iVOD / 164264

Field Value
IVOD_ID 164264
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164264
日期 2025-10-16
會議資料.會議代碼 委員會-11-4-20-2
會議資料.會議代碼:str 第11屆第4會期財政委員會第2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 2
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2次全體委員會議
影片種類 Clip
開始時間 2025-10-16T10:42:26+08:00
結束時間 2025-10-16T10:55:33+08:00
影片長度 00:13:07
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6022c9f6d63255a3e84cf7c5571f2c889ba2ba11b833fe0ade83ed45c59a17eb29602ffc9a9b6cbf5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 林思銘
委員發言時間 10:42:26 - 10:55:33
會議時間 2025-10-16T09:00:00+08:00
會議名稱 立法院第11屆第4會期財政委員會第2次全體委員會議(事由:邀請財政部莊部長翠雲率所屬機關首長暨國營事業董事長、總經理(含各轉投資事業機構公股代表之董、監事)列席業務報告,並備質詢。 【10月13日、15日及16日三天一次會】)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 1.19534375
transcript.pyannote[0].end 9.46409375
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 9.76784375
transcript.pyannote[1].end 11.96159375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 12.31596875
transcript.pyannote[2].end 15.16784375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 15.72471875
transcript.pyannote[3].end 23.48721875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 24.01034375
transcript.pyannote[4].end 30.40596875
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 31.31721875
transcript.pyannote[5].end 48.79971875
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 36.34596875
transcript.pyannote[6].end 36.75096875
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 37.07159375
transcript.pyannote[7].end 37.59471875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 41.69534375
transcript.pyannote[8].end 41.74596875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 41.74596875
transcript.pyannote[9].end 42.13409375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 42.13409375
transcript.pyannote[10].end 42.15096875
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 43.33221875
transcript.pyannote[11].end 44.66534375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 45.77909375
transcript.pyannote[12].end 49.40721875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 49.59284375
transcript.pyannote[13].end 59.58284375
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 50.26784375
transcript.pyannote[14].end 52.14096875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 55.53284375
transcript.pyannote[15].end 56.57909375
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 57.22034375
transcript.pyannote[16].end 62.56971875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 61.59096875
transcript.pyannote[17].end 66.24846875
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 63.00846875
transcript.pyannote[18].end 63.81846875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 63.85221875
transcript.pyannote[19].end 65.86034375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 66.31596875
transcript.pyannote[20].end 69.92721875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 70.41659375
transcript.pyannote[21].end 78.70221875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 79.34346875
transcript.pyannote[22].end 94.15971875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 94.34534375
transcript.pyannote[23].end 95.29034375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 95.66159375
transcript.pyannote[24].end 108.99284375
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 101.44971875
transcript.pyannote[25].end 102.49596875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 109.14471875
transcript.pyannote[26].end 114.51096875
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 113.19471875
transcript.pyannote[27].end 113.24534375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 113.24534375
transcript.pyannote[28].end 114.03846875
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 114.76409375
transcript.pyannote[29].end 121.76721875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 119.77596875
transcript.pyannote[30].end 124.04534375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 123.03284375
transcript.pyannote[31].end 130.96409375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 124.75409375
