iVOD / 164646

Field Value
IVOD_ID 164646
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164646
日期 2025-10-23
會議資料.會議代碼 委員會-11-4-35-8
會議資料.會議代碼:str 第11屆第4會期外交及國防委員會第8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 8
會議資料.種類 委員會
會議資料.委員會代碼[0] 35
會議資料.委員會代碼:str[0] 外交及國防委員會
會議資料.標題 第11屆第4會期外交及國防委員會第8次全體委員會議
影片種類 Clip
開始時間 2025-10-23T09:26:44+08:00
結束時間 2025-10-23T09:42:29+08:00
影片長度 00:15:45
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/1f1f5c91750503d36e20be6fc66741298c2d94e6d34c5cc93bd93a97ab14671356f6ed70b2e814a85ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 王定宇
委員發言時間 09:26:44 - 09:42:29
會議時間 2025-10-23T09:00:00+08:00
會議名稱 立法院第11屆第4會期外交及國防委員會第8次全體委員會議(事由:邀請國防部部長顧立雄報告業務概況,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 0.72284375
transcript.pyannote[0].end 2.56221875
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 3.23721875
transcript.pyannote[1].end 4.28346875
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 11.69159375
transcript.pyannote[2].end 12.19784375
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 12.19784375
transcript.pyannote[3].end 12.40034375
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 12.40034375
transcript.pyannote[4].end 15.79221875
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 15.96096875
transcript.pyannote[5].end 21.17534375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 21.61409375
transcript.pyannote[6].end 25.93409375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 26.27159375
transcript.pyannote[7].end 28.24596875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 28.70159375
transcript.pyannote[8].end 41.30721875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 41.69534375
transcript.pyannote[9].end 52.86659375
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 53.86221875
transcript.pyannote[10].end 54.41909375
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 54.68909375
transcript.pyannote[11].end 56.56221875
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 57.37221875
transcript.pyannote[12].end 75.12471875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 77.36909375
transcript.pyannote[13].end 84.10221875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 84.57471875
transcript.pyannote[14].end 85.18221875
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 85.50284375
transcript.pyannote[15].end 86.93721875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 86.93721875
transcript.pyannote[16].end 87.89909375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 87.89909375
transcript.pyannote[17].end 94.17659375
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 91.59471875
transcript.pyannote[18].end 93.85596875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 94.31159375
transcript.pyannote[19].end 101.88846875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 94.56471875
transcript.pyannote[20].end 94.83471875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 102.20909375
transcript.pyannote[21].end 106.83284375
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 107.37284375
transcript.pyannote[22].end 109.02659375
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 109.39784375
transcript.pyannote[23].end 111.82784375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 112.03034375
transcript.pyannote[24].end 119.99534375
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 119.92784375
transcript.pyannote[25].end 124.02846875
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 124.12971875
transcript.pyannote[26].end 138.25409375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 127.65659375
transcript.pyannote[27].end 127.99409375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 138.99659375
transcript.pyannote[28].end 148.71659375
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 148.98659375
transcript.pyannote[29].end 151.83846875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 152.24346875
transcript.pyannote[30].end 153.82971875
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 154.18409375
