iVOD / 170347

Field Value
IVOD_ID 170347
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/170347
日期 2026-07-08
會議資料.會議代碼 委員會-11-5-19-20
會議資料.會議代碼:str 第11屆第5會期經濟委員會第20次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 20
會議資料.種類 委員會
會議資料.委員會代碼[0] 19
會議資料.委員會代碼:str[0] 經濟委員會
會議資料.標題 第11屆第5會期經濟委員會第20次全體委員會議
影片種類 Clip
開始時間 2026-07-08T10:58:57+08:00
結束時間 2026-07-08T11:06:57+08:00
影片長度 00:08:00
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/4fafa81be08c8210ce019b62bf84398c3f9d9bcb29de6404d75944b02079af3054ed8f2ce0dbea445ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 邱志偉
委員發言時間 10:58:57 - 11:06:57
會議時間 2026-07-08T09:00:00+08:00
會議名稱 立法院第11屆第5會期經濟委員會第20次全體委員會議(事由:一、邀請經濟部部長、國家發展委員會主任委員、外交部首長、僑務委員會首長、大陸委員會首長、財政部首長、金融監督管理委員會首長、內政部首長就「協助海外台商因應地緣政治變化及區域經濟整合之輔導策略」進行報告,並備質詢。 二、邀請經濟部部長就「全國電力資源供需報告」進行報告,並備質詢。 【7月8日及7月9日二天一次會】)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 12.56909375
transcript.pyannote[0].end 15.15096875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 19.90971875
transcript.pyannote[1].end 22.62659375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 23.04846875
transcript.pyannote[2].end 24.93846875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 25.12409375
transcript.pyannote[3].end 26.10284375
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 26.23784375
transcript.pyannote[4].end 26.57534375
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 31.94159375
transcript.pyannote[5].end 32.92034375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 33.59534375
transcript.pyannote[6].end 37.10534375
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 37.74659375
transcript.pyannote[7].end 39.19784375
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 40.26096875
transcript.pyannote[8].end 40.95284375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 42.10034375
transcript.pyannote[9].end 42.48846875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 43.60221875
transcript.pyannote[10].end 43.97346875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 44.29409375
transcript.pyannote[11].end 45.82971875
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 47.17971875
transcript.pyannote[12].end 47.48346875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 48.31034375
transcript.pyannote[13].end 48.59721875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 49.77846875
transcript.pyannote[14].end 50.45346875
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 50.68971875
transcript.pyannote[15].end 51.01034375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 51.22971875
transcript.pyannote[16].end 51.78659375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 52.36034375
transcript.pyannote[17].end 54.85784375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 55.17846875
transcript.pyannote[18].end 57.25409375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 57.76034375
transcript.pyannote[19].end 63.44721875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 64.17284375
transcript.pyannote[20].end 65.28659375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 66.06284375
transcript.pyannote[21].end 67.37909375
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 67.85159375
transcript.pyannote[22].end 69.45471875
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 70.01159375
transcript.pyannote[23].end 72.49221875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 73.30221875
transcript.pyannote[24].end 76.59284375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 76.76159375
transcript.pyannote[25].end 82.31346875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 82.81971875
transcript.pyannote[26].end 85.87409375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 86.49846875
transcript.pyannote[27].end 90.32909375
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 90.90284375
transcript.pyannote[28].end 95.40846875
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 96.13409375
transcript.pyannote[29].end 98.71596875
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 99.03659375
transcript.pyannote[30].end 100.33596875
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 100.65659375