transcript.pyannote[32].end 125.31096875
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 126.71159375
transcript.pyannote[33].end 128.26409375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 129.47909375
transcript.pyannote[34].end 131.80784375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 131.57159375
transcript.pyannote[35].end 132.39846875
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 132.75284375
transcript.pyannote[36].end 134.64284375
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 134.92971875
transcript.pyannote[37].end 138.13596875
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 138.35534375
transcript.pyannote[38].end 140.88659375
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 141.96659375
transcript.pyannote[39].end 150.20159375
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 150.72471875
transcript.pyannote[40].end 157.08659375
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 157.87971875
transcript.pyannote[41].end 158.41971875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 159.04409375
transcript.pyannote[42].end 159.98909375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 160.56284375
transcript.pyannote[43].end 167.53221875
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 169.08471875
transcript.pyannote[44].end 193.28346875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 185.40284375
transcript.pyannote[45].end 185.45346875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 185.45346875
transcript.pyannote[46].end 186.26346875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 190.41471875
transcript.pyannote[47].end 190.93784375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 191.62971875
transcript.pyannote[48].end 195.25784375
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 195.56159375
transcript.pyannote[49].end 203.61096875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 204.15096875
transcript.pyannote[50].end 206.76659375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 207.25596875
transcript.pyannote[51].end 216.99284375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 218.89971875
transcript.pyannote[52].end 226.94909375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 224.38409375
transcript.pyannote[53].end 238.55909375
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 227.11784375
transcript.pyannote[54].end 229.58159375
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 230.23971875
transcript.pyannote[55].end 231.15096875
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 237.47909375
transcript.pyannote[56].end 239.01471875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 238.74471875
transcript.pyannote[57].end 267.70221875
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 268.19159375
transcript.pyannote[58].end 273.16971875
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 273.60846875
transcript.pyannote[59].end 275.75159375
transcript.pyannote[60].speaker SPEAKER_02
transcript.pyannote[60].start 275.98784375
transcript.pyannote[60].end 285.87659375
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 285.91034375
transcript.pyannote[61].end 286.04534375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 286.06221875
transcript.pyannote[62].end 290.65221875
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 290.80409375
transcript.pyannote[63].end 296.74409375
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 297.38534375
transcript.pyannote[64].end 298.24596875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 298.58346875
transcript.pyannote[65].end 301.57034375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 301.73909375
transcript.pyannote[66].end 311.22284375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 311.76284375
transcript.pyannote[67].end 323.00159375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 323.69346875
transcript.pyannote[68].end 332.62034375
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 328.97534375
transcript.pyannote[69].end 329.38034375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 329.38034375
