iVOD / 164239

Field Value
IVOD_ID 164239
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164239
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 2025-10-16T09:24:46+08:00
結束時間 2025-10-16T09:35:05+08:00
影片長度 00:10:19
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6022c9f6d63255a30b25e295ab490aa99ba2ba11b833fe0a5dd201981b308a87ee4908f1f42fde8f5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 吳秉叡
委員發言時間 09:24:46 - 09:35:05
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 3.13596875
transcript.pyannote[0].end 3.15284375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 3.15284375
transcript.pyannote[1].end 3.45659375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 3.45659375
transcript.pyannote[2].end 3.52409375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 3.52409375
transcript.pyannote[3].end 3.60846875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 4.11471875
transcript.pyannote[4].end 5.22846875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 5.56596875
transcript.pyannote[5].end 7.27034375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 7.50659375
transcript.pyannote[6].end 8.62034375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 9.32909375
transcript.pyannote[7].end 12.36659375
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 13.29471875
transcript.pyannote[8].end 14.39159375
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 15.04971875
transcript.pyannote[9].end 15.69096875
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 16.70346875
transcript.pyannote[10].end 24.38159375
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 24.80346875
transcript.pyannote[11].end 25.42784375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 25.71471875
transcript.pyannote[12].end 27.14909375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 27.77346875
transcript.pyannote[13].end 29.88284375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 30.18659375
transcript.pyannote[14].end 34.48971875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 34.97909375
transcript.pyannote[15].end 35.38409375
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 36.85221875
transcript.pyannote[16].end 39.90659375
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 41.17221875
transcript.pyannote[17].end 42.15096875
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 41.50971875
transcript.pyannote[18].end 44.42909375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 45.01971875
transcript.pyannote[19].end 50.53784375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 48.95159375
transcript.pyannote[20].end 49.47471875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 50.33534375
transcript.pyannote[21].end 51.90471875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 51.26346875
transcript.pyannote[22].end 53.22096875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 52.83284375
transcript.pyannote[23].end 54.84096875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 55.39784375
transcript.pyannote[24].end 62.53596875
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 62.85659375
transcript.pyannote[25].end 78.78659375
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 79.07346875
transcript.pyannote[26].end 85.11471875
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 84.67596875
transcript.pyannote[27].end 86.71784375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 85.60409375
transcript.pyannote[28].end 85.82346875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 86.02596875
transcript.pyannote[29].end 96.89346875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 90.63284375
transcript.pyannote[30].end 91.10534375
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 93.19784375
transcript.pyannote[31].end 93.78846875
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 95.88096875
transcript.pyannote[32].end 98.73284375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 98.98596875
transcript.pyannote[33].end 103.28909375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 99.40784375
transcript.pyannote[34].end 99.44159375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 103.84596875