transcript.pyannote[31].end 101.36534375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 101.78721875
transcript.pyannote[32].end 102.15846875
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 103.08659375
transcript.pyannote[33].end 105.80346875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 106.47846875
transcript.pyannote[34].end 112.51971875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 113.21159375
transcript.pyannote[35].end 113.73471875
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 114.56159375
transcript.pyannote[36].end 120.09659375
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 120.56909375
transcript.pyannote[37].end 123.13409375
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 123.67409375
transcript.pyannote[38].end 124.29846875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 124.83846875
transcript.pyannote[39].end 127.97721875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 128.14596875
transcript.pyannote[40].end 131.70659375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 131.92596875
transcript.pyannote[41].end 132.93846875
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 133.63034375
transcript.pyannote[42].end 135.60471875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 135.97596875
transcript.pyannote[43].end 143.48534375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 143.73846875
transcript.pyannote[44].end 155.71971875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 156.90096875
transcript.pyannote[45].end 168.29159375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 168.89909375
transcript.pyannote[46].end 170.28284375
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 176.10471875
transcript.pyannote[47].end 176.35784375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 176.42534375
transcript.pyannote[48].end 184.59284375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 185.06534375
transcript.pyannote[49].end 189.45284375
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 189.62159375
transcript.pyannote[50].end 192.86159375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 193.21596875
transcript.pyannote[51].end 197.02971875
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 197.70471875
transcript.pyannote[52].end 201.18096875
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 201.40034375
transcript.pyannote[53].end 202.75034375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 202.75034375
transcript.pyannote[54].end 202.93596875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 202.93596875
transcript.pyannote[55].end 204.53909375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 204.79221875
transcript.pyannote[56].end 205.14659375
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 205.45034375
transcript.pyannote[57].end 206.96909375
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 207.39096875
transcript.pyannote[58].end 210.78284375
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 211.40721875
transcript.pyannote[59].end 214.37721875
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 214.98471875
transcript.pyannote[60].end 216.26721875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 216.89159375
transcript.pyannote[61].end 220.75596875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 221.19471875
transcript.pyannote[62].end 222.74721875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 223.08471875
transcript.pyannote[63].end 237.79971875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 238.10346875
transcript.pyannote[64].end 250.35471875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 248.41409375
transcript.pyannote[65].end 249.29159375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 250.35471875
transcript.pyannote[66].end 250.37159375
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 250.37159375
transcript.pyannote[67].end 250.42221875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 250.42221875
transcript.pyannote[68].end 250.54034375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 250.54034375
transcript.pyannote[69].end 250.82721875