transcript.pyannote[70].end 329.39721875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 330.05534375
transcript.pyannote[71].end 330.35909375
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 332.94096875
transcript.pyannote[72].end 337.90221875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 336.48471875
transcript.pyannote[73].end 336.77159375
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 338.20596875
transcript.pyannote[74].end 344.34846875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 343.53846875
transcript.pyannote[75].end 343.97721875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 344.55096875
transcript.pyannote[76].end 379.21221875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 369.34034375
transcript.pyannote[77].end 369.76221875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 375.44909375
transcript.pyannote[78].end 375.97221875
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 376.19159375
transcript.pyannote[79].end 377.69346875
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 378.30096875
transcript.pyannote[80].end 381.03471875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 379.93784375
transcript.pyannote[81].end 385.00034375
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 382.30034375
transcript.pyannote[82].end 385.81034375
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 385.35471875
transcript.pyannote[83].end 396.40784375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 389.03346875
transcript.pyannote[84].end 389.64096875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 389.64096875
transcript.pyannote[85].end 389.67471875
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 397.23471875
transcript.pyannote[86].end 397.82534375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 397.36971875
transcript.pyannote[87].end 428.67284375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 400.45784375
transcript.pyannote[88].end 400.99784375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 410.02596875
transcript.pyannote[89].end 410.43096875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 414.05909375
transcript.pyannote[90].end 414.78471875
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 416.16846875
transcript.pyannote[91].end 416.69159375
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 427.91346875
transcript.pyannote[92].end 435.87846875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 436.18221875
transcript.pyannote[93].end 449.88471875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 437.41409375
transcript.pyannote[94].end 440.45159375
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 441.73409375
transcript.pyannote[95].end 442.24034375
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 449.88471875
transcript.pyannote[96].end 450.07034375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 450.07034375
transcript.pyannote[97].end 465.27471875
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 460.97159375
transcript.pyannote[98].end 461.81534375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 462.97971875
transcript.pyannote[99].end 520.48971875
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 522.37971875
transcript.pyannote[100].end 550.13909375
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 527.44221875
transcript.pyannote[101].end 527.91471875
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 527.91471875
transcript.pyannote[102].end 527.99909375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 542.02221875
transcript.pyannote[103].end 542.62971875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 548.50221875
transcript.pyannote[104].end 549.04221875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 549.49784375
transcript.pyannote[105].end 555.70784375
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 554.64471875
transcript.pyannote[106].end 559.23471875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 558.79596875
transcript.pyannote[107].end 570.38909375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 559.38659375
transcript.pyannote[108].end 559.75784375
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 559.99409375