transcript.pyannote[35].end 106.30971875
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 107.03534375
transcript.pyannote[36].end 112.73909375
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 112.94159375
transcript.pyannote[37].end 114.86534375
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 115.28721875
transcript.pyannote[38].end 122.86409375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 123.87659375
transcript.pyannote[39].end 128.56784375
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 128.85471875
transcript.pyannote[40].end 130.89659375
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 131.28471875
transcript.pyannote[41].end 137.91659375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 138.22034375
transcript.pyannote[42].end 144.37971875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 141.12284375
transcript.pyannote[43].end 142.00034375
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 144.37971875
transcript.pyannote[44].end 149.22284375
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 144.58221875
transcript.pyannote[45].end 147.41721875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 148.42971875
transcript.pyannote[46].end 154.21784375
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 154.60596875
transcript.pyannote[47].end 155.77034375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 156.36096875
transcript.pyannote[48].end 159.43221875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 159.70221875
transcript.pyannote[49].end 165.05159375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 165.52409375
transcript.pyannote[50].end 166.77284375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 166.85721875
transcript.pyannote[51].end 168.86534375
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 168.86534375
transcript.pyannote[52].end 169.23659375
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 169.60784375
transcript.pyannote[53].end 172.69596875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 172.89846875
transcript.pyannote[54].end 172.91534375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 172.91534375
transcript.pyannote[55].end 173.16846875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 173.40471875
transcript.pyannote[56].end 173.82659375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 174.06284375
transcript.pyannote[57].end 175.31159375
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 175.69971875
transcript.pyannote[58].end 176.59409375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 176.91471875
transcript.pyannote[59].end 179.27721875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 179.71596875
transcript.pyannote[60].end 181.30221875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 181.70721875
transcript.pyannote[61].end 183.68159375
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 184.39034375
transcript.pyannote[62].end 186.39846875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 186.65159375
transcript.pyannote[63].end 187.17471875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 187.57971875
transcript.pyannote[64].end 188.32221875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 189.14909375
transcript.pyannote[65].end 193.99221875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 194.27909375
transcript.pyannote[66].end 198.37971875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 199.02096875
transcript.pyannote[67].end 205.34909375
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 205.61909375
transcript.pyannote[68].end 208.75784375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 205.65284375
transcript.pyannote[69].end 205.97346875
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 205.97346875
transcript.pyannote[70].end 206.19284375
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 209.16284375
transcript.pyannote[71].end 213.90471875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 214.10721875
transcript.pyannote[72].end 214.61346875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 215.20409375
