iVOD / 150783

Field Value
IVOD_ID 150783
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/150783
日期 2024-04-01
會議資料.會議代碼 委員會-11-1-20-6
會議資料.會議代碼:str 第11屆第1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 1
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1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 2024-04-01T11:27:26+08:00
結束時間 2024-04-01T11:40:30+08:00
影片長度 00:13:04
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/01d093d00f1a07c08bd706e6aade18bcee14ad7ded5d841af8ba9b0039caa7a6cab6589a64c104af5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 顏寬恒
委員發言時間 11:27:26 - 11:40:30
會議時間 2024-04-01T09:00:00+08:00
會議名稱 立法院第11屆第1會期財政委員會第6次全體委員會議(事由:邀請財政部莊部長翠雲、金融監督管理委員會黃主任委員天牧、內政部、國家發展委員會就「如何積極推動金融業投注國內公共建設,並達成社宅百萬戶之政策目標」進行專題報告,並備質詢。 【4月1日及3日二天一次會】)
transcript.pyannote[0].speaker SPEAKER_04
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 0.89159375
transcript.pyannote[1].speaker SPEAKER_04
transcript.pyannote[1].start 2.02221875
transcript.pyannote[1].end 3.10221875
transcript.pyannote[2].speaker SPEAKER_04
transcript.pyannote[2].start 3.74346875
transcript.pyannote[2].end 5.17784375
transcript.pyannote[3].speaker SPEAKER_04
transcript.pyannote[3].start 5.56596875
transcript.pyannote[3].end 6.30846875
transcript.pyannote[4].speaker SPEAKER_04
transcript.pyannote[4].start 7.54034375
transcript.pyannote[4].end 8.82284375
transcript.pyannote[5].speaker SPEAKER_04
transcript.pyannote[5].start 9.46409375
transcript.pyannote[5].end 10.51034375
transcript.pyannote[6].speaker SPEAKER_04
transcript.pyannote[6].start 10.78034375
transcript.pyannote[6].end 11.48909375
transcript.pyannote[7].speaker SPEAKER_04
transcript.pyannote[7].start 11.65784375
transcript.pyannote[7].end 19.13346875
transcript.pyannote[8].speaker SPEAKER_04
transcript.pyannote[8].start 28.81971875
transcript.pyannote[8].end 32.97096875
transcript.pyannote[9].speaker SPEAKER_04
transcript.pyannote[9].start 33.24096875
transcript.pyannote[9].end 35.60346875
transcript.pyannote[10].speaker SPEAKER_04
transcript.pyannote[10].start 36.16034375
transcript.pyannote[10].end 41.05409375
transcript.pyannote[11].speaker SPEAKER_04
transcript.pyannote[11].start 41.27346875
transcript.pyannote[11].end 41.72909375
transcript.pyannote[12].speaker SPEAKER_04
transcript.pyannote[12].start 42.40409375
transcript.pyannote[12].end 43.29846875
transcript.pyannote[13].speaker SPEAKER_04
transcript.pyannote[13].start 43.68659375
transcript.pyannote[13].end 46.62284375
transcript.pyannote[14].speaker SPEAKER_04
transcript.pyannote[14].start 47.26409375
transcript.pyannote[14].end 47.92221875
transcript.pyannote[15].speaker SPEAKER_04
transcript.pyannote[15].start 48.42846875
transcript.pyannote[15].end 52.46159375
transcript.pyannote[16].speaker SPEAKER_04
transcript.pyannote[16].start 53.27159375
transcript.pyannote[16].end 56.52846875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 58.08096875
transcript.pyannote[17].end 71.88471875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 72.27284375
transcript.pyannote[18].end 74.11221875
transcript.pyannote[19].speaker SPEAKER_04
transcript.pyannote[19].start 74.34846875
transcript.pyannote[19].end 77.82471875
transcript.pyannote[20].speaker SPEAKER_04
transcript.pyannote[20].start 78.53346875
transcript.pyannote[20].end 79.91721875
transcript.pyannote[21].speaker SPEAKER_04
transcript.pyannote[21].start 80.89596875
transcript.pyannote[21].end 85.48596875
transcript.pyannote[22].speaker SPEAKER_04
transcript.pyannote[22].start 85.68846875