transcript.pyannote[109].end 560.09534375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 560.11221875
transcript.pyannote[110].end 560.14596875
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 565.36034375
transcript.pyannote[111].end 566.28846875
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 570.65909375
transcript.pyannote[112].end 573.67971875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 571.23284375
transcript.pyannote[113].end 571.65471875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 571.67159375
transcript.pyannote[114].end 571.82346875
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 571.92471875
transcript.pyannote[115].end 573.66284375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 573.67971875
transcript.pyannote[116].end 575.21534375
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 576.86909375
transcript.pyannote[117].end 579.56909375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 581.18909375
transcript.pyannote[118].end 582.58971875
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 585.50909375
transcript.pyannote[119].end 587.21346875
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 588.63096875
transcript.pyannote[120].end 589.33971875
transcript.pyannote[121].speaker SPEAKER_02
transcript.pyannote[121].start 589.76159375
transcript.pyannote[121].end 590.11596875
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 591.26346875
transcript.pyannote[122].end 593.45721875
transcript.pyannote[123].speaker SPEAKER_02
transcript.pyannote[123].start 594.09846875
transcript.pyannote[123].end 597.37221875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 594.11534375
transcript.pyannote[124].end 594.68909375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 597.72659375
transcript.pyannote[125].end 621.09846875
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 621.40221875
transcript.pyannote[126].end 630.98721875
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 632.37096875
transcript.pyannote[127].end 632.79284375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 632.42159375
transcript.pyannote[128].end 641.78721875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 634.37909375
transcript.pyannote[129].end 635.13846875
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 637.28159375
transcript.pyannote[130].end 638.36159375
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 640.08284375
transcript.pyannote[131].end 642.69846875
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 643.39034375
transcript.pyannote[132].end 644.55471875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 644.72346875
transcript.pyannote[133].end 648.75659375
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 644.95971875
transcript.pyannote[134].end 646.71471875
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 647.23784375
transcript.pyannote[135].end 649.31346875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 649.66784375
transcript.pyannote[136].end 653.05971875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 649.70159375
transcript.pyannote[137].end 651.50721875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 653.43096875
transcript.pyannote[138].end 654.52784375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 653.53221875
transcript.pyannote[139].end 670.25534375
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 661.76721875
transcript.pyannote[140].end 662.23971875
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 668.31471875
transcript.pyannote[141].end 668.75346875
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 669.95159375
transcript.pyannote[142].end 673.09034375
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 670.62659375
transcript.pyannote[143].end 670.74471875
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 673.46159375
transcript.pyannote[144].end 690.58971875
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 690.92721875
transcript.pyannote[145].end 697.76159375
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 692.86784375
transcript.pyannote[146].end 693.30659375