transcript.pyannote[31].end 159.51659375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 160.27596875
transcript.pyannote[32].end 161.28846875
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 162.08159375
transcript.pyannote[33].end 171.31221875
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 170.41784375
transcript.pyannote[34].end 174.58596875
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 175.49721875
transcript.pyannote[35].end 177.48846875
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 177.96096875
transcript.pyannote[36].end 179.54721875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 179.68221875
transcript.pyannote[37].end 181.43721875
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 182.11221875
transcript.pyannote[38].end 185.33534375
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 185.57159375
transcript.pyannote[39].end 188.42346875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 188.62596875
transcript.pyannote[40].end 189.55409375
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 190.26284375
transcript.pyannote[41].end 196.42221875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 196.47284375
transcript.pyannote[42].end 197.77221875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 198.04221875
transcript.pyannote[43].end 209.58471875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 209.87159375
transcript.pyannote[44].end 210.52971875
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 211.08659375
transcript.pyannote[45].end 216.97596875
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 218.68034375
transcript.pyannote[46].end 219.23721875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 220.35096875
transcript.pyannote[47].end 233.02409375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 230.40846875
transcript.pyannote[48].end 230.96534375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 233.56409375
transcript.pyannote[49].end 246.16971875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 245.69721875
transcript.pyannote[50].end 269.82846875
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 271.33034375
transcript.pyannote[51].end 272.27534375
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 272.66346875
transcript.pyannote[52].end 276.81471875
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 276.96659375
transcript.pyannote[53].end 287.05784375
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 287.05784375
transcript.pyannote[54].end 293.75721875
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 287.09159375
transcript.pyannote[55].end 287.96909375
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 293.35221875
transcript.pyannote[56].end 293.74034375
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 293.75721875
transcript.pyannote[57].end 298.83659375
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 299.39346875
transcript.pyannote[58].end 310.27784375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 310.98659375
transcript.pyannote[59].end 315.98159375
transcript.pyannote[60].speaker SPEAKER_02
transcript.pyannote[60].start 316.06596875
transcript.pyannote[60].end 319.40721875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 316.13346875
transcript.pyannote[61].end 316.65659375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 319.05284375
transcript.pyannote[62].end 320.18346875
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 320.18346875
transcript.pyannote[63].end 323.30534375
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 320.20034375
transcript.pyannote[64].end 320.31846875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 323.86221875
transcript.pyannote[65].end 343.60596875
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 343.65659375
transcript.pyannote[66].end 343.69034375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 344.01096875
transcript.pyannote[67].end 345.51284375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 346.62659375