transcript.pyannote[22].end 86.78534375
transcript.pyannote[23].speaker SPEAKER_04
transcript.pyannote[23].start 87.17346875
transcript.pyannote[23].end 92.03346875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 92.40471875
transcript.pyannote[24].end 98.37846875
transcript.pyannote[25].speaker SPEAKER_04
transcript.pyannote[25].start 95.45909375
transcript.pyannote[25].end 95.57721875
transcript.pyannote[26].speaker SPEAKER_04
transcript.pyannote[26].start 98.02409375
transcript.pyannote[26].end 105.63471875
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 107.30534375
transcript.pyannote[27].end 107.82846875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 108.30096875
transcript.pyannote[28].end 109.90409375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 109.95471875
transcript.pyannote[29].end 115.94534375
transcript.pyannote[30].speaker SPEAKER_04
transcript.pyannote[30].start 116.51909375
transcript.pyannote[30].end 118.22346875
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 118.29096875
transcript.pyannote[31].end 127.04909375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 127.20096875
transcript.pyannote[32].end 132.04409375
transcript.pyannote[33].speaker SPEAKER_04
transcript.pyannote[33].start 131.65596875
transcript.pyannote[33].end 132.02721875
transcript.pyannote[34].speaker SPEAKER_04
transcript.pyannote[34].start 132.04409375
transcript.pyannote[34].end 133.59659375
transcript.pyannote[35].speaker SPEAKER_04
transcript.pyannote[35].start 134.00159375
transcript.pyannote[35].end 137.54534375
transcript.pyannote[36].speaker SPEAKER_04
transcript.pyannote[36].start 138.11909375
transcript.pyannote[36].end 138.91221875
transcript.pyannote[37].speaker SPEAKER_04
transcript.pyannote[37].start 144.71721875
transcript.pyannote[37].end 146.21909375
transcript.pyannote[38].speaker SPEAKER_04
transcript.pyannote[38].start 146.69159375
transcript.pyannote[38].end 161.06909375
transcript.pyannote[39].speaker SPEAKER_04
transcript.pyannote[39].start 161.54159375
transcript.pyannote[39].end 162.08159375
transcript.pyannote[40].speaker SPEAKER_04
transcript.pyannote[40].start 162.57096875
transcript.pyannote[40].end 163.81971875
transcript.pyannote[41].speaker SPEAKER_04
transcript.pyannote[41].start 164.17409375
transcript.pyannote[41].end 165.06846875
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 165.06846875
transcript.pyannote[42].end 196.13534375
transcript.pyannote[43].speaker SPEAKER_04
transcript.pyannote[43].start 197.13096875
transcript.pyannote[43].end 197.53596875
transcript.pyannote[44].speaker SPEAKER_04
transcript.pyannote[44].start 198.59909375
transcript.pyannote[44].end 207.45846875
transcript.pyannote[45].speaker SPEAKER_04
transcript.pyannote[45].start 208.01534375
transcript.pyannote[45].end 209.39909375
transcript.pyannote[46].speaker SPEAKER_04
transcript.pyannote[46].start 209.73659375
transcript.pyannote[46].end 210.73221875
transcript.pyannote[47].speaker SPEAKER_04
transcript.pyannote[47].start 211.44096875
transcript.pyannote[47].end 214.30971875
transcript.pyannote[48].speaker SPEAKER_04
transcript.pyannote[48].start 214.54596875
transcript.pyannote[48].end 217.06034375
transcript.pyannote[49].speaker SPEAKER_04
transcript.pyannote[49].start 217.58346875
transcript.pyannote[49].end 219.57471875
transcript.pyannote[50].speaker SPEAKER_04
transcript.pyannote[50].start 220.28346875
transcript.pyannote[50].end 221.19471875
transcript.pyannote[51].speaker SPEAKER_04