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 694.90971875
transcript.pyannote[147].end 696.31034375
transcript.pyannote[148].speaker SPEAKER_00
transcript.pyannote[148].start 696.31034375
transcript.pyannote[148].end 696.34409375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 698.21721875
transcript.pyannote[149].end 755.54159375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 718.33221875
transcript.pyannote[150].end 718.77096875
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 725.38596875
transcript.pyannote[151].end 725.55471875
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 751.81221875
transcript.pyannote[152].end 753.24659375
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 755.54159375
transcript.pyannote[153].end 761.81909375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 762.12284375
transcript.pyannote[154].end 768.75471875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 766.03784375
transcript.pyannote[155].end 766.78034375
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 767.70846875
transcript.pyannote[156].end 775.31909375
transcript.pyannote[157].speaker SPEAKER_00
transcript.pyannote[157].start 772.36596875
transcript.pyannote[157].end 772.43346875
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 772.51784375
transcript.pyannote[158].end 772.63596875
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 772.73721875
transcript.pyannote[159].end 772.85534375
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 777.41159375
transcript.pyannote[160].end 777.98534375
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 778.55909375
transcript.pyannote[161].end 778.99784375
transcript.whisperx[0].start 1.209
transcript.whisperx[0].end 30.186
transcript.whisperx[0].text 委員好部長早部長這個就財化法的修法那個主院長在10月14號提出說依循垂直事權能夠劃分水平財源能夠均衡兩個方向將由副院長鄭麗君和地方討論並表示今年會提出一個版本來所以請問部長財政部是不是在這個會期結束前一定會提出財化法的修法版本
transcript.whisperx[1].start 31.777
transcript.whisperx[1].end 36.039
transcript.whisperx[1].text 跟委員報告那天院長在總資訊室有提到在今年底前會有院版那我們下個禮拜二會再邀請地方政府再來開會因為我們之前已經開過三次那現在還會在記者共識上繼續往前推進所以一定會在今年這個會期會提出來嗎
transcript.whisperx[2].start 50.025
transcript.whisperx[2].end 65.869
transcript.whisperx[2].text 今年底前9月13號院長邀請了22縣市的首長來也都聽取了他們的意見今年底的話可能就是會趕上這個會期我們一直不斷的都在討論謝謝委員指教部長 因為8月30號行政院表示說就是有345億這個345億的統籌分配稅款無法完成分配
transcript.whisperx[3].start 79.44
transcript.whisperx[3].end 94.957
transcript.whisperx[3].text 所以原因講說是因為無法逾越現有母法內的公式所以我要請問部長那在這一次的修法版本你們要提出的行政院的版本是否也會將這一個部分提出完整的一個做法會把它提出來
transcript.whisperx[4].start 96.014
transcript.whisperx[4].end 114.344
transcript.whisperx[4].text 跟委員報告這345億沒有辦法分出去委員知道應該16條之一那個分母的部分有問題嘛所以我們這個部分因為依法行政這個部分就沒有辦法分出去345億那這個部分我知道大院的委員也有要做提案去修正這個分母的部分
transcript.whisperx[5].start 114.884
transcript.whisperx[5].end 140.752
transcript.whisperx[5].text 那行政院未來我們要提出的版本會是一個完整的版本並不會只是針對這個問題一定會就這個部分會提出一個版本出來我們會在整體的分配的部分會做不是就這個公式這個也不會是我們未來的公式其實部長我提出一個建議其實說這個345億的解決方法只要進行二次分配就可以了
transcript.whisperx[6].start 142.032
transcript.whisperx[6].end 167.288
transcript.whisperx[6].text 也就是說把這345億元依照現行的這個修法的公式進行二次的分配計算就可以把這些345億就可以再次算出各縣市的分配的數字請問部長為什麼不做就是說二次的分配把這些剩餘款依照原有的我們修法的公式去做並不可行啊
transcript.whisperx[7].start 169.621
transcript.whisperx[7].end 194.354
transcript.whisperx[7].text 跟委員報告我們在算的時候一定依照一個法律而且現在這一次的財化法把原來有授權財政部訂定分配辦法的那個法條依據都把它刪掉了換言之財政部只能依照這個法條來做並沒有自行決定說我再怎麼樣的調整分配這表示說不願意讓財政部去做這方面的事我肯定你說按照法條來做
transcript.whisperx[8].start 195.675
transcript.whisperx[8].end 216.408
transcript.whisperx[8].text 即使這樣做二次分配或者是三次的分配這樣也是依照原來母法的公式去計算所以這並沒有逾越母法的問題我是建議你就是說在未來做這個如果財政部要提出修法的版本我這個建議你是不是可以納入參考的依據
transcript.whisperx[9].start 218.953
transcript.whisperx[9].end 239.368
transcript.whisperx[9].text 政府所提的版本會跟這個公司不會不盡相同不會相同的因為我們會就整體面的去做考量其實廣義啦我給你一個建議似乎並沒有那麼難所以你們可以去多方面做一個考量不要這個自私一分了解另外這個部長
transcript.whisperx[10].start 240.889
transcript.whisperx[10].end 267.4
transcript.whisperx[10].text 財政部在本週二公布了今年一到九月的稅收累計時增兩兆八千七百一十億佔累計分配預算數的百分之九十三佔前年預算數的百分之七十五點五但是比去年同期卻少了三百六十五億年減百分之二點五實現一個衰退的一個現象
transcript.whisperx[11].start 268.3
transcript.whisperx[11].end 295.288
transcript.whisperx[11].text 但是我們看到台股在今年九月的表現逆勢成長 頻頻創新高九月正交稅的收入就高達312億年增52.6%創下歷年來台股在九月最亮麗的表現同時也是單月第三高更是16年來的最大增幅保持連二紅的一個狀態讓我們衰退的情況趨緩
transcript.whisperx[12].start 297.469
transcript.whisperx[12].end 320.026
