IVOD_ID |
160483 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/160483 |
日期 |
2025-04-23 |
會議資料.會議代碼 |
委員會-11-3-20-9 |
會議資料.會議代碼:str |
第11屆第3會期財政委員會第9次全體委員會議 |
會議資料.屆 |
11 |
會議資料.會期 |
3 |
會議資料.會次 |
9 |
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3會期財政委員會第9次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2025-04-23T10:00:30+08:00 |
結束時間 |
2025-04-23T10:11:52+08:00 |
影片長度 |
00:11:22 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/27ac2f54fdf75cc077d1e70f87a5200ec0f390e692fb4f2487b5e96e7cd6ee72f151987b109fadff5ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
吳秉叡 |
委員發言時間 |
10:00:30 - 10:11:52 |
會議時間 |
2025-04-23T09:00:00+08:00 |
會議名稱 |
立法院第11屆第3會期財政委員會第9次全體委員會議(事由:一、審查「貨物稅條例」34案:
(一) 本院委員葉元之等21人擬具「貨物稅條例刪除部分條文草案」案。
(二) 本院委員廖先翔等16人擬具「貨物稅條例刪除第八條條文草案」案。
(三) 本院台灣民眾黨黨團擬具「貨物稅條例第十一條、第十一條之一及第三十七條條文修正草案」案。
(四) 本院委員邱若華等20人擬具「貨物稅條例第十一條條文修正草案」案。
(五) 本院委員魯明哲等16人、委員顏寬恒等19人、委員羅廷瑋等16人、委員賴士葆等21人、委員邱鎮軍等22人、委員徐欣瑩等27人、委員翁曉玲等17人、委員羅明才等16人、委員郭國文等17人、委員王鴻薇等24人、委員廖偉翔等17人、委員許宇甄等21人、委員黃建賓等16人、委員林思銘等21人、委員萬美玲等16人分別擬具「貨物稅條例第十一條之一條文修正草案」等15案。
(六) 本院委員李坤城等24人擬具「貨物稅條例第十一條之一、第十二條之五及第十二條之六條文修正草案」案。
(七) 本院委員鄭天財Sra Kacaw等19人、委員林思銘等19人、委員涂權吉等17人、委員陳玉珍等19人、委員馬文君等18人、委員王世堅等19人、委員張智倫等25人、委員魯明哲等16人、委員王鴻薇等19人、委員楊瓊瓔等20人、委員邱鎮軍等24人、委員萬美玲等18人、委員廖偉翔等17人分別擬具「貨物稅條例第十二條條文修正草案」等13案。
(八) 本院委員邱鎮軍等19人擬具「貨物稅條例第十二條之三條文修正草案」案。
二、審查人民請願案有關「貨物稅條例」7案。) |
transcript.pyannote[0].speaker |
SPEAKER_02 |
transcript.pyannote[0].start |
0.03096875 |
transcript.pyannote[0].end |
0.70596875 |
transcript.pyannote[1].speaker |
SPEAKER_02 |
transcript.pyannote[1].start |
0.95909375 |
transcript.pyannote[1].end |
3.49034375 |
transcript.pyannote[2].speaker |
SPEAKER_01 |
transcript.pyannote[2].start |
5.76846875 |
transcript.pyannote[2].end |
6.32534375 |
transcript.pyannote[3].speaker |
SPEAKER_02 |
transcript.pyannote[3].start |
7.75971875 |
transcript.pyannote[3].end |
14.83034375 |
transcript.pyannote[4].speaker |
SPEAKER_02 |
transcript.pyannote[4].start |
15.25221875 |
transcript.pyannote[4].end |
15.80909375 |
transcript.pyannote[5].speaker |
SPEAKER_01 |
transcript.pyannote[5].start |
15.28596875 |
transcript.pyannote[5].end |
15.99471875 |
transcript.pyannote[6].speaker |
SPEAKER_01 |
transcript.pyannote[6].start |
16.14659375 |
transcript.pyannote[6].end |
19.87596875 |
transcript.pyannote[7].speaker |
SPEAKER_01 |
transcript.pyannote[7].start |
20.11221875 |
transcript.pyannote[7].end |
31.11471875 |
transcript.pyannote[8].speaker |
SPEAKER_02 |
transcript.pyannote[8].start |
20.14596875 |
transcript.pyannote[8].end |
20.19659375 |
transcript.pyannote[9].speaker |
SPEAKER_00 |
transcript.pyannote[9].start |
25.61346875 |
transcript.pyannote[9].end |
25.98471875 |
transcript.pyannote[10].speaker |
SPEAKER_01 |
transcript.pyannote[10].start |
31.31721875 |
transcript.pyannote[10].end |
34.91159375 |
transcript.pyannote[11].speaker |
SPEAKER_00 |
transcript.pyannote[11].start |
31.33409375 |
transcript.pyannote[11].end |
31.38471875 |
transcript.pyannote[12].speaker |
SPEAKER_02 |
transcript.pyannote[12].start |
31.38471875 |
transcript.pyannote[12].end |
31.70534375 |
transcript.pyannote[13].speaker |
SPEAKER_00 |
transcript.pyannote[13].start |
31.70534375 |
transcript.pyannote[13].end |