transcript.pyannote[51].start 221.39721875
transcript.pyannote[51].end 224.36721875
transcript.pyannote[52].speaker SPEAKER_04
transcript.pyannote[52].start 224.89034375
transcript.pyannote[52].end 227.91096875
transcript.pyannote[53].speaker SPEAKER_04
transcript.pyannote[53].start 228.29909375
transcript.pyannote[53].end 230.34096875
transcript.pyannote[54].speaker SPEAKER_04
transcript.pyannote[54].start 230.74596875
transcript.pyannote[54].end 232.38284375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 232.92284375
transcript.pyannote[55].end 253.13909375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 253.32471875
transcript.pyannote[56].end 281.20221875
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 281.35409375
transcript.pyannote[57].end 288.99846875
transcript.pyannote[58].speaker SPEAKER_04
transcript.pyannote[58].start 288.28971875
transcript.pyannote[58].end 292.13721875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 289.97721875
transcript.pyannote[59].end 290.26409375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 291.88409375
transcript.pyannote[60].end 298.33034375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 298.49909375
transcript.pyannote[61].end 330.02159375
transcript.pyannote[62].speaker SPEAKER_04
transcript.pyannote[62].start 330.34221875
transcript.pyannote[62].end 332.46846875
transcript.pyannote[63].speaker SPEAKER_04
transcript.pyannote[63].start 332.80596875
transcript.pyannote[63].end 336.06284375
transcript.pyannote[64].speaker SPEAKER_04
transcript.pyannote[64].start 336.11346875
transcript.pyannote[64].end 337.44659375
transcript.pyannote[65].speaker SPEAKER_04
transcript.pyannote[65].start 338.07096875
transcript.pyannote[65].end 339.42096875
transcript.pyannote[66].speaker SPEAKER_04
transcript.pyannote[66].start 339.62346875
transcript.pyannote[66].end 342.84659375
transcript.pyannote[67].speaker SPEAKER_04
transcript.pyannote[67].start 342.98159375
transcript.pyannote[67].end 343.84221875
transcript.pyannote[68].speaker SPEAKER_04
transcript.pyannote[68].start 344.28096875
transcript.pyannote[68].end 345.61409375
transcript.pyannote[69].speaker SPEAKER_04
transcript.pyannote[69].start 345.81659375
transcript.pyannote[69].end 348.41534375
transcript.pyannote[70].speaker SPEAKER_04
transcript.pyannote[70].start 348.49971875
transcript.pyannote[70].end 359.43471875
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 351.67221875
transcript.pyannote[71].end 351.80721875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 351.97596875
transcript.pyannote[72].end 352.24596875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 359.08034375
transcript.pyannote[73].end 359.11409375
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 359.11409375
transcript.pyannote[74].end 359.90721875
transcript.pyannote[75].speaker SPEAKER_04
transcript.pyannote[75].start 359.67096875
transcript.pyannote[75].end 359.68784375
transcript.pyannote[76].speaker SPEAKER_04
transcript.pyannote[76].start 359.82284375
transcript.pyannote[76].end 367.23096875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 367.50096875
transcript.pyannote[77].end 377.30534375
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 377.44034375
transcript.pyannote[78].end 381.03471875
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 381.10221875
transcript.pyannote[79].end 388.17284375
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 388.35846875
transcript.pyannote[80].end 407.78159375