transcript.whisperx[12].text 所以部長 9月份的股市表現這麼亮眼那證交稅 印花稅 盈利事業 房地合一稅以及整體的這個稅收多個項目也都創下單月的新高但是我們比去年的同期總稅收卻減少了365億那請問這個具體的原因是什麼為什麼會這個總稅收會減少
transcript.whisperx[13].start 324.049
transcript.whisperx[13].end 342.689
transcript.whisperx[13].text 跟委員報告您剛才有365億是中央的部分跟去年同期相比差365億那剛剛您提到印花稅或者娛樂稅或房屋稅都增加那是屬於地方稅不在我們這個統計裡面另外房地合一所得稅是要進到長照基金跟住宅基金也沒有在這個稅收的統計裡面
transcript.whisperx[14].start 344.871
transcript.whisperx[14].end 371.732
transcript.whisperx[14].text 另外您刚刚也提到的股市的证交税9月确实日均量达到6006亿所以9月份这单一月份的证交税比去年的同期的9月份的证交税是增加107亿但是我们累计1到9月的股市的日均量是4451亿比去年同期的4943亿是少的所以1到9月份的证交税呢
transcript.whisperx[15].start 372.112
transcript.whisperx[15].end 396.173
transcript.whisperx[15].text 事实上比去年同期是减少了223亿跟委员报告这是最主要的部分正交税是减少的股市表现那么亮那是单一八月份非常好整个平均下来是一到九月下来是差500亿平均数差500亿那未来我们看10月到12月如果股市能够更往上走那也许可以把这个缺口补上
transcript.whisperx[16].start 397.567
transcript.whisperx[16].end 421.162
transcript.whisperx[16].text 另外一个减少的原因是营锁税的部分营锁税的部分是减少比去年同期减少481亿这个部分有部分原因是因为站脚税款还没有入账要到10月会入账还有一个就是因为对等关税因为受冲击的产业他们申请延期跟分期就会递延入账另外货物税也减少了比去年同期减少123亿
transcript.whisperx[17].start 422.443
transcript.whisperx[17].end 435.306
transcript.whisperx[17].text 那最主要是小客車的部分貨物稅減少的比較多那因為前面的稅制大家有些觀望的態度所以我們按照目前的這樣的一個稅收的表現是所以是否代表今年我們可能會短徵
transcript.whisperx[18].start 436.6
transcript.whisperx[18].end 464.555
transcript.whisperx[18].text 今年要达成因为今年的预算数跟委员报告114年我们税客收入的预算数比去年113年10增数10增数就增加了947亿增加947亿但是我们到9月底为止的10增数却比去年减少所以这个部分要达成114年的预算数很具有挑战性我们再看后面的税收情况再来跟委员报告
transcript.whisperx[19].start 465.135
transcript.whisperx[19].end 479.286
transcript.whisperx[19].text 是 部長最後一個問題請問就是我們在114年9月1日起新清安貸款的撥款案件將不計入銀行法72條之2的限額主要就是為了紓解銀行房貸量能的一個緊竅
transcript.whisperx[20].start 481.504
transcript.whisperx[20].end 495.614
transcript.whisperx[20].text 財政部在9月5號有對外公布統計到114年的8月22號所有公股銀行的受理清清安貸款以何代上代撥款的額度的件數共計12,923件金額高達1,257億餘元
transcript.whisperx[21].start 502.458
transcript.whisperx[21].end 517.845
transcript.whisperx[21].text 原預估撥貸的時間大概要0.5個月至4個月所以請問部長各公股銀行在新清安貸款放貸鬆綁後目前最新的上貸撥款還有多少件貸撥款金額還有多少
transcript.whisperx[22].start 523.201
transcript.whisperx[22].end 534.606
transcript.whisperx[22].text 9月1號以後把那個銀行法那個規定天花板拿清清安不受那個限制以後那到今年為止還有要分別降到了5200件跟566億那大概時間要也就是說分別減少了60%跟55%啦件數減少60%那等待的時間也縮短了大概在兩個月以內可以做合撥是
transcript.whisperx[23].start 549.632
transcript.whisperx[23].end 574.279
transcript.whisperx[23].text 所以各大公股銀行的這個帶波件數以及帶波金額都已經明顯的減少了明顯減少那也協助一些沒有自有房屋是不是請各大公股銀行可以把現在到目前為止我們帶波的件數以及帶波的這個金額可以匯後以素面提供給我們本委員會沒有問題 謝謝委員是 我們就提供是 謝謝好 部長
transcript.whisperx[24].start 576.909
transcript.whisperx[24].end 579.19
transcript.whisperx[24].text 部長請回 請101董事長我們請賈董事長剩下幾秒而已來 董事長
transcript.whisperx[25].start 591.791
transcript.whisperx[25].end 620.531
transcript.whisperx[25].text 簡單就叫你啦我想我也好是你就任期已經也超過一年了那麼記得你在剛上任的時候呢可能因為明星的官黃社會各界對你有所期待許多媒體也聚焦在你身上而當初董事長你全家獨你當101董事長撐不到半年但是現在已經撐了一年多了我們看到整個觀景台語商場的人潮確實也看到一些成長
transcript.whisperx[26].start 621.511
transcript.whisperx[26].end 630.701
transcript.whisperx[26].text 所以請問董事長這一年多來你應該也從申書到現在完全上手那這一年你為101增加了多少的營收
transcript.whisperx[27].start 632.786
transcript.whisperx[27].end 641.552
transcript.whisperx[27].text 這一年增加多少營收嗎?我應該說我們是正向的成長成長幾%你知道嗎?10%以內那實際的數字是大概多少?
transcript.whisperx[28].start 653.719
transcript.whisperx[28].end 672.578
transcript.whisperx[28].text 10%大概多少錢因為實際的數字我們今年的這個還沒有真正的到了這個結尾的部分對所以說可能要等年底的時候那我們的財報跟我們的這個整個數字都會公告所以到時候委員您可以知道的是那個董事長我想我給你一個取喜
transcript.whisperx[29].start 673.659
transcript.whisperx[29].end 690.346
transcript.whisperx[29].text 我們希望你在第二年進入第二年之後你會交出一張非常亮麗的成績單你自己覺得說未來你還有哪些項目可以做改善或者再更提升你的一個經營的效率
transcript.whisperx[30].start 691.264
transcript.whisperx[30].end 697.066
transcript.whisperx[30].text 首先非常感謝委員你好像給我一個可以宣傳的機會我覺得我的目標基本上我個人在101如果很幸運的話可以完成我的任期三年的話我想我的個人的KPI就是我會增加101的營收另外一方面我也希望101再增加我們回饋社會我們在公益捐款的部分而且是實際捐款的數字
transcript.whisperx[31].start 720.753
transcript.whisperx[31].end 731.098
transcript.whisperx[31].text 這個部分我相信我要把這兩個數字都是正向拉高的部分另外就是如果要講到一個比較再創新一點的活動的話大家可以期待我們明年會跟Netflix有一個全球的直播
transcript.whisperx[32].start 740.083
transcript.whisperx[32].end 754.097
transcript.whisperx[32].text Netflix的全球直播呢基本上就是讓我們台灣讓我們台北101呢可以展現在全球觀眾的面前那我想這是一個非常大的案子也請大家期待那當然還有我們的跨年煙火
transcript.whisperx[33].start 755.698
transcript.whisperx[33].end 774.963
transcript.whisperx[33].text 是是是現在董事長我想就是希望你能夠讓101的經營整個這個營收體質能夠更加的完善進步好我努力加油謝謝我繼續打臉我的家人好謝謝謝謝林思明 趙偉欸 趙偉拜託