transcript.pyannote[68].end 347.16659375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 347.60534375
transcript.pyannote[69].end 364.00784375
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 356.02596875
transcript.pyannote[70].end 358.79346875
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 362.80971875
transcript.pyannote[71].end 364.31159375
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 364.31159375
transcript.pyannote[72].end 365.96534375
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 364.36221875
transcript.pyannote[73].end 367.21409375
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 366.72471875
transcript.pyannote[74].end 367.97346875
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 367.97346875
transcript.pyannote[75].end 368.64846875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 368.64846875
transcript.pyannote[76].end 368.74971875
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 368.74971875
transcript.pyannote[77].end 369.50909375
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 369.50909375
transcript.pyannote[78].end 369.54284375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 369.54284375
transcript.pyannote[79].end 370.18409375
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 370.18409375
transcript.pyannote[80].end 370.50471875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 370.50471875
transcript.pyannote[81].end 375.04409375
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 375.28034375
transcript.pyannote[82].end 381.00096875
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 381.40596875
transcript.pyannote[83].end 385.40534375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 385.48971875
transcript.pyannote[84].end 399.10784375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 399.66471875
transcript.pyannote[85].end 402.61784375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 403.17471875
transcript.pyannote[86].end 404.08596875
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 405.14909375
transcript.pyannote[87].end 405.97596875
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 406.97159375
transcript.pyannote[88].end 407.29221875
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 408.00096875
transcript.pyannote[89].end 410.92034375
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 410.95409375
transcript.pyannote[90].end 414.70034375
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 414.95346875
transcript.pyannote[91].end 415.78034375
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 416.08409375
transcript.pyannote[92].end 424.57221875
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 424.79159375
transcript.pyannote[93].end 441.19409375
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 441.44721875
transcript.pyannote[94].end 446.42534375
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 446.61096875
transcript.pyannote[95].end 452.58471875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 453.04034375
transcript.pyannote[96].end 459.95909375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 461.02221875
transcript.pyannote[97].end 470.38784375
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 470.67471875
transcript.pyannote[98].end 472.19346875
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 472.68284375
transcript.pyannote[99].end 476.59784375
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 477.40784375
transcript.pyannote[100].end 478.74096875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 478.97721875
transcript.pyannote[101].end 479.34846875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 479.70284375
transcript.pyannote[102].end 486.62159375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 487.14471875
transcript.pyannote[103].end 492.57846875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 492.91596875
transcript.pyannote[104].end 493.89471875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 492.94971875
transcript.pyannote[105].end 493.92846875
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 493.92846875