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 396.03659375
transcript.pyannote[81].end 396.52596875
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 407.98409375
transcript.pyannote[82].end 448.26471875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 411.89909375
transcript.pyannote[83].end 412.20284375
transcript.pyannote[84].speaker SPEAKER_04
transcript.pyannote[84].start 445.98659375
transcript.pyannote[84].end 447.18471875
transcript.pyannote[85].speaker SPEAKER_04
transcript.pyannote[85].start 448.70346875
transcript.pyannote[85].end 454.62659375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 449.88471875
transcript.pyannote[86].end 452.19659375
transcript.pyannote[87].speaker SPEAKER_04
transcript.pyannote[87].start 455.13284375
transcript.pyannote[87].end 455.85846875
transcript.pyannote[88].speaker SPEAKER_04
transcript.pyannote[88].start 459.13221875
transcript.pyannote[88].end 460.73534375
transcript.pyannote[89].speaker SPEAKER_04
transcript.pyannote[89].start 461.34284375
transcript.pyannote[89].end 461.96721875
transcript.pyannote[90].speaker SPEAKER_04
transcript.pyannote[90].start 462.45659375
transcript.pyannote[90].end 480.83346875
transcript.pyannote[91].speaker SPEAKER_04
transcript.pyannote[91].start 481.50846875
transcript.pyannote[91].end 482.09909375
transcript.pyannote[92].speaker SPEAKER_04
transcript.pyannote[92].start 482.25096875
transcript.pyannote[92].end 485.30534375
transcript.pyannote[93].speaker SPEAKER_04
transcript.pyannote[93].start 485.76096875
transcript.pyannote[93].end 488.47784375
transcript.pyannote[94].speaker SPEAKER_04
transcript.pyannote[94].start 488.57909375
transcript.pyannote[94].end 500.27346875
transcript.pyannote[95].speaker SPEAKER_03
transcript.pyannote[95].start 492.12284375
transcript.pyannote[95].end 492.19034375
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 492.19034375
transcript.pyannote[96].end 492.20721875
transcript.pyannote[97].speaker SPEAKER_04
transcript.pyannote[97].start 500.52659375
transcript.pyannote[97].end 502.24784375
transcript.pyannote[98].speaker SPEAKER_04
transcript.pyannote[98].start 502.38284375
transcript.pyannote[98].end 505.25159375
transcript.pyannote[99].speaker SPEAKER_04
transcript.pyannote[99].start 505.47096875
transcript.pyannote[99].end 508.96409375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 509.57159375
transcript.pyannote[100].end 513.60471875
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 513.85784375
transcript.pyannote[101].end 523.96596875
transcript.pyannote[102].speaker SPEAKER_04
transcript.pyannote[102].start 523.96596875
transcript.pyannote[102].end 525.97409375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 525.97409375
transcript.pyannote[103].end 529.99034375
transcript.pyannote[104].speaker SPEAKER_04
transcript.pyannote[104].start 528.42096875
transcript.pyannote[104].end 528.80909375
transcript.pyannote[105].speaker SPEAKER_04
transcript.pyannote[105].start 529.99034375
transcript.pyannote[105].end 530.15909375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 530.64846875
transcript.pyannote[106].end 530.66534375
transcript.pyannote[107].speaker SPEAKER_04
transcript.pyannote[107].start 530.66534375
transcript.pyannote[107].end 530.74971875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 530.74971875
transcript.pyannote[108].end 530.76659375
transcript.pyannote[109].speaker SPEAKER_04
transcript.pyannote[109].start 530.76659375