transcript.pyannote[73].end 218.78159375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 219.60846875
transcript.pyannote[74].end 224.73846875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 224.99159375
transcript.pyannote[75].end 229.39596875
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 230.27346875
transcript.pyannote[76].end 234.82971875
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 234.82971875
transcript.pyannote[77].end 235.03221875
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 235.03221875
transcript.pyannote[78].end 236.48346875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 235.13346875
transcript.pyannote[79].end 235.33596875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 236.85471875
transcript.pyannote[80].end 239.65596875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 239.97659375
transcript.pyannote[81].end 244.33034375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 244.98846875
transcript.pyannote[82].end 246.74346875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 247.90784375
transcript.pyannote[83].end 249.03846875
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 249.37596875
transcript.pyannote[84].end 254.94471875
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 254.94471875
transcript.pyannote[85].end 255.36659375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 256.49721875
transcript.pyannote[86].end 261.82971875
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 262.52159375
transcript.pyannote[87].end 280.18971875
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 268.76534375
transcript.pyannote[88].end 271.16159375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 271.16159375
transcript.pyannote[89].end 271.66784375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 280.81409375
transcript.pyannote[90].end 282.16409375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 282.73784375
transcript.pyannote[91].end 289.89284375
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 290.80409375
transcript.pyannote[92].end 291.32721875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 291.37784375
transcript.pyannote[93].end 300.43971875
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 301.26659375
transcript.pyannote[94].end 303.30846875
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 304.03409375
transcript.pyannote[95].end 306.17721875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 306.86909375
transcript.pyannote[96].end 308.11784375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 308.55659375
transcript.pyannote[97].end 311.00346875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 311.66159375
transcript.pyannote[98].end 312.57284375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 313.18034375
transcript.pyannote[99].end 319.81221875
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 321.17909375
transcript.pyannote[100].end 326.89971875
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 325.81971875
transcript.pyannote[101].end 325.90409375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 327.01784375
transcript.pyannote[102].end 329.44784375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 328.90784375
transcript.pyannote[103].end 331.08471875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 331.08471875
transcript.pyannote[104].end 335.26971875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 333.73409375
transcript.pyannote[105].end 334.00409375
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 334.74659375
transcript.pyannote[106].end 336.43409375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 336.88971875
transcript.pyannote[107].end 340.80471875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 341.29409375
transcript.pyannote[108].end 345.09096875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 345.83346875
transcript.pyannote[109].end 347.31846875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 348.22971875
transcript.pyannote[110].end 367.80471875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 367.80471875
transcript.pyannote[111].end 374.74034375
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 367.82159375