transcript.pyannote[106].end 496.20659375
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 496.84784375
transcript.pyannote[107].end 498.24846875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 499.44659375
transcript.pyannote[108].end 502.06221875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 500.40846875
transcript.pyannote[109].end 501.97784375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 501.97784375
transcript.pyannote[110].end 502.02846875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 503.05784375
transcript.pyannote[111].end 505.63971875
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 506.17971875
transcript.pyannote[112].end 507.04034375
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 507.69846875
transcript.pyannote[113].end 549.70034375
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 550.89846875
transcript.pyannote[114].end 551.87721875
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 552.60284375
transcript.pyannote[115].end 554.44221875
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 554.44221875
transcript.pyannote[116].end 559.06596875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 555.53909375
transcript.pyannote[117].end 555.97784375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 559.50471875
transcript.pyannote[118].end 560.41596875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 561.20909375
transcript.pyannote[119].end 563.36909375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 563.97659375
transcript.pyannote[120].end 566.22096875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 566.44034375
transcript.pyannote[121].end 577.62846875
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 576.27846875
transcript.pyannote[122].end 578.16846875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 578.16846875
transcript.pyannote[123].end 578.97846875
transcript.pyannote[124].speaker SPEAKER_02
transcript.pyannote[124].start 578.97846875
transcript.pyannote[124].end 580.00784375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 580.00784375
transcript.pyannote[125].end 580.34534375
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 580.34534375
transcript.pyannote[126].end 582.33659375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 580.36221875
transcript.pyannote[127].end 581.15534375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 582.33659375
transcript.pyannote[128].end 582.55596875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 582.55596875
transcript.pyannote[129].end 583.87221875
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 583.92284375
transcript.pyannote[130].end 583.93971875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 583.93971875
transcript.pyannote[131].end 584.31096875
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 584.31096875
transcript.pyannote[132].end 590.95971875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 590.95971875
transcript.pyannote[133].end 593.35596875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 591.58409375
transcript.pyannote[134].end 593.94659375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 593.94659375
transcript.pyannote[135].end 594.33471875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 594.33471875
transcript.pyannote[136].end 598.03034375
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 599.43096875
transcript.pyannote[137].end 601.47284375
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 602.01284375
transcript.pyannote[138].end 603.00846875
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 603.56534375
transcript.pyannote[139].end 607.39596875
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 607.54784375
transcript.pyannote[140].end 608.49284375
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 609.28596875
transcript.pyannote[141].end 610.11284375
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 610.55159375
transcript.pyannote[142].end 612.03659375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 612.39096875