transcript.pyannote[109].end 530.98596875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 530.98596875
transcript.pyannote[110].end 531.01971875
transcript.pyannote[111].speaker SPEAKER_04
transcript.pyannote[111].start 531.42471875
transcript.pyannote[111].end 531.44159375
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 531.44159375
transcript.pyannote[112].end 531.45846875
transcript.pyannote[113].speaker SPEAKER_04
transcript.pyannote[113].start 531.45846875
transcript.pyannote[113].end 531.52596875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 531.52596875
transcript.pyannote[114].end 531.96471875
transcript.pyannote[115].speaker SPEAKER_04
transcript.pyannote[115].start 531.96471875
transcript.pyannote[115].end 532.92659375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 532.92659375
transcript.pyannote[116].end 534.74909375
transcript.pyannote[117].speaker SPEAKER_04
transcript.pyannote[117].start 532.97721875
transcript.pyannote[117].end 533.82096875
transcript.pyannote[118].speaker SPEAKER_04
transcript.pyannote[118].start 533.92221875
transcript.pyannote[118].end 535.18784375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 535.18784375
transcript.pyannote[119].end 535.28909375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 535.37346875
transcript.pyannote[120].end 535.42409375
transcript.pyannote[121].speaker SPEAKER_04
transcript.pyannote[121].start 535.42409375
transcript.pyannote[121].end 541.21221875
transcript.pyannote[122].speaker SPEAKER_04
transcript.pyannote[122].start 547.38846875
transcript.pyannote[122].end 549.56534375
transcript.pyannote[123].speaker SPEAKER_04
transcript.pyannote[123].start 549.98721875
transcript.pyannote[123].end 564.60096875
transcript.pyannote[124].speaker SPEAKER_04
transcript.pyannote[124].start 565.07346875
transcript.pyannote[124].end 565.95096875
transcript.pyannote[125].speaker SPEAKER_04
transcript.pyannote[125].start 566.11971875
transcript.pyannote[125].end 567.68909375
transcript.pyannote[126].speaker SPEAKER_04
transcript.pyannote[126].start 567.99284375
transcript.pyannote[126].end 570.55784375
transcript.pyannote[127].speaker SPEAKER_04
transcript.pyannote[127].start 570.57471875
transcript.pyannote[127].end 572.12721875
transcript.pyannote[128].speaker SPEAKER_04
transcript.pyannote[128].start 572.38034375
transcript.pyannote[128].end 581.27346875
transcript.pyannote[129].speaker SPEAKER_04
transcript.pyannote[129].start 581.77971875
transcript.pyannote[129].end 597.25409375
transcript.pyannote[130].speaker SPEAKER_04
transcript.pyannote[130].start 597.52409375
transcript.pyannote[130].end 598.03034375
transcript.pyannote[131].speaker SPEAKER_04
transcript.pyannote[131].start 598.50284375
transcript.pyannote[131].end 605.05034375
transcript.pyannote[132].speaker SPEAKER_04
transcript.pyannote[132].start 605.47221875
transcript.pyannote[132].end 606.24846875
transcript.pyannote[133].speaker SPEAKER_04
transcript.pyannote[133].start 606.70409375
transcript.pyannote[133].end 619.96784375
transcript.pyannote[134].speaker SPEAKER_03
transcript.pyannote[134].start 619.96784375
transcript.pyannote[134].end 620.01846875
transcript.pyannote[135].speaker SPEAKER_04
transcript.pyannote[135].start 620.37284375
transcript.pyannote[135].end 620.54159375
transcript.pyannote[136].speaker SPEAKER_03
transcript.pyannote[136].start 620.54159375
transcript.pyannote[136].end 653.98784375
transcript.pyannote[137].speaker SPEAKER_04
transcript.pyannote[137].start 620.55846875
transcript.pyannote[137].end 621.28409375
