote[252].start 647.81159375
transcript.pyannote[252].end 649.26284375
transcript.pyannote[253].speaker SPEAKER_00
transcript.pyannote[253].start 649.60034375
transcript.pyannote[253].end 650.30909375
transcript.pyannote[254].speaker SPEAKER_01
transcript.pyannote[254].start 650.03909375
transcript.pyannote[254].end 651.22034375
transcript.pyannote[255].speaker SPEAKER_01
transcript.pyannote[255].start 651.25409375
transcript.pyannote[255].end 653.83596875
transcript.pyannote[256].speaker SPEAKER_00
transcript.pyannote[256].start 651.52409375
transcript.pyannote[256].end 653.88659375
transcript.pyannote[257].speaker SPEAKER_01
transcript.pyannote[257].start 653.85284375
transcript.pyannote[257].end 664.23096875
transcript.pyannote[258].speaker SPEAKER_00
transcript.pyannote[258].start 658.51034375
transcript.pyannote[258].end 659.42159375
transcript.pyannote[259].speaker SPEAKER_00
transcript.pyannote[259].start 663.16784375
transcript.pyannote[259].end 668.78721875
transcript.pyannote[260].speaker SPEAKER_00
transcript.pyannote[260].start 669.25971875
transcript.pyannote[260].end 672.55034375
transcript.pyannote[261].speaker SPEAKER_01
transcript.pyannote[261].start 672.16221875
transcript.pyannote[261].end 676.98846875
transcript.pyannote[262].speaker SPEAKER_00
transcript.pyannote[262].start 673.84971875
transcript.pyannote[262].end 674.91284375
transcript.pyannote[263].speaker SPEAKER_00
transcript.pyannote[263].start 675.67221875
transcript.pyannote[263].end 676.63409375
transcript.pyannote[264].speaker SPEAKER_00
transcript.pyannote[264].start 676.98846875
transcript.pyannote[264].end 681.34221875
transcript.pyannote[265].speaker SPEAKER_00
transcript.pyannote[265].start 681.71346875
transcript.pyannote[265].end 683.50221875
transcript.pyannote[266].speaker SPEAKER_00
transcript.pyannote[266].start 684.07596875
transcript.pyannote[266].end 685.20659375
transcript.pyannote[267].speaker SPEAKER_01
transcript.pyannote[267].start 685.20659375
transcript.pyannote[267].end 685.25721875
transcript.pyannote[268].speaker SPEAKER_00
transcript.pyannote[268].start 685.40909375
transcript.pyannote[268].end 690.97784375
transcript.pyannote[269].speaker SPEAKER_01
transcript.pyannote[269].start 687.77159375
transcript.pyannote[269].end 687.99096875
transcript.pyannote[270].speaker SPEAKER_01
transcript.pyannote[270].start 689.71221875
transcript.pyannote[270].end 693.18846875
transcript.pyannote[271].speaker SPEAKER_01
transcript.pyannote[271].start 693.93096875
transcript.pyannote[271].end 694.74096875
transcript.pyannote[272].speaker SPEAKER_01
transcript.pyannote[272].start 695.82096875
transcript.pyannote[272].end 705.03471875
transcript.whisperx[0].start 2.05
transcript.whisperx[0].end 4.391
transcript.whisperx[0].text 中央印製廠林總總台你好外匯存底
transcript.whisperx[1].start 21.408
transcript.whisperx[1].end 45.851
transcript.whisperx[1].text 很高啊還好啦 是不是一個秀肌肉的好機會喔 是事實上我們沒有這個意思我們沒有這個意思我們發現說我們外匯存體持續在高升可是為什麼全世界很多國家外匯存體不升還減
transcript.whisperx[2].start 50.228
transcript.whisperx[2].end 66.308
transcript.whisperx[2].text 有的國家的外匯存底不升還減也有一些的國家是確實是因為他的資金流出去太多第二個他的外匯存底投資的成效不夠好
transcript.whisperx[3].start 69.221
transcript.whisperx[3].end 94.293
transcript.whisperx[3].text 黃金跟我們的儲備是這樣有不同的幣別黃金等等大概這五年前到現在產生了若干的變化很多人看在買黃金你看全世界我們講這五年來黃金購入買最多的是哪幾個國家
transcript.whisperx[4].start 96.505
transcript.whisperx[4].end 117.745
transcript.whisperx[4].text 大概是Russia跟中國大陸的中國大陸跟Russia德國有沒有買?沒有,德國沒有買,美國沒有買,英國也沒有買這些先進的國家都沒有買,日本也沒有買法國好像也沒有買南韓?