transcript.pyannote[112].end 369.96471875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 370.01534375
transcript.pyannote[113].end 370.08284375
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 370.26846875
transcript.pyannote[114].end 370.48784375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 370.52159375
transcript.pyannote[115].end 370.60596875
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 375.04409375
transcript.pyannote[116].end 375.36471875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 375.36471875
transcript.pyannote[117].end 377.64284375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 378.01409375
transcript.pyannote[118].end 378.23346875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 378.70596875
transcript.pyannote[119].end 391.21034375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 391.21034375
transcript.pyannote[120].end 394.11284375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 394.11284375
transcript.pyannote[121].end 396.13784375
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 396.13784375
transcript.pyannote[122].end 410.90346875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 396.40784375
transcript.pyannote[123].end 397.03221875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 408.69284375
transcript.pyannote[124].end 420.03284375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 412.55721875
transcript.pyannote[125].end 413.33346875
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 420.33659375
transcript.pyannote[126].end 428.14971875
transcript.pyannote[127].speaker SPEAKER_00
transcript.pyannote[127].start 428.14971875
transcript.pyannote[127].end 428.94284375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 428.36909375
transcript.pyannote[128].end 434.98409375
transcript.pyannote[129].speaker SPEAKER_00
transcript.pyannote[129].start 430.25909375
transcript.pyannote[129].end 430.76534375
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 435.59159375
transcript.pyannote[130].end 438.74721875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 439.48971875
transcript.pyannote[131].end 440.29971875
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 440.63721875
transcript.pyannote[132].end 443.10096875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 443.59034375
transcript.pyannote[133].end 444.56909375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 445.26096875
transcript.pyannote[134].end 446.96534375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 447.30284375
transcript.pyannote[135].end 447.91034375
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 448.51784375
transcript.pyannote[136].end 450.23909375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 451.21784375
transcript.pyannote[137].end 452.70284375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 453.34409375
transcript.pyannote[138].end 459.28409375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 460.44846875
transcript.pyannote[139].end 462.94596875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 463.85721875
transcript.pyannote[140].end 466.27034375
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 467.11409375
transcript.pyannote[141].end 475.12971875
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 475.19721875
transcript.pyannote[142].end 476.47971875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 477.12096875
transcript.pyannote[143].end 478.84221875
transcript.pyannote[144].speaker SPEAKER_01
transcript.pyannote[144].start 479.36534375
transcript.pyannote[144].end 481.03596875
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 481.40721875
transcript.pyannote[145].end 483.38159375
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 483.92159375
transcript.pyannote[146].end 486.89159375
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 486.41909375
transcript.pyannote[147].end 487.60034375
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 487.51596875
transcript.pyannote[148].end 491.90346875
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 488.95034375
transcript.pyannote[149].end 489.38909375