transcript.pyannote[138].speaker SPEAKER_04
transcript.pyannote[138].start 653.98784375
transcript.pyannote[138].end 655.54034375
transcript.pyannote[139].speaker SPEAKER_04
transcript.pyannote[139].start 655.96221875
transcript.pyannote[139].end 656.82284375
transcript.pyannote[140].speaker SPEAKER_04
transcript.pyannote[140].start 657.85221875
transcript.pyannote[140].end 662.39159375
transcript.pyannote[141].speaker SPEAKER_04
transcript.pyannote[141].start 662.64471875
transcript.pyannote[141].end 664.53471875
transcript.pyannote[142].speaker SPEAKER_04
transcript.pyannote[142].start 664.90596875
transcript.pyannote[142].end 666.52596875
transcript.pyannote[143].speaker SPEAKER_04
transcript.pyannote[143].start 666.89721875
transcript.pyannote[143].end 667.43721875
transcript.pyannote[144].speaker SPEAKER_04
transcript.pyannote[144].start 667.84221875
transcript.pyannote[144].end 668.78721875
transcript.pyannote[145].speaker SPEAKER_04
transcript.pyannote[145].start 669.09096875
transcript.pyannote[145].end 674.87909375
transcript.pyannote[146].speaker SPEAKER_04
transcript.pyannote[146].start 675.30096875
transcript.pyannote[146].end 675.84096875
transcript.pyannote[147].speaker SPEAKER_04
transcript.pyannote[147].start 676.02659375
transcript.pyannote[147].end 677.89971875
transcript.pyannote[148].speaker SPEAKER_04
transcript.pyannote[148].start 678.03471875
transcript.pyannote[148].end 698.57159375
transcript.pyannote[149].speaker SPEAKER_03
transcript.pyannote[149].start 698.57159375
transcript.pyannote[149].end 699.04409375
transcript.pyannote[150].speaker SPEAKER_04
transcript.pyannote[150].start 699.04409375
transcript.pyannote[150].end 701.18721875
transcript.pyannote[151].speaker SPEAKER_03
transcript.pyannote[151].start 701.18721875
transcript.pyannote[151].end 707.70096875
transcript.pyannote[152].speaker SPEAKER_04
transcript.pyannote[152].start 706.92471875
transcript.pyannote[152].end 712.98284375
transcript.pyannote[153].speaker SPEAKER_03
transcript.pyannote[153].start 708.03846875
transcript.pyannote[153].end 708.46034375
transcript.pyannote[154].speaker SPEAKER_04
transcript.pyannote[154].start 713.79284375
transcript.pyannote[154].end 714.68721875
transcript.pyannote[155].speaker SPEAKER_04
transcript.pyannote[155].start 715.51409375
transcript.pyannote[155].end 729.63846875
transcript.pyannote[156].speaker SPEAKER_03
transcript.pyannote[156].start 730.07721875
transcript.pyannote[156].end 730.09409375
transcript.pyannote[157].speaker SPEAKER_04
transcript.pyannote[157].start 730.09409375
transcript.pyannote[157].end 731.03909375
transcript.pyannote[158].speaker SPEAKER_03
transcript.pyannote[158].start 731.03909375
transcript.pyannote[158].end 746.56409375
transcript.pyannote[159].speaker SPEAKER_04
transcript.pyannote[159].start 745.36596875
transcript.pyannote[159].end 746.54721875
transcript.pyannote[160].speaker SPEAKER_04
transcript.pyannote[160].start 746.56409375
transcript.pyannote[160].end 746.59784375
transcript.pyannote[161].speaker SPEAKER_03
transcript.pyannote[161].start 746.59784375
transcript.pyannote[161].end 746.96909375
transcript.pyannote[162].speaker SPEAKER_04
transcript.pyannote[162].start 746.96909375
transcript.pyannote[162].end 755.23784375
transcript.pyannote[163].speaker SPEAKER_04
transcript.pyannote[163].start 755.38971875
transcript.pyannote[163].end 757.11096875
transcript.pyannote[164].speaker SPEAKER_03
transcript.pyannote[164].start 757.11096875
transcript.pyannote[164].end 763.96221875