transcript.whisperx[5].start 118.866
transcript.whisperx[5].end 142.034
transcript.whisperx[5].text 南韓沒有買最近沒有買好像他前一波有買他前一波的時候有買不過那一次他買的時候據我了解他買的時候是低但是他有上漲但是後來下來他嚇了一跳
transcript.whisperx[6].start 143.465
transcript.whisperx[6].end 168.365
transcript.whisperx[6].text 結果後來他就不敢買但是後來黃金的價格一直上去黃金漲了那麼多央行有沒有買我們沒有買我們跟其他主要的國家來比較的時候我們都沒有買所以總裁你對美元是不是有很大的信心
transcript.whisperx[7].start 172.007
transcript.whisperx[7].end 194.061
transcript.whisperx[7].text 也不是說我對美元有特別的信心那也不是說對它沒有信心我們是比較了各個幣別來講的話相對的那也不是說因為我們對美元有絕對的信心然後我們的外匯存底美元的部位才會比較大不過我跟委員報告了
transcript.whisperx[8].start 194.864
transcript.whisperx[8].end 218.103
transcript.whisperx[8].text 我們的進出口廠商百分之九十到九十五它的報價都是用什麼它都是用美元那如果說在這種它的報價都是百分之九十到九十五都是用美元來報價的時候呢那我們的外匯存體是不是也要因應它那所以呢如果說我們把它降到百分之八十
transcript.whisperx[9].start 219.251
transcript.whisperx[9].end 245.203
transcript.whisperx[9].text 你也不能就說我們對美元特別有信心這是第一點也就是說我們的進出口廠商他大部分的報價都是用美元的時候那當然我們的存底就是以美元為主這是第一點第二點以整個全球的一個貨幣制度來看的話呢美元他就是共同的貨幣現在全世界你的說法最強就是美元
transcript.whisperx[10].start 246.063
transcript.whisperx[10].end 263.358
transcript.whisperx[10].text 所以我們外匯存體持有美元的比重也很高啊那當然啊我剛剛在說第一個我們的進出口廠商的報價大部分90%到95%都是用美元啊那我看你也很聰明啊你美元大概我們持有有沒有65%什麼
transcript.whisperx[11].start 265.834
transcript.whisperx[11].end 283.876
transcript.whisperx[11].text 美元的持有,占我們的外匯存底有沒有65%?應該有有沒有接近七成?應該有有啊,好像比重又變高了應該有啊那占七成,那其他百分之三十是什麼?這就我們diversify
transcript.whisperx[12].start 284.577
transcript.whisperx[12].end 285.798
transcript.whisperx[12].text 第二比重的話我們要看情況有的時候是歐元 有些時候是人民幣 有些時候是其他的貨幣
transcript.whisperx[13].start 308.249
transcript.whisperx[13].end 330.521
transcript.whisperx[13].text 為什麼你會想持有人民幣因為我跟委員報告啦人民幣是因為我們台灣跟中國大陸的一個貿易呢他的這個要清算的時候呢人民幣就是本身他就因為我們跟他的貿易很大所以也就是說我們也必須要握有部分的人民幣作為
transcript.whisperx[14].start 331.562
transcript.whisperx[14].end 355.283
transcript.whisperx[14].text 我們的廠商跟中國大陸的一個廠商的清算人民幣的持有有沒有佔百分之五上上下下上上下?那Range大概有多少Range有沒有超過3%我現在忘了啦 待會底下的時候我再告訴你我跟委員報告你會不會再加持人民幣
transcript.whisperx[15].start 356.784
transcript.whisperx[15].end 371.902
transcript.whisperx[15].text 你會不會再增加持有人民幣我跟委員報告人民幣以前我們會多持有它有兩個因素第一個因素就是說我們跟中國大陸的一個貿易的往來大
transcript.whisperx[16].start 372.54
transcript.whisperx[16].end 388.157
transcript.whisperx[16].text 而且我們的廠商有一些它的收支有一部分是用人民幣這是第一點第二點當時的人民幣的利率非常高好像甚至都比美銀高
transcript.whisperx[17].start 389.458
transcript.whisperx[17].end 403.411
transcript.whisperx[17].text 所以在這種情況之下我們都有一個比重就是歐元人民幣後來就下降下來為什麼會下降下來現在下降多少下降下來我現在不太曉得今天有沒有剩大概5%
transcript.whisperx[18].start 405.012
transcript.whisperx[18].end 420.361