transcript.pyannote[150].speaker SPEAKER_02
transcript.pyannote[150].start 491.90346875
transcript.pyannote[150].end 498.97409375
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 496.25721875
transcript.pyannote[151].end 500.37471875
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 500.37471875
transcript.pyannote[152].end 500.67846875
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 500.67846875
transcript.pyannote[153].end 502.87221875
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 503.42909375
transcript.pyannote[154].end 504.69471875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 504.98159375
transcript.pyannote[155].end 508.15409375
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 508.98096875
transcript.pyannote[156].end 511.98471875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 512.47409375
transcript.pyannote[157].end 549.98721875
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 545.00909375
transcript.pyannote[158].end 545.22846875
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 548.65409375
transcript.pyannote[159].end 580.71659375
transcript.pyannote[160].speaker SPEAKER_02
transcript.pyannote[160].start 579.09659375
transcript.pyannote[160].end 580.68284375
transcript.pyannote[161].speaker SPEAKER_02
transcript.pyannote[161].start 580.71659375
transcript.pyannote[161].end 581.12159375
transcript.pyannote[162].speaker SPEAKER_01
transcript.pyannote[162].start 581.08784375
transcript.pyannote[162].end 583.34909375
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 583.45034375
transcript.pyannote[163].end 585.17159375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 585.45846875
transcript.pyannote[164].end 586.70721875
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 587.12909375
transcript.pyannote[165].end 591.22971875
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 589.77846875
transcript.pyannote[166].end 590.41971875
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 590.62221875
transcript.pyannote[167].end 590.65596875
transcript.pyannote[168].speaker SPEAKER_02
transcript.pyannote[168].start 591.22971875
transcript.pyannote[168].end 591.90471875
transcript.pyannote[169].speaker SPEAKER_01
transcript.pyannote[169].start 591.90471875
transcript.pyannote[169].end 603.14346875
transcript.pyannote[170].speaker SPEAKER_02
transcript.pyannote[170].start 591.93846875
transcript.pyannote[170].end 592.47846875
transcript.pyannote[171].speaker SPEAKER_02
transcript.pyannote[171].start 598.33409375
transcript.pyannote[171].end 598.62096875
transcript.pyannote[172].speaker SPEAKER_02
transcript.pyannote[172].start 603.14346875
transcript.pyannote[172].end 605.13471875
transcript.pyannote[173].speaker SPEAKER_01
transcript.pyannote[173].start 603.27846875
transcript.pyannote[173].end 603.73409375
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 606.19784375
transcript.pyannote[174].end 610.80471875
transcript.whisperx[0].start 3.137
transcript.whisperx[0].end 26.342
transcript.whisperx[0].text 委員好川普長早根據你今天早上的報告今年度在收這個稅收的時候它的比例是比較慢但是你沒有說明其中很大原因是因為為了因應美國關稅政策延緩提供了這個延分期繳納
transcript.whisperx[1].start 27.862
transcript.whisperx[1].end 54.691
transcript.whisperx[1].text 所以造成這個統計的結果那這個因應美國關稅所提供的研分期繳納到底會有沒有計算過這樣子事實上是少收了多少將來當然會補上啦我是說目前少收了多少大概有申請研分期大概有530幾億主要是營所稅的部分加上這個其實就沒有慢了
transcript.whisperx[2].start 55.844
transcript.whisperx[2].end 84.382
transcript.whisperx[2].text 對 那也跟委員報告我們先跟委員報告就是114年的稅客收入的預算數比113年的實徵數我們有增加到947億好 947億那我們如果到9月底為止我們中央的實徵數和到去年同期的實徵數事實上目前來說是少了365億那主要的原因也可以跟委員報告第一個就是銀索稅的部分
transcript.whisperx[3].start 84.682
transcript.whisperx[3].end 102.873
transcript.whisperx[3].text 就是剛剛講的這個啊 延分期啊延分期之外還有因為站腳稅款是到9月那所以有些稅款會在10月才入帳那所以真正的稅款會到10月我們才可以看出一個全貌我跟你說 我認為你們還是估得很保守因為今年的GDP照主計總數的講法今年明顯就會超過4.5個百分點
transcript.whisperx[4].start 107.136
transcript.whisperx[4].end 122.178
transcript.whisperx[4].text 然後成長數所以你明年的稅客收入依照你們今年提出的預算數估起來是保守我再一次跟你講你估的保守本來沒有問題啦但是被人家拿來做政治操作就會產生問題
transcript.whisperx[5].start 124.299
transcript.whisperx[5].end 142.628
transcript.whisperx[5].text 預算收入是一個估計數沒有什麼超收的問題中華民國要收每一毛稅全部都要法律有明文規定法律有明文規定你也不能不收啊所以哪有什麼超收這個字母字也根本不對超過估計的預算數時收數超過估數
transcript.whisperx[6].start 146.75