transcript.pyannote[165].speaker SPEAKER_04
transcript.pyannote[165].start 763.28721875
transcript.pyannote[165].end 763.64159375
transcript.pyannote[166].speaker SPEAKER_04
transcript.pyannote[166].start 763.96221875
transcript.pyannote[166].end 765.56534375
transcript.pyannote[167].speaker SPEAKER_03
transcript.pyannote[167].start 765.86909375
transcript.pyannote[167].end 765.95346875
transcript.pyannote[168].speaker SPEAKER_04
transcript.pyannote[168].start 765.95346875
transcript.pyannote[168].end 766.47659375
transcript.pyannote[169].speaker SPEAKER_04
transcript.pyannote[169].start 766.61159375
transcript.pyannote[169].end 770.15534375
transcript.pyannote[170].speaker SPEAKER_00
transcript.pyannote[170].start 782.87909375
transcript.pyannote[170].end 784.04346875
transcript.whisperx[0].start 0.209
transcript.whisperx[0].end 18.843
transcript.whisperx[0].text 銀行局還有國發會財政部莊部長以及內政部監管會黃主委內政部花次長那我先邀請銀行局莊局長跟國發會副主委有請莊局長跟剛副主委
transcript.whisperx[1].start 29.317
transcript.whisperx[1].end 45.047
transcript.whisperx[1].text 兩位好今天是電價調漲的第一天那平均調漲11%那央行估計說今年的全年CPI年增率是2.16%主計總數25日預估為2.03%國發會則預估為2.05到2.15%那為什麼不同到底是誰算錯了可不可以告訴我
transcript.whisperx[2].start 58.086
transcript.whisperx[2].end 73.292
transcript.whisperx[2].text 我想那個物價上漲率會根據模型來做推估那模型設定的參數不一樣都會有些微的差異可是可以看到這三個的預測值大概都是在一個區間的範圍之內這個預測值是當初都沒有納入電價調漲的這個設計對不對
transcript.whisperx[3].start 81.093
transcript.whisperx[3].end 104.642
transcript.whisperx[3].text 當初在上前次的質詢不管是主計處或者是這個都有央行都有這樣子回覆都沒有納入我們物價調漲了應該是說現在這個數字是有納入的那之前的是沒有納入那物價指數不只會影響每年所得稅的免稅還有很多的層面那現在你們預估的都不一樣我們到底要聽誰的
transcript.whisperx[4].start 108.376
transcript.whisperx[4].end 122.846
transcript.whisperx[4].text 我們基本上大概都會以主計處的為因為他是一個統計的發行的單位這樣子就是主計處的為準那央行因為他有貨幣政策資金的需要所以他也會有他的
transcript.whisperx[5].start 123.336
transcript.whisperx[5].end 124.157
transcript.whisperx[5].text 主席翠雲、金融部長莊部長
transcript.whisperx[6].start 144.741
transcript.whisperx[6].end 172.966
transcript.whisperx[6].text 委員好部長好部長那個網站上的數據顯示民國111年民間簽約投資公共建設金額是2828億但112年卻只有1876是什麼原因造成了這個短少了這麼多短少了1000億跟委員報告111年最主要是因為有6件比較大的超過百億元以上
transcript.whisperx[7].start 173.444
transcript.whisperx[7].end 173.564
transcript.whisperx[7].text 只是﹐
transcript.whisperx[8].start 198.669
transcript.whisperx[8].end 210.459
transcript.whisperx[8].text 民間機構參與促參法的公共建設投資案件的投資總額占整體公共建設經費比例不到一成那促參成效似乎很差
transcript.whisperx[9].start 211.482
transcript.whisperx[9].end 232.068
transcript.whisperx[9].text 那財政部最新的統計2023年受選資金投入公共建設簽約的只有兩案2023年那金額合計只有112.7億那是4年最少案件是4年最少那金額是5年新低那到底是什麼原因可不可以告訴我們
transcript.whisperx[10].start 233.164
transcript.whisperx[10].end 246.65
transcript.whisperx[10].text 委員報告在促參的部分民間投資其實沒有說很差當然財政部也一直都在努力包含就有關法制面的我們把它完善然後包含我們去年111年修了促參法擴大了公共建設的範圍的項目第二個我們也增加了有長
transcript.whisperx[11].start 254.854
transcript.whisperx[11].end 277.894
transcript.whisperx[11].text 公共服務就政府有償購買公共服務的機制另外我們現在也在對於有關那個履約期間相關的爭議我們財政部也成立了相關的委員的委員會條條解委員條解會然後來協助在執行過程當中發生履約爭議希望他們盡快的把這個解決以後然後持續讓公共服務能夠有效的提供
transcript.whisperx[12].start 278.414
transcript.whisperx[12].end 306.771
transcript.whisperx[12].text 另外對於重大公共建設的一個範圍財政部也持續和中央的目的事業主管機關在檢討調整希望能夠吸引更多的民間資金能夠投注怎麼吸引部長可不可以告訴我們具體的辦法要怎麼吸引比如我像剛剛所提的就是說我們擴大它的建設範圍的種類可以有更多的案源那另外就是法規面把它備齊然後對於履約爭議的部分我們提供相關的機制可以盡快的一個解決然後對於重大公共建設範圍做調整
transcript.whisperx[13].start 308.188
transcript.whisperx[13].end 329.753
transcript.whisperx[13].text 然後更大的資金可以進來我想這個部分是財政部可以做的部分那我相信我們也可以在國發會審議相關的一個計畫的公共建設計畫的時候我們盡量建議相關主管機關能夠把它改走促餐的模式然後提供按援讓民間的資金可以有相關的投資標的可以來做促餐
transcript.whisperx[14].start 330.733
transcript.whisperx[14].end 359.558
transcript.whisperx[14].text 對,那比如說國內齁那目前我們國內保險業的資金達到32兆達到32兆那就保險業龐大的資金要投入國內產業重要建設但是他必須要兩個點要注意的就是說第一個他時間要夠長是然後呢他的這個報酬要穩定是的時間過長報酬要穩定那報酬他們依照保險公司的一個理想報酬投報大概3到4%是是是