31.73909375 |
transcript.pyannote[14].speaker |
SPEAKER_01 |
transcript.pyannote[14].start |
35.01284375 |
transcript.pyannote[14].end |
41.47596875 |
transcript.pyannote[15].speaker |
SPEAKER_02 |
transcript.pyannote[15].start |
39.40034375 |
transcript.pyannote[15].end |
40.51409375 |
transcript.pyannote[16].speaker |
SPEAKER_02 |
transcript.pyannote[16].start |
40.85159375 |
transcript.pyannote[16].end |
42.23534375 |
transcript.pyannote[17].speaker |
SPEAKER_01 |
transcript.pyannote[17].start |
41.59409375 |
transcript.pyannote[17].end |
42.79221875 |
transcript.pyannote[18].speaker |
SPEAKER_02 |
transcript.pyannote[18].start |
42.79221875 |
transcript.pyannote[18].end |
44.44596875 |
transcript.pyannote[19].speaker |
SPEAKER_02 |
transcript.pyannote[19].start |
44.76659375 |
transcript.pyannote[19].end |
50.13284375 |
transcript.pyannote[20].speaker |
SPEAKER_02 |
transcript.pyannote[20].start |
50.68971875 |
transcript.pyannote[20].end |
53.01846875 |
transcript.pyannote[21].speaker |
SPEAKER_02 |
transcript.pyannote[21].start |
53.81159375 |
transcript.pyannote[21].end |
54.70596875 |
transcript.pyannote[22].speaker |
SPEAKER_01 |
transcript.pyannote[22].start |
53.86221875 |
transcript.pyannote[22].end |
66.68721875 |
transcript.pyannote[23].speaker |
SPEAKER_02 |
transcript.pyannote[23].start |
59.16096875 |
transcript.pyannote[23].end |
59.86971875 |
transcript.pyannote[24].speaker |
SPEAKER_02 |
transcript.pyannote[24].start |
66.92346875 |
transcript.pyannote[24].end |
68.49284375 |
transcript.pyannote[25].speaker |
SPEAKER_01 |
transcript.pyannote[25].start |
68.66159375 |
transcript.pyannote[25].end |
69.30284375 |
transcript.pyannote[26].speaker |
SPEAKER_01 |
transcript.pyannote[26].start |
69.64034375 |
transcript.pyannote[26].end |
72.54284375 |
transcript.pyannote[27].speaker |
SPEAKER_01 |
transcript.pyannote[27].start |
76.86284375 |
transcript.pyannote[27].end |
89.65409375 |
transcript.pyannote[28].speaker |
SPEAKER_01 |
transcript.pyannote[28].start |
89.94096875 |
transcript.pyannote[28].end |
102.63096875 |
transcript.pyannote[29].speaker |
SPEAKER_02 |
transcript.pyannote[29].start |
102.68159375 |
transcript.pyannote[29].end |
104.13284375 |
transcript.pyannote[30].speaker |
SPEAKER_02 |
transcript.pyannote[30].start |
104.60534375 |
transcript.pyannote[30].end |
104.77409375 |
transcript.pyannote[31].speaker |
SPEAKER_01 |
transcript.pyannote[31].start |
105.56721875 |
transcript.pyannote[31].end |
107.11971875 |
transcript.pyannote[32].speaker |
SPEAKER_01 |
transcript.pyannote[32].start |
108.04784375 |
transcript.pyannote[32].end |
129.96846875 |
transcript.pyannote[33].speaker |
SPEAKER_02 |
transcript.pyannote[33].start |
108.52034375 |
transcript.pyannote[33].end |
109.56659375 |
transcript.pyannote[34].speaker |
SPEAKER_02 |
transcript.pyannote[34].start |
129.96846875 |
transcript.pyannote[34].end |
131.57159375 |
transcript.pyannote[35].speaker |
SPEAKER_01 |
transcript.pyannote[35].start |
131.57159375 |
transcript.pyannote[35].end |
137.41034375 |
transcript.pyannote[36].speaker |
SPEAKER_02 |
transcript.pyannote[36].start |
131.60534375 |
transcript.pyannote[36].end |
131.63909375 |
transcript.pyannote[37].speaker |