transcript.whisperx[6].end 172.361
transcript.whisperx[6].text 超过原来估计的预算数对那我是要跟你说其实你今年还是孤跑手的如果照我们今年这个GDP的成长再加上目前因为AI因为这个电子产业当然我们现在是M型化但是台湾的产业刚好就是在AI在电子产业这一块也是世界的非常重要的分布所以短期之内看起来这一方面还会很有荣景
transcript.whisperx[7].start 173.479
transcript.whisperx[7].end 198.049
transcript.whisperx[7].text 那我是認為啦今年的上市櫃公司所獲利可能會創歷史新高以前市造今年可能會不值所以我是覺得你們的估算還是很保守那你如果很保守你就要開始在因應在野黨又要講說來你超收啊你要還稅於民啊錢給我啊他不知道我們
transcript.whisperx[8].start 199.39
transcript.whisperx[8].end 218.513
transcript.whisperx[8].text 優先順序該要做的事情裡面有很多就變成要舉借來特別預算所以他每次來跟你講都講一半欸我要發錢這個東西你說說沒有錢那你們怎麼有錢去做其他事情我要做其他事情因為其他事情的優先順序很重要啊
transcript.whisperx[9].start 219.69
transcript.whisperx[9].end 246.643
transcript.whisperx[9].text 可能比每一個國民要領一萬塊還要重要啊所以他沒有當家他不知道我們在講的是體制行政機關有使用人事跟預算的權利立法機關哪裡有憲法規定我們不能為增加預算的提案結果立法院弄一個法律叫你這邊花錢那邊花錢整個國家體制都破壞掉了嘛
transcript.whisperx[10].start 248.132
transcript.whisperx[10].end 261.066
transcript.whisperx[10].text 這樣子你要怎麼擔任所以我是這一次跟你說財政收支劃分法現在行政院要提出版本了對不對財政收支劃分法他不是只有管收不是只有中央跟地方財
transcript.whisperx[11].start 262.608
transcript.whisperx[11].end 289.28
transcript.whisperx[11].text 政的分配跟地方政府水平的財政的分配不是他重要的是資的部分權責要相符哪一些部分要中央來執行哪一些部分地方政府要執行講清楚在這個執行政策上面總共要花多少錢這樣子才能分配錢先要講事權的分配事權的分配完之後才搭配給多少錢
transcript.whisperx[12].start 290.902
transcript.whisperx[12].end 319.131
transcript.whisperx[12].text 是的 那我對你們的期許是把這個事情跟社會大眾講清楚你們的版本喔 行政院的版本現在來到立法院我認為很難過啦因為現在藍白人數量是多他不跟你討論真正的到底是需要什麼反正大家就是講到錢就是搶然後不講道理你現在這個財政收支劃分法如果沒有好好處理我跟你講會發生幾件事情第一個每一個地方政府都搶稅
transcript.whisperx[13].start 321.226
transcript.whisperx[13].end 346.016
transcript.whisperx[13].text 因為你現在營業稅大部分就變成財政收支劃分法裡面的統籌分配稅款了嘛要分給地方政府嘛扣掉4%以外全部歸地方政府那你的4%是要給你們積增的金額啊積增金額以及那個獎金統一發票獎金那我現在問一個問題啦齁你現在如果舉一個例子你企業的總部給我設在台北市結果你工廠設在桃園或是生產的地點設在新北的將來營業稅算在哪裡繳
transcript.whisperx[14].start 348.805
transcript.whisperx[14].end 373.77
transcript.whisperx[14].text 跟委員報告最主要因為這一次新版的財化法他在裡面把盈利事業的營業額的比重放得非常高也就是會遇到委員剛剛講的這個情況那因為把營業額放得特別高以至於工商發展的城市他就貨配特別多那麼就是會造成各縣市政府未來會去爭取相關的企業當然我不是啦我如果是新北市長我現在就要求我在新北市在這邊給我設生產地點的你營業額不給我弄過來新北市的話
transcript.whisperx[15].start 378.752
transcript.whisperx[15].end 395.852
transcript.whisperx[15].text 我就要開始來找你這個有什麼地方不符合任何的法令都是給你嚴格監管那這樣就變成每一個地方政府為了自己的將來的統籌分配稅就變成搶稅啦是 而且會干擾到企業的一個運作對 那你這個事情你準備要怎麼解釋
transcript.whisperx[16].start 396.572
transcript.whisperx[16].end 417.565
transcript.whisperx[16].text 怎麼要處理未來我們的財化法的規劃其實是第一個會優先要彌補基整財政收支的一個差段這個部分然後把營業額的部分不會把它放到這麼高我們會基本上要先保障財源你講的是你現在行政院提出的草案嘛那我現在跟你講的是現在立法院已經通過的那個案子你們現在提過來這個草案我認為不容易過啦
transcript.whisperx[17].start 420.487
transcript.whisperx[17].end 438.534
transcript.whisperx[17].text 但是你們要好好的跟社會大眾說明你們現在提出這個草案是基於什麼原因必須要這樣子處理我跟你講不然都獨厚台北市啊台北市企業總部一大堆結果他生產的地點都在別人的地方將來一頁稅都算台北市的第二個我們國稅局有非常多優秀的公務員可是一個問題啊
transcript.whisperx[18].start 445.462
transcript.whisperx[18].end 466.045
transcript.whisperx[18].text 你這個是代收將來營業稅要給地方政府國稅局這麼認真幹嘛我在那邊計徵拿到的稅款又不是歸我專門政府是地方政府我替地方政府在查稅結果你們國稅局當壞人然後拿到錢的都是地方政府
transcript.whisperx[19].start 467.145
transcript.whisperx[19].end 483.118
transcript.whisperx[19].text 那國稅局的同仁要為地方政府去得罪這些優秀公園要為地方政府去得罪那麼多人去得罪這些企業大家都知道為國家查稅是合理的但是問題是你要查稅喔被查稅的對象他就心中
transcript.whisperx[20].start 483.999
transcript.whisperx[20].end 502.183
transcript.whisperx[20].text 不論如何他心裡都會有怨言嘛對不對那這個問題你要怎麼解決我覺得將來這個方面的激增也會出問題耶我想委員您的建議我們都會在新版財化法這個我們未來要向外界說清楚講明白說清楚好那最後問一個小問題這個國營在新南向國家現在有很多分行要裁撤那可不可以跟我說明主要的考量是什麼
transcript.whisperx[21].start 512.823
transcript.whisperx[21].end 516.245
transcript.whisperx[21].text 我想我們的國營在設外面的紙行分行或辦事處他們要考量的因素包含有營運成本的問題還有業務拓展的問題還有怎麼樣整合他們的據點資源來降低營運成本當然也有跟當地的一些政局的影響業務的情形都要考慮我想我們的國營我們的公股行庫對於外面設分行或紙行辦事處他們在如何設點的時候都要會做整體的考量
transcript.whisperx[22].start 540.057
transcript.whisperx[22].end 542.641
transcript.whisperx[22].text 而且我們也會尊重他們在業務佈局上的一些審慎的一些課而且他要經過經管會的同意他要經過當地政府的同意都有一定的程序你講的我懂啦養光可能是比較特別因為他進來就是政變之後有很多的不安定
transcript.whisperx[23].start 555.879
transcript.whisperx[23].end 558.961
transcript.whisperx[23].text 那其他的地方你如果這樣講是對的話你是說情況有所變更嗎不然當初要設分行也是要跟金管會申請經過審慎的考量之後才慎重的決定去設分行現在設了之後突然之間好幾家銀行都要測這個據點
transcript.whisperx[24].start 572.91
transcript.whisperx[24].end 602.353
transcript.whisperx[24].text 那就代表當初籌設時候的判斷跟現在實際的狀況是有所差距是變動的情況這個變動如果是外在環境的變動我們了解這個變動就要理由就要講出來要講清楚說明白好不好我們對你們很支持但是你們要加油你們的困境要向社會大眾說明在立法院講是沒有人聽得到的好不好這裡是講這裡現在是比例大小沒有在講道理的
transcript.whisperx[25].start 602.893
transcript.whisperx[25].end 604.374
transcript.whisperx[25].text 好謝謝委員謝謝委員期許謝謝好謝謝吳委員接下來我們請賴世保委員