transcript.pyannote[143].end 613.63971875
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 615.41159375
transcript.pyannote[144].end 620.62596875
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 620.81159375
transcript.pyannote[145].end 622.92096875
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 623.62971875
transcript.pyannote[146].end 625.55346875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 625.97534375
transcript.pyannote[147].end 628.00034375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 629.33346875
transcript.pyannote[148].end 630.73409375
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 631.00409375
transcript.pyannote[149].end 642.49596875
transcript.pyannote[150].speaker SPEAKER_02
transcript.pyannote[150].start 643.37346875
transcript.pyannote[150].end 644.60534375
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 644.95971875
transcript.pyannote[151].end 646.86659375
transcript.pyannote[152].speaker SPEAKER_01
transcript.pyannote[152].start 647.86221875
transcript.pyannote[152].end 656.14784375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 656.43471875
transcript.pyannote[153].end 668.06159375
transcript.pyannote[154].speaker SPEAKER_03
transcript.pyannote[154].start 656.68784375
transcript.pyannote[154].end 656.97471875
transcript.pyannote[155].speaker SPEAKER_02
transcript.pyannote[155].start 656.97471875
transcript.pyannote[155].end 657.07596875
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 657.90284375
transcript.pyannote[156].end 659.06721875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 664.63596875
transcript.pyannote[157].end 665.00721875
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 665.44596875
transcript.pyannote[158].end 685.03784375
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 670.94721875
transcript.pyannote[159].end 671.40284375
transcript.pyannote[160].speaker SPEAKER_02
transcript.pyannote[160].start 685.56096875
transcript.pyannote[160].end 693.71159375
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 691.99034375
transcript.pyannote[161].end 692.15909375
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 694.21784375
transcript.pyannote[162].end 727.95096875
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 728.50784375
transcript.pyannote[163].end 729.46971875
transcript.pyannote[164].speaker SPEAKER_02
transcript.pyannote[164].start 730.14471875
transcript.pyannote[164].end 736.62471875
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 737.29971875
transcript.pyannote[165].end 739.57784375
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 739.94909375
transcript.pyannote[166].end 741.56909375
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 742.78409375
transcript.pyannote[167].end 746.47971875
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 747.30659375
transcript.pyannote[168].end 767.94471875
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 767.26971875
transcript.pyannote[169].end 774.00284375
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 769.59846875
transcript.pyannote[170].end 770.49284375
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 773.58096875
transcript.pyannote[171].end 774.84659375
transcript.pyannote[172].speaker SPEAKER_01
transcript.pyannote[172].start 775.06596875
transcript.pyannote[172].end 784.46534375
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 784.46534375
transcript.pyannote[173].end 790.74284375
transcript.pyannote[174].speaker SPEAKER_01
transcript.pyannote[174].start 784.95471875
transcript.pyannote[174].end 785.51159375
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 791.31659375
transcript.pyannote[175].end 793.99971875
transcript.pyannote[176].speaker SPEAKER_02
transcript.pyannote[176].start 794.82659375
transcript.pyannote[176].end 795.43409375
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 795.73784375
transcript.pyannote[177].end 796.93596875
transcript.pyannote[178].speaker SPEAKER_00
transcript.pyannote[178].start 796.44659375
transcript.pyannote[178].end 797.03721875