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 251.45159375
transcript.pyannote[70].end 253.84784375
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 254.28659375
transcript.pyannote[71].end 260.95221875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 260.80034375
transcript.pyannote[72].end 262.18409375
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 262.60596875
transcript.pyannote[73].end 263.63534375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 262.63971875
transcript.pyannote[74].end 263.51721875
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 264.02346875
transcript.pyannote[75].end 267.07784375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 264.27659375
transcript.pyannote[76].end 264.32721875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 267.44909375
transcript.pyannote[77].end 279.43034375
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 279.81846875
transcript.pyannote[78].end 280.13909375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 280.78034375
transcript.pyannote[79].end 283.46346875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 283.88534375
transcript.pyannote[80].end 293.25096875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 293.25096875
transcript.pyannote[81].end 293.28471875
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 293.63909375
transcript.pyannote[82].end 294.02721875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 294.02721875
transcript.pyannote[83].end 298.09409375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 294.39846875
transcript.pyannote[84].end 294.87096875
transcript.pyannote[85].speaker SPEAKER_00
transcript.pyannote[85].start 298.46534375
transcript.pyannote[85].end 299.88284375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 300.30471875
transcript.pyannote[86].end 303.96659375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 303.96659375
transcript.pyannote[87].end 304.84409375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 305.28284375
transcript.pyannote[88].end 305.29971875
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 305.29971875
transcript.pyannote[89].end 310.91909375
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 310.04159375
transcript.pyannote[90].end 311.15534375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 311.15534375
transcript.pyannote[91].end 311.17221875
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 311.17221875
transcript.pyannote[92].end 311.18909375
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 311.18909375
transcript.pyannote[93].end 311.40846875
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 311.40846875
transcript.pyannote[94].end 311.72909375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 311.72909375
transcript.pyannote[95].end 311.77971875
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 311.77971875
transcript.pyannote[96].end 311.79659375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 312.57284375
transcript.pyannote[97].end 313.26471875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 314.31096875
transcript.pyannote[98].end 320.74034375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 315.86346875
transcript.pyannote[99].end 324.38534375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 321.36471875
transcript.pyannote[100].end 323.08596875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 325.49909375
transcript.pyannote[101].end 327.38909375
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 327.77721875
transcript.pyannote[102].end 331.33784375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 328.92471875
transcript.pyannote[103].end 331.37159375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 331.37159375
transcript.pyannote[104].end 331.57409375
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 332.38409375
transcript.pyannote[105].end 338.03721875
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 338.94846875
transcript.pyannote[106].end 339.03284375
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 339.03284375
transcript.pyannote[107].end 339.33659375
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 339.33659375