transcript.whisperx[18].text 應該是低一點歐元的持有大概有多少歐元的持有也大概是差不多我們大部分第二個就是說我們第二個幣幣我同事告訴我我們第二個幣幣就是歐元第二個是歐元第三個是人民幣第四個
transcript.whisperx[19].start 422.422
transcript.whisperx[19].end 427.285
transcript.whisperx[19].text 我們第四個的話就是說英鎊、澳幣、日元這些都是有加幣也有也蠻多元化的啦你會不會考慮說現在全世界變化很快美伊戰爭、俄烏戰爭打完以後
transcript.whisperx[20].start 449.775
transcript.whisperx[20].end 465.824
transcript.whisperx[20].text 美金會不會變弱?因為全世界都贊成啊這個委員做這樣的一個預測我記得啊不知道對不對我記得啊就是說去年初去年初或是去年中以後大家就說美國要降息所以美元都會會弱
transcript.whisperx[21].start 470.566
transcript.whisperx[21].end 479.252
transcript.whisperx[21].text 但是好像也沒有這麼一回事從最近來看的話它的指數是降到96但是最近都又跑到100以上所以我跟委員報告匯率的預測很難你要在這邊叫我來預測說美元會強會弱誰知道美元發行的基礎它是用
transcript.whisperx[22].start 499.421
transcript.whisperx[22].end 520.096
transcript.whisperx[22].text 黃金來做發行準備對不對也不是那美國發行美金是用什麼做準備我跟委員報告等一下那我們新台幣的發行是用什麼我們是用黃金做準備黃金還有我們的外存底黃金很好啦因為一閃一閃亮晶晶我們黃金有多少噸我們黃金有480幾噸
transcript.whisperx[23].start 530.44
transcript.whisperx[23].end 537.668
transcript.whisperx[23].text 423噸423好像是一個護國神山我們台幣的護國神山有沒有減少我們沒有減少有沒有增加沒有增加
transcript.whisperx[24].start 544.295
transcript.whisperx[24].end 559.271
transcript.whisperx[24].text 我們手上都是美金美債那你會不會考慮說萬一萬一美元來一天因為走強以後就必定會走弱嘛你會不會把手上
transcript.whisperx[25].start 559.952
transcript.whisperx[25].end 574.606
transcript.whisperx[25].text 的外匯存底來轉化來買一些黃金我們也有考慮只是說有考慮還沒做是還沒有做而已考慮那個點大概什麼時候會做我怎麼會曉得只是說我們認為
transcript.whisperx[26].start 576.067
transcript.whisperx[26].end 589.993
transcript.whisperx[26].text 我們認為就是說我們覺得是一個很好的時機是很好的時點的時候呢中央銀行會進去我從來沒有聽過你講這句話但是我跟委員報告黃金貴不貴黃金貴不貴以現在來講的話我總覺得它是貴現在貴喔所以你覺得現在貴貴與不貴事實上跟現在我們都是靠美金美元可是
transcript.whisperx[27].start 606.048
transcript.whisperx[27].end 632.857
transcript.whisperx[27].text 總裁啊美國他的黃金儲備啊他黃金還在不在啊他在啊你有見過嗎我看過啊你到哪裡看的我看過我在美國看的美國有四個地方你在哪個地方看到我在紐約看的紐約紐約他是因為聯邦銀行的這個說黃金放那邊嗎對啦那個不是最大宗對啦最大宗是在肯特基吧
transcript.whisperx[28].start 634.719
transcript.whisperx[28].end 649.115
transcript.whisperx[28].text 這個我就不曉得啦反正我看過啦肯特基那個量是最大的連那個川普啊他Elon Musk上去的時候說50年沒人去看過黃金部長還在不在是啦 應該在啦應該在喔
transcript.whisperx[29].start 651.957
transcript.whisperx[29].end 668.288
transcript.whisperx[29].text 眼見為憑 改天你可不可以帶我們去看一下我想中央銀行 全球的中央銀行都是很謹慎的啦所以你們懷疑中央銀行還在不在啊那當然在啊我們台灣的我應該覺得我有去看過啦我們主席也去看過
transcript.whisperx[30].start 669.332
transcript.whisperx[30].end 690.541
transcript.whisperx[30].text 可是美國的我沒去看過啊 總裁你也沒看過啊不過我將心比心啦 中央銀行都是很謹慎的啦謝謝 榮民財委員那個總裁最後一句話萬一如果去看 黃金不在對美元會產生什麼樣的變化 下期分解下次再跟我說 這個機率是零啦好 謝謝
transcript.whisperx[31].start 695.914
transcript.whisperx[31].end 704.333
transcript.whisperx[31].text 我因為對他們非常有信心所以我在財政委員會14年了但是我沒有去過他們新店文員來 下一個諮詢委員請陳玉珍委員質詢