transcript.pyannote[179].speaker SPEAKER_00
transcript.pyannote[179].start 797.10471875
transcript.pyannote[179].end 834.85409375
transcript.pyannote[180].speaker SPEAKER_02
transcript.pyannote[180].start 821.52284375
transcript.pyannote[180].end 824.20596875
transcript.pyannote[181].speaker SPEAKER_01
transcript.pyannote[181].start 824.20596875
transcript.pyannote[181].end 824.52659375
transcript.pyannote[182].speaker SPEAKER_02
transcript.pyannote[182].start 833.09909375
transcript.pyannote[182].end 833.53784375
transcript.pyannote[183].speaker SPEAKER_02
transcript.pyannote[183].start 833.62221875
transcript.pyannote[183].end 843.49409375
transcript.pyannote[184].speaker SPEAKER_00
transcript.pyannote[184].start 835.07346875
transcript.pyannote[184].end 835.84971875
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 837.19971875
transcript.pyannote[185].end 839.10659375
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 844.05096875
transcript.pyannote[186].end 844.97909375
transcript.pyannote[187].speaker SPEAKER_02
transcript.pyannote[187].start 845.70471875
transcript.pyannote[187].end 846.95346875
transcript.pyannote[188].speaker SPEAKER_02
transcript.pyannote[188].start 847.40909375
transcript.pyannote[188].end 849.01221875
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 848.43846875
transcript.pyannote[189].end 848.65784375
transcript.pyannote[190].speaker SPEAKER_00
transcript.pyannote[190].start 849.01221875
transcript.pyannote[190].end 849.34971875
transcript.pyannote[191].speaker SPEAKER_02
transcript.pyannote[191].start 849.34971875
transcript.pyannote[191].end 850.24409375
transcript.pyannote[192].speaker SPEAKER_00
transcript.pyannote[192].start 849.36659375
transcript.pyannote[192].end 849.38346875
transcript.pyannote[193].speaker SPEAKER_02
transcript.pyannote[193].start 850.42971875
transcript.pyannote[193].end 851.84721875
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 853.80471875
transcript.pyannote[194].end 856.79159375
transcript.pyannote[195].speaker SPEAKER_03
transcript.pyannote[195].start 856.79159375
transcript.pyannote[195].end 857.68596875
transcript.pyannote[196].speaker SPEAKER_02
transcript.pyannote[196].start 857.36534375
transcript.pyannote[196].end 858.00659375
transcript.pyannote[197].speaker SPEAKER_03
transcript.pyannote[197].start 858.68159375
transcript.pyannote[197].end 874.66221875
transcript.pyannote[198].speaker SPEAKER_02
transcript.pyannote[198].start 863.62596875
transcript.pyannote[198].end 866.64659375
transcript.pyannote[199].speaker SPEAKER_02
transcript.pyannote[199].start 874.18971875
transcript.pyannote[199].end 877.42971875
transcript.pyannote[200].speaker SPEAKER_02
transcript.pyannote[200].start 877.54784375
transcript.pyannote[200].end 879.26909375
transcript.pyannote[201].speaker SPEAKER_02
transcript.pyannote[201].start 879.65721875
transcript.pyannote[201].end 882.25596875
transcript.pyannote[202].speaker SPEAKER_02
transcript.pyannote[202].start 882.55971875
transcript.pyannote[202].end 885.02346875
transcript.pyannote[203].speaker SPEAKER_02
transcript.pyannote[203].start 885.36096875
transcript.pyannote[203].end 887.65596875
transcript.pyannote[204].speaker SPEAKER_02
transcript.pyannote[204].start 888.09471875
transcript.pyannote[204].end 890.76096875
transcript.pyannote[205].speaker SPEAKER_02
transcript.pyannote[205].start 891.13221875
transcript.pyannote[205].end 905.05409375
transcript.pyannote[206].speaker SPEAKER_02
transcript.pyannote[206].start 905.61096875
transcript.pyannote[206].end 915.60096875
transcript.pyannote[207].speaker SPEAKER_02
transcript.pyannote[207].start 916.15784375
transcript.pyannote[207].end 929.16846875
transcript.pyannote[208].speaker SPEAKER_02
transcript.pyannote[208].start 929.21909375
transcript.pyannote[208].end 935.85096875
transcript.pyannote[209].speaker SPEAKER_00
transcript.pyannote[209].start 935.54721875
transcript.pyannote[209].end 945.75659375
transcript.whisperx[0].start 1.18
transcript.whisperx[0].end 2.203
transcript.whisperx[0].text 謝謝主席 麻煩部長請部長