transcript.pyannote[108].end 339.74159375
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 339.38721875
transcript.pyannote[109].end 339.69096875
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 339.74159375
transcript.pyannote[110].end 349.12409375
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 349.78221875
transcript.pyannote[111].end 354.57471875
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 354.70971875
transcript.pyannote[112].end 355.77284375
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 356.05971875
transcript.pyannote[113].end 363.16409375
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 363.43409375
transcript.pyannote[114].end 373.40721875
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 363.55221875
transcript.pyannote[115].end 363.90659375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 369.57659375
transcript.pyannote[116].end 371.50034375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 373.84596875
transcript.pyannote[117].end 377.62596875
transcript.pyannote[118].speaker SPEAKER_00
transcript.pyannote[118].start 378.11534375
transcript.pyannote[118].end 381.81096875
transcript.pyannote[119].speaker SPEAKER_00
transcript.pyannote[119].start 382.24971875
transcript.pyannote[119].end 384.52784375
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 384.88221875
transcript.pyannote[120].end 386.51909375
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 387.22784375
transcript.pyannote[121].end 388.12221875
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 388.17284375
transcript.pyannote[122].end 388.99971875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 389.30346875
transcript.pyannote[123].end 392.40846875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 392.64471875
transcript.pyannote[124].end 393.43784375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 393.89346875
transcript.pyannote[125].end 402.04409375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 402.28034375
transcript.pyannote[126].end 424.99409375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 425.12909375
transcript.pyannote[127].end 429.02721875
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 429.02721875
transcript.pyannote[128].end 435.79409375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 429.60096875
transcript.pyannote[129].end 430.57971875
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 436.72221875
transcript.pyannote[130].end 440.72159375
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 440.92409375
transcript.pyannote[131].end 444.34971875
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 444.60284375
transcript.pyannote[132].end 445.96971875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 445.96971875
transcript.pyannote[133].end 446.05409375
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 446.05409375
transcript.pyannote[134].end 446.23971875
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 446.23971875
transcript.pyannote[135].end 446.32409375
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 446.32409375
transcript.pyannote[136].end 446.54346875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 446.54346875
transcript.pyannote[137].end 446.56034375
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 446.69534375
transcript.pyannote[138].end 446.74596875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 446.74596875
transcript.pyannote[139].end 462.25409375
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 446.86409375
transcript.pyannote[140].end 447.43784375
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 462.47346875
transcript.pyannote[141].end 471.33284375
transcript.pyannote[142].speaker SPEAKER_00
transcript.pyannote[142].start 471.75471875
transcript.pyannote[142].end 472.27784375
transcript.pyannote[143].speaker SPEAKER_00
transcript.pyannote[143].start 472.53096875
transcript.pyannote[143].end 476.42909375
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 476.69909375
transcript.pyannote[144].end 476.76659375
transcript.pyannote[145].speaker SPEAKER_00
transcript.pyannote[145].start 477.23909375