transcript.whisperx[15].start 359.918
transcript.whisperx[15].end 387.463
transcript.whisperx[15].text 那這3到4%政府要提出什麼樣的公共建設投資案是符合這樣子一個合理的投資報酬?是,所以跟委員報告有關第一個就是我們要多開發相關的案源就是說以初餐的模式來做就是案源的部分要擴大那第二個部分就是我們的法規相關讓它能夠更完備那這個部分金管會其實剛剛在我們的主委的報告裡面也就法規的一些修正
transcript.whisperx[16].start 388.444
transcript.whisperx[16].end 414.262
transcript.whisperx[16].text 保險業可以去投注到公共建設那其實這個部分就您剛剛講第一個一個收益率以及一個時間的長各方面的話其實像我們的一關像民生的一個民生的一個公共公用事業比如說霧水道的霧水下水道的一個處理或者是長照的長照的事業或者是物流中心以及焚化爐這些都是一個比較長年期的而且他的獲益率會有一定的
transcript.whisperx[17].start 414.702
transcript.whisperx[17].end 414.922
transcript.whisperx[17].text 委員會委員會委員會
transcript.whisperx[18].start 430.609
transcript.whisperx[18].end 432.59
transcript.whisperx[18].text 接下來我們再來請金管會黃主委請黃主委
transcript.whisperx[19].start 459.361
transcript.whisperx[19].end 472.393
transcript.whisperx[19].text 委員好 主委好主委 我們保險業的資金32兆有69.6%到去年9月底有69.6%投資國外其中61.9%投資有價證券那受選實際投資國內的公共建設大概是佔新台幣1300億
transcript.whisperx[20].start 481.562
transcript.whisperx[20].end 508.749
transcript.whisperx[20].text 可用:占可用資金的0.38%這個比例這麼懸殊那投資國外公共建設約7500億占了2.2%在金管會條件係數鼓勵投資公建型私募股權基金投資5加2產業的部分的狀況之下那今年可不可以請主委告訴我們今年預計保險資金投入國內公共建設的資金會達到多少
transcript.whisperx[21].start 510.28
transcript.whisperx[21].end 525.781
transcript.whisperx[21].text 這個不太容易這個時候去預算但是我們基本上尤其在去年年底已經把一些重要的風險係數都降低了希望能夠去年多少去年是5000多億嗎5000多億5900多億對對對那今年會不會再增加往上走
transcript.whisperx[22].start 525.981
transcript.whisperx[22].end 526.762
transcript.whisperx[22].text 主席優生再接著請內政部花次長
transcript.whisperx[23].start 548.167
transcript.whisperx[23].end 559.958
transcript.whisperx[23].text 市長112年12月14日在行政院報告推動社宅注宅成果與提升社宅用地供給經濟措施當中預計在今年113年可達到20萬戶社會注宅的目標
transcript.whisperx[24].start 565.163
transcript.whisperx[24].end 580.432
transcript.whisperx[24].text 下階段社宅2032年會達到一百萬戶的目標請注意喔這一百萬是包括了25萬直接興建25萬包租貸款還有50萬戶的租金補貼加起來總共一百萬
transcript.whisperx[25].start 581.823
transcript.whisperx[25].end 592.214
transcript.whisperx[25].text 那這8年齁未來8年要完成那當然也要求各縣市在進行這個開發徵收還有市地存貨的時候保留3到5%直轄市5%非直轄市3%專案讓售給中央來興辦社宅
transcript.whisperx[26].start 597.62
transcript.whisperx[26].end 618.215
transcript.whisperx[26].text 那針對2035年要完成新建百萬的這樣子的比例等於是全國租屋家戶總數量那未來目標只要是有在外面租屋需求的這些家戶政府都會直接協助並且提出配套措施那請問內政部年底預計完成的20萬戶會不會如期達標
transcript.whisperx[27].start 620.616
transcript.whisperx[27].end 643.517
transcript.whisperx[27].text 8月20萬戶這20萬戶今年年底會達標那50萬戶的租金補貼應該就在今年的年中就會達標了所以說其實今年應該就可以做到就是這百萬戶裡面的70萬會在今年其實就做得到那剩下的部分其實現在直接興建每年可以增加2萬戶包租貸款大概可以增加
transcript.whisperx[28].start 644.077
transcript.whisperx[28].end 644.298
transcript.whisperx[28].text 委員會主席
transcript.whisperx[29].start 657.881
transcript.whisperx[29].end 663.364
transcript.whisperx[29].text 到目前2月統計臺中市中央加地方預計興建10,6406戶臺中市府佔了10225中央負責佔了6181市府的達成率72%中央只有65%
transcript.whisperx[30].start 676.17
transcript.whisperx[30].end 687.435
transcript.whisperx[30].text 以本席的選區烏日一個榮泉安居是國家住宅及都市更新中心在烏日區的首座設宅目標工程費10億4月2日要舉辦開工典禮這部分
transcript.whisperx[31].start 691.937
transcript.whisperx[31].end 692.558
transcript.whisperx[31].text 主要就是說﹖
transcript.whisperx[32].start 715.563
transcript.whisperx[32].end 726.511
transcript.whisperx[32].text 中央擴大租金補貼專案計畫是從111年到114年就等於是說這個計畫到2025年那總補貼的規模達到300億如果要達到租宅百萬戶的目標是不是租屋補貼除了繼續實施還要放大這個規模 對不對
transcript.whisperx[33].start 734.036
transcript.whisperx[33].end 754.481
transcript.whisperx[33].text 租用補貼會實施因為賴總統的政見裡面就提到會繼續實施到至少未來的8年都沒有問題那包租貸款跟直接信件都要做所以說這個資源當然會需求會擴大我先請教部長 房租一定漲 現在萬物期漲 電價漲什麼都漲那房租一定跟著漲 那租屋補貼會不會漲 補貼的金額會不會升高
transcript.whisperx[34].start 757.142
transcript.whisperx[34].end 757.262
transcript.whisperx[34].text 謝謝主席