transcript.whisperx[1].start 12.985
transcript.whisperx[1].end 40.843
transcript.whisperx[1].text 部長早 幾個問題要請教部長第一個我們當然最近大概連續三波中共在點名懸賞通緝不管是軍情局 資通電軍或者新戰大隊等等當然這個做賊的很抓賊法律也不及於台灣那他的內容拼湊而來不見得正確這我們都知道 我就不重複了我要請教就是說畢竟他一直撈到了一些資料
transcript.whisperx[2].start 41.824
transcript.whisperx[2].end 52.602
transcript.whisperx[2].text 我們國防部對於洩漏的管道還有亡羊補牢把這個洞堵上了沒有那現在是軍安總隊在管這一塊呢還是哪個單位在管這一塊是不是先請教部長
transcript.whisperx[3].start 54.885
transcript.whisperx[3].end 72.409
transcript.whisperx[3].text 我想我們就這些任意拼湊的這些相關的資料我們第一個還是要說明這個是屬於中共認知作戰的一部分當然啦 產生一種心理規則所以我們的部分我們會要求這些這個
transcript.whisperx[4].start 77.461
transcript.whisperx[4].end 101.59
transcript.whisperx[4].text 同仁在這個社群媒體上面在從事任何相關的這些發布的時候不要做任何部長 堵上有兩個洞一個就是說他當然還是撈一些資料有的是從社群 有的是從個人的一些資料這個是過去已經發生的
transcript.whisperx[5].start 102.31
transcript.whisperx[5].end 111.63
transcript.whisperx[5].text 那在未來我們對於機敏單位我們的軍事官兵他的身份的保密的強化你們有沒有準備備案出來了
transcript.whisperx[6].start 112.076
transcript.whisperx[6].end 137.978
transcript.whisperx[6].text 對 現在就是會進行相關的一些進一步的保密作為包括研議利用運用化名的這個等等對 就是說我們不管就機敏單位我們自己知道啦當然我們不能全軍都用化名那等於沒有化名一樣嘛所以哪些單位要用化名來保護他的身份那我還是有個建議如果他在為國效力保護我們國家的情形下
transcript.whisperx[7].start 139.259
transcript.whisperx[7].end 161.066
transcript.whisperx[7].text 這些軍事官兵也是我們的弟兄我們應該要保護他們所以他如果遭遇到類似的情形不管有或沒有這個對對岸準不準我們不說對於相關的保護還有如果遭致損失應該比照軍情人員給予相當的補貼我不知道我們國防部現在有沒有進行這樣的作業或者有沒有這個打算
transcript.whisperx[8].start 162.393
transcript.whisperx[8].end 187.119
transcript.whisperx[8].text 我們會在第一時間對這些單位及官兵給予關懷輔導然後並且進一步採取適當的保護措施我舉個例子 史順文 史中將他現在是局長 他被點名了那他本身也許是資安專家他退下來之後呢 他找工作開始遇到困難或者他在旅行的時候 我那天問國安局我們不是Interpol的會員 中國是
transcript.whisperx[9].start 190.322
transcript.whisperx[9].end 216.816
transcript.whisperx[9].text 他把這個丟到裡面的黃色通緝名單紅色通緝名單的時候在旅行上會導致一些不便利還有一些風險那我們當然用化名來處理也是另外一種不便利他的資歷沒辦法去累積我的意思說就我們相關機敏工作人員他為國家犧牲付出那我們比照我剛才講軍情單位或者勤工相關單位有沒有適當的補貼的計畫有沒有這個打算
transcript.whisperx[10].start 220.393
transcript.whisperx[10].end 233.668
transcript.whisperx[10].text 因為這些人員我覺得他們發布的有點狀況不太一樣因為有自動電軍也有這個星戰大隊對 星戰大隊自動電軍是應該是比照情報機關
transcript.whisperx[11].start 235.467
transcript.whisperx[11].end 253.538
transcript.whisperx[11].text 那可能有相關的這些法制可以援引作為一個依據那新戰大隊的部分呢他並不是同情報機關我這邊我們今天沒有說要答案啦甚至有答案我們未必要在這邊揭露我建議部長跟相關單位去研議一下
transcript.whisperx[12].start 254.338
transcript.whisperx[12].end 269.623
transcript.whisperx[12].text 如果這樣的情形它屬於勤工法規定的單位我們有沒有什麼適當的救濟或者補貼計畫那對於非勤工法的單位我們有沒有什麼樣的打算至少讓弟兄知道我在這個國軍的大家庭裡面為國效力
transcript.whisperx[13].start 271.377
transcript.whisperx[13].end 297.535
transcript.whisperx[13].text 部隊有考慮到我 考慮到我面對的風險那我這一個部分我希望我們國防部如果有這樣的方案的話適當的方式讓委員會知道那我們接到一些部隊一些想法反應的時候也可以幫你們做說明因為事實上公布的有很多其實不是現役的人員並不是現役但他因為他現役時候的情形如果遭致損失我認為還是要給予關懷
transcript.whisperx[14].start 299.448
transcript.whisperx[14].end 322.927
transcript.whisperx[14].text 他不是因為他自己的事嘛他是因為幫國家效力遭遇到這樣的情形我們適度的關懷關懷的方案本席間沒有要求說一定要怎麼樣那你要有個方案出來讓他知道部隊有看到我這一塊這樣因為離退的人員將來回來也是我們的戰力啊他還沒有整個被除役嘛是 我們會來研議因為部長你本身也從國安會秘書長到國防部
transcript.whisperx[15].start 324.857
transcript.whisperx[15].end 345.194
transcript.whisperx[15].text 針對中國解放軍的這些動作我們有沒有一些類似的制裁的反制美國做過美國把他們的軍備局局長他們的名詞跟我們不一樣美國把軍備局局長的海外資產還有他的遷徙旅遊列為制裁對象我們國防部有沒有考慮
transcript.whisperx[16].start 347.728
transcript.whisperx[16].end 368.908
transcript.whisperx[16].text 我想就這個部分應該如果要討論這件事情的話我覺得應該是有國安會來協調因為中國在公布這件事情的時候據我了解也不是國防部在發布他是用發言單位 他在做星戰 認知作戰國務院還有公安局
transcript.whisperx[17].start 371.009
transcript.whisperx[17].end 398.749
transcript.whisperx[17].text 他是用發布通緝的方式他有他政治目的他把他內政化那美國曾經就中國幾個軍備相關的單位進行制裁那我不是說我們要完全這樣做我是說思考一下跟盟友特別是美國這邊來思考針對中國解放軍威脅我們國家的安全傷害區域安全的情形下大家可以合作讓這樣子的人
transcript.whisperx[18].start 401.371
transcript.whisperx[18].end 424.148
transcript.whisperx[18].text 這些賊要抓賊頭嘛 把他點一下 制裁一下因為根據中國自己的統計資料他們的高官貴人 海外藏的資產跟親屬是一大堆啦這個我是給部長建議 這當然可以到國安會去討論所以有關這個相關單位 資通監軍 軍情局等等這當然是一個認知作戰
transcript.whisperx[19].start 424.928
transcript.whisperx[19].end 451.028
transcript.whisperx[19].text 那我們一方面要穩定自己人的軍心另外一方面適當的反制作為讓對方被點到的人他也會難過一下像之前美國空軍學院把他們的火箭軍所有的座標連軍犬的訓練單位座標都列出來隔沒一兩個月他們火箭軍從司令副司令到這個他們叫做子戰員通通都換掉了這個是給部長做建議下一個議題我要請教這個比較嚴肅了
transcript.whisperx[20].start 453.609
transcript.whisperx[20].end 478.096
transcript.whisperx[20].text 我們的邊線筆其實今天剛好主席給我們比較長的時間我們來研究一下邊線筆我先請教部長我們對於部隊的邊線筆有一個名詞叫做戰力域值英文叫ThresholdThreshold就是臨界點戰力域值我們自己國軍有沒有設定那個是百分之多少這個是不是請