transcript.pyannote[145].end 478.50471875
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 479.12909375
transcript.pyannote[146].end 482.33534375
transcript.pyannote[147].speaker SPEAKER_01
transcript.pyannote[147].start 479.16284375
transcript.pyannote[147].end 481.00221875
transcript.whisperx[0].start 12.588
transcript.whisperx[0].end 15.93
transcript.whisperx[0].text 好 謝謝接下來我們請邱兆偉質詢謝謝主席是不是請喬委會的副委員長來請喬委會委員好 委員長您知道台灣最大的貿易逆差國是哪一國最大的貿易逆差國美國吧
transcript.whisperx[1].start 42.148
transcript.whisperx[1].end 59.302
transcript.whisperx[1].text 不是 部長 進一步 國務部長是韓國 是我們東北亞共同生活圈 共同安全圈的一個重要鄰國我們對韓國出口是8379億
transcript.whisperx[2].start 66.749
transcript.whisperx[2].end 89.124
transcript.whisperx[2].text 韓國輸台的金額是1.94兆貿易逆差是1.16兆所以我們對韓國的關係不管是當然安全跟政治是比較屬於上位但是經貿跟人與人交流我覺得人與人交流是非常的暢旺這個台岸之間每年往來大概300萬
transcript.whisperx[3].start 90.97
transcript.whisperx[3].end 99.708
transcript.whisperx[3].text 那這個貿易為什麼會形成那麼大的逆差這個我想請教一下部長之前為什麼會提這個問題就是說僑委會對
transcript.whisperx[4].start 103.841
transcript.whisperx[4].end 132.74
transcript.whisperx[4].text 對韓國的這個台僑組織或者是他們的當然台商會他們主要是大企業我們在韓國的投資比較少所以目前沒有發展出這個台商會的組織所以我覺得僑委會會長應該去一趟韓國了解一下這個台僑的成立的狀況因為有一些年輕世代他們因為婚姻關係因為工作關係但是沒有有組織的系統去把它整合起來
transcript.whisperx[5].start 133.72
transcript.whisperx[5].end 150.712
transcript.whisperx[5].text 所以我希望說你們僑屋秘書要更努力把這些在韓國工作也好 因為婚姻關係也好 或者求學也好這個秘籍能夠掌握甚至我們在韓國的這些僑胞台僑能夠組成一個組織讓他們能夠發揮這個僑社的力量
transcript.whisperx[6].start 157.22
transcript.whisperx[6].end 168.076
transcript.whisperx[6].text 謝謝委員我們努力的來去往這個方向了解跟發展那台商會你們可以去輔導一下是是好謝謝謝謝林副委員長是接下來請這個經濟部鞏部長好請鞏部長
transcript.whisperx[7].start 176.547
transcript.whisperx[7].end 204.15
transcript.whisperx[7].text 因為我昨天剛從韓國回來當然他們這個政治關係不像台日那麼的這個弱弱但是只要有做就會有成長所以雖然說這個民間交流觀光非常的韓劇非常流行所以他們是文化輸出大國不只文化輸出大國他們也是對台灣是貿易的大順差所以說從台灣賺了很多錢
transcript.whisperx[8].start 205.549
transcript.whisperx[8].end 207.814
transcript.whisperx[8].text 所以我們應該怎麼樣經營跟韓國的關係從經貿怎麼樣把這個貿易的逆差能夠做一些調整
transcript.whisperx[9].start 215.149
transcript.whisperx[9].end 235.765
transcript.whisperx[9].text 逆差不會那麼大 去年2025年這個逆差成長了23%主要原因是什麼 部長主要原因是因為現在就是AI Server的部分嘛那現在HBM 就是記憶體晶片的部分大部分是三星跟SK HENES在做嘛
transcript.whisperx[10].start 236.505
transcript.whisperx[10].end 261.943
transcript.whisperx[10].text 那當然少部分美光是在台灣有在做但是大部分他做完以後就要拿到台灣來封裝封裝完以後再賣到美國或其他國家去所以變成這種情況是健康的嗎所以我們希望就是說我們有一些我們記憶體的這些HBM可以在台灣可以有機會發展起來有沒有具體的做法
transcript.whisperx[11].start 262.703
transcript.whisperx[11].end 279.114
transcript.whisperx[11].text 或者策略把台海目前的貿易狀況做一些調整對現在就是說包括在台灣增加投資的美光或者是我們在地的包括南亞科技啊他們也在做記憶體的這個晶片上能量的這個提升
transcript.whisperx[12].start 280.836
transcript.whisperx[12].end 299.324
transcript.whisperx[12].text 不只是高科技產業有很多其他的譬如說農產品也好等等對文化的部分我想韓國的文化是台灣人還算蠻喜歡的啦那很多的這些如果文化可以用貿易量來看的話我們是文化逆差國韓國對我們是文化順差國高我順差
transcript.whisperx[13].start 305.807
transcript.whisperx[13].end 329.697
transcript.whisperx[13].text 韓國的很多的朋友或年輕朋友事實上來台灣觀光旅遊是蠻多的你也聽過BTS嗎沒有不是啦現場沒有看過啦但是有聽過連部長都有聽過我也是昨天才聽過我想在場大家都知道BTS在高雄舉辦的這個韓團內容應該知道齁
transcript.whisperx[14].start 333.579
transcript.whisperx[14].end 353.82
transcript.whisperx[14].text 韓團在高雄舉辦的這個演唱會是買不到票 我們也買不到票所以韓文化輸出的力量很大然後我不曉得他們貿易對台灣的貿易這個順差是如此之大所以這個你要從這個貿易量來看要怎麼去調整對台灣貿易比較有利的方向是是是
transcript.whisperx[15].start 354.861
transcript.whisperx[15].end 370.507
transcript.whisperx[15].text 那另外這個青能的合作因為青能現在還是一個示範計畫所以未來韓國跟日本已經發展很久了而且有一些青能的載具青能的藝術工具台灣現在還是一個示範點在高雄怎麼樣學習韓熱的經驗
transcript.whisperx[16].start 373.928
transcript.whisperx[16].end 386.28
transcript.whisperx[16].text 把青人透過跟他們合作也好你要有個戰略甚至學習他們的發展經驗把青人能夠導向一個重要的再生能源
transcript.whisperx[17].start 387.267
transcript.whisperx[17].end 410.186
transcript.whisperx[17].text 那個部長您的看法呢對就是因為輕能它的就是有怎麼產新運輕還有輕的運用這有三段那我們就有多元的在實施當中那日韓它有一個很大的這個應用範圍就是它的輕能車他們有在不斷的往這個發展我們將來對於輕能的運用
transcript.whisperx[18].start 414.329
transcript.whisperx[18].end 435.541
transcript.whisperx[18].text 現在比較在實驗階段的除了剛剛講的那個輕能車一部之外另外就是怎麼樣混清的這個發電那這個台電公司已經有在做這樣示範性的一些好像力道不夠然後執行力也有在提升你把韓國日本那一套學習過來就好了
transcript.whisperx[19].start 437.049
transcript.whisperx[19].end 458.245
transcript.whisperx[19].text 然後跟他們有更多的合作我覺得這是可以做一個能源合作的一個戰略思考特別跟日本、韓國本來我們是想跟日本合作有關運輕的部分從澳洲有運輕可以來台灣但是後來日本有實驗性但是這個實驗性應該已經是暫停了
transcript.whisperx[20].start 461.027
transcript.whisperx[20].end 479.268
transcript.whisperx[20].text 因為那個成本比起這個比原來規劃裡面要超出的非常多顯然就是說他的成熟度可能還要再等一段時間好 我還有七八個問題但是我要遵守我定下來的時間一身作者好 謝謝 蕭長偉