transcript.whisperx[21].start 479.758
transcript.whisperx[21].end 500.212
transcript.whisperx[21].text 你知道戰力域值這個是我們有關邊線比到達這個臨界點部隊就不太能夠拉出去了委員好 我首先說明我們國軍整個目標邊線比的目標是80%美軍的邊線比是多少它的臨界點在哪裡85%啦 我幫你查了啦美軍的戰力訓練跟裝備應該比我們好
transcript.whisperx[22].start 507.742
transcript.whisperx[22].end 527.61
transcript.whisperx[22].text 可他邊線比達到85%在美軍的定義這個部隊要研究為什麼發生這個事情這個部隊是沒辦法拉出去作戰的就是戰力減損的狀態那我們如果看一下我們國軍歷年的邊線比我現在邊線比還是用整體來除其實這樣除是不對的喔我應該看飛機 空軍的他負責維修飛機的
transcript.whisperx[23].start 530.851
transcript.whisperx[23].end 540.813
transcript.whisperx[23].text 我海軍陸戰隊的我裝甲兵的那樣看會更清楚但是以平均數來看2020年我們整體有88.572021年到87.572022年到822023年到802024年到78今年大概我看是75上下一直往下掉現在目前是78.6你看78.6比你們自己設的臨界點80%也是比較低嘛
transcript.whisperx[24].start 561.28
transcript.whisperx[24].end 590.163
transcript.whisperx[24].text 是跟委員說明就是說兩個方面第一個方面就是說從119年開始一直到現在其實每年的我們的編制數都是越來越多的那其實我們現在的人數跟111年的那你的意思是說我們的分母變大了我的編制有擴充我有增兵編制變大了但是蘿蔔坑變多了蘿蔔雖然沒有少但是坑變大所以數字掉下來嗎
transcript.whisperx[25].start 591.664
transcript.whisperx[25].end 611.001
transcript.whisperx[25].text 我們看細部數字 這數字是你們的喔你看一下喔 我們以士兵來看機部單位 72% 炮兵 68%你可以往下看 這數據你們都看得到兵的部分 你看防空飛彈指揮部 41%
transcript.whisperx[26].start 615.438
transcript.whisperx[26].end 642.2
transcript.whisperx[26].text 好幾個單位55有69 67以美軍的這個叫做threshold臨界點來講85%我們沒有一個沒有一個達標耶以我們自己的80%來看是很嚴重的低喔事關的部分只有少數幾個單位勉強達標多數都在按照我們國軍的最低域值戰力域值就最低標準限以下
transcript.whisperx[27].start 643.605
transcript.whisperx[27].end 646.7
transcript.whisperx[27].text 為什麼士兵為什麼士兵特別低
transcript.whisperx[28].start 648.098
transcript.whisperx[28].end 677.336
transcript.whisperx[28].text 跟委員說明我分三個方面來跟委員說明我們其實今年從去年到今年所有的成效都在逐步的提升沒有啊我看到數字是一年一年往下掉啊就是說除了編制數增加之外另外就是少子化我們在109年那個少子化我們20年前21年前少生的現在也不會補生啊少子化是一個區間那不是一年兩年我現在跟你研究的情形就是說你剛才講編制放大
transcript.whisperx[29].start 677.796
transcript.whisperx[29].end 691.006
transcript.whisperx[29].text 我可以接受但那個精準的數據因為屬於軍事機密我沒辦法去算你的編制如果增加了2000人足不足以影響這個比例我是懷疑喔以統計上來看我現在是要你找出這個問題來你看像裝甲單位
transcript.whisperx[30].start 694.549
transcript.whisperx[30].end 713.872
transcript.whisperx[30].text 裝甲是最需要專業的 我一個戰車營要多少人我們曾經因為車長邊線筆掉到六成五以下 第九屆吧當時我們就把少衛中衛到上衛他可以延到17年 擇優加三可以到20年
transcript.whisperx[31].start 715.253
transcript.whisperx[31].end 741.352
transcript.whisperx[31].text 讓中衛 少衛的年輕軍官他不用擔心他升不上去 領不到終身縫他有個願景 我們希望穩定嘛所以你要找出病因來 我們才能找出解方你用錯的話 會產生什麼情形邊線筆不足 第一個戰力不足第二個我們現在很多高精的裝備在操作上專業性不足的人來操作 他的危險性會升高
transcript.whisperx[32].start 742.907
transcript.whisperx[32].end 769.46
transcript.whisperx[32].text 會有這些問題所以你們到底有沒有研究過為什麼賓的部分特別低跟委員說明我們今年的數據我用今年數據來跟委員做說明不市府在112年是5400113年是5057元但是今年到現在10月份是2600多元也就是說不市府我們到目前為止比去年同期減少1400這個叫流盈率嘛是流盈率
transcript.whisperx[33].start 769.64
transcript.whisperx[33].end 793.535
transcript.whisperx[33].text 你們流營率沒有降 你們流營率在86%以上這是不適服的 那流營率我們部班標準是76去年部長來的時候 採取很多人性化的管理措施之後我們去年的流營率是82 今年到目前為止是86對 我印象你流營率 流營率到86 好事老兵長留久用 戰力強可是我們的邊線比較往下掉 就代表什麼問題
transcript.whisperx[34].start 794.898
transcript.whisperx[34].end 821.207
transcript.whisperx[34].text 招募沒有募新的進來跟委員報告因為我們如果拿三月的邊線比是76.9的話現在的邊線比78.6所以我當然希望我們還是朝向更好的方向發展那是第一點 第二點的話就是說有一些當時在討論各項佳績的時候就有討論到說哪些部隊的邊線比是
transcript.whisperx[35].start 821.587
transcript.whisperx[35].end 839.095
transcript.whisperx[35].text 所以這個就是我要最後建議的結論所以我們當時才會在這個從4月1號開始我們調升這個志願家族之外主要就著重在這個戰鬥部隊的他在不同的家族留下我們要的戰力嘛所以部長因為時間超過了我還聽說一個現象我們駝江級的邊線筆徑
transcript.whisperx[36].start 845.748
transcript.whisperx[36].end 848.19
transcript.whisperx[36].text 低於50%有沒有這個現象 海軍這邊 駝江級我們這個最新的這算艇啦 800噸上下的 艦啦
transcript.whisperx[37].start 858.895
transcript.whisperx[37].end 887.437
transcript.whisperx[37].text 海軍參謀長那個駝江級它整體的邊線大概會弱於大概70到72有到70到72沒有低於50低於50會嚇到應該是有些船的士兵那因為士兵數的確是有些船的士兵數會多跟少但我會按照任務來做邊背跟調整所以我建議部長跟我們軍總第一個把那一個戰力域值也就是那個臨界點在每個單位可能要把它當作一個科學來研究
transcript.whisperx[38].start 888.277
transcript.whisperx[38].end 915.18
transcript.whisperx[38].text 美軍是85%但他每個單位還不一樣到這個單位低於那裡對戰力就有減損的時候我們該做什麼作為這是第一個第二個我們4月1號或者過去這麼多年來其實國軍的薪資我聽到很多專業的將領在講薪資不是齊頭式的問題而是透過專業的加擠在特別辛苦或特別需要或特別專業的地方透過加擠把人才留下來
transcript.whisperx[39].start 917.182
transcript.whisperx[39].end 944.318
transcript.whisperx[39].text 這個部分其實我倒希望國防部提出一個方案跟我們委員會大家來討論我們都希望加薪但是每一分薪水每一分預算用在對的對國防有幫助的那這個我今天有關編線筆花了一點時間跟部長這邊討論我們未來繼續再探討這個話題我們希望看到你們提出一些改善的方案我想不管在招募或者不釋乎或者留營率或者是有關這個全面檢視整體檢視軍人待遇我們都會持續來進行好 謝謝 謝謝部長