SPEAKER_02 |
transcript.pyannote[37].start |
131.94284375 |
transcript.pyannote[37].end |
133.20846875 |
transcript.pyannote[38].speaker |
SPEAKER_02 |
transcript.pyannote[38].start |
136.07721875 |
transcript.pyannote[38].end |
143.65409375 |
transcript.pyannote[39].speaker |
SPEAKER_02 |
transcript.pyannote[39].start |
144.22784375 |
transcript.pyannote[39].end |
145.42596875 |
transcript.pyannote[40].speaker |
SPEAKER_01 |
transcript.pyannote[40].start |
145.61159375 |
transcript.pyannote[40].end |
146.32034375 |
transcript.pyannote[41].speaker |
SPEAKER_02 |
transcript.pyannote[41].start |
146.94471875 |
transcript.pyannote[41].end |
147.60284375 |
transcript.pyannote[42].speaker |
SPEAKER_02 |
transcript.pyannote[42].start |
147.90659375 |
transcript.pyannote[42].end |
149.22284375 |
transcript.pyannote[43].speaker |
SPEAKER_01 |
transcript.pyannote[43].start |
149.47596875 |
transcript.pyannote[43].end |
154.50471875 |
transcript.pyannote[44].speaker |
SPEAKER_02 |
transcript.pyannote[44].start |
154.70721875 |
transcript.pyannote[44].end |
156.47909375 |
transcript.pyannote[45].speaker |
SPEAKER_01 |
transcript.pyannote[45].start |
157.05284375 |
transcript.pyannote[45].end |
157.45784375 |
transcript.pyannote[46].speaker |
SPEAKER_01 |
transcript.pyannote[46].start |
157.93034375 |
transcript.pyannote[46].end |
164.46096875 |
transcript.pyannote[47].speaker |
SPEAKER_02 |
transcript.pyannote[47].start |
164.98409375 |
transcript.pyannote[47].end |
165.03471875 |
transcript.pyannote[48].speaker |
SPEAKER_01 |
transcript.pyannote[48].start |
165.03471875 |
transcript.pyannote[48].end |
165.20346875 |
transcript.pyannote[49].speaker |
SPEAKER_02 |
transcript.pyannote[49].start |
165.20346875 |
transcript.pyannote[49].end |
165.28784375 |
transcript.pyannote[50].speaker |
SPEAKER_01 |
transcript.pyannote[50].start |
165.28784375 |
transcript.pyannote[50].end |
165.32159375 |
transcript.pyannote[51].speaker |
SPEAKER_02 |
transcript.pyannote[51].start |
165.32159375 |
transcript.pyannote[51].end |
165.42284375 |
transcript.pyannote[52].speaker |
SPEAKER_01 |
transcript.pyannote[52].start |
165.42284375 |
transcript.pyannote[52].end |
165.45659375 |
transcript.pyannote[53].speaker |
SPEAKER_02 |
transcript.pyannote[53].start |
165.45659375 |
transcript.pyannote[53].end |
166.77284375 |
transcript.pyannote[54].speaker |
SPEAKER_01 |
transcript.pyannote[54].start |
166.95846875 |
transcript.pyannote[54].end |
168.17346875 |
transcript.pyannote[55].speaker |
SPEAKER_02 |
transcript.pyannote[55].start |
168.34221875 |
transcript.pyannote[55].end |
171.34596875 |
transcript.pyannote[56].speaker |
SPEAKER_02 |
transcript.pyannote[56].start |
172.76346875 |
transcript.pyannote[56].end |
174.65346875 |
transcript.pyannote[57].speaker |
SPEAKER_02 |
transcript.pyannote[57].start |
175.00784375 |
transcript.pyannote[57].end |
176.52659375 |
transcript.pyannote[58].speaker |
SPEAKER_02 |
transcript.pyannote[58].start |
177.21846875 |
transcript.pyannote[58].end |
183.59721875 |
transcript.pyannote[59].speaker |
SPEAKER_02 |
transcript.pyannote[59].start |
184.28909375 |
transcript.pyannote[59].end |
185.99346875 |
transcript.pyannote[60].speaker |
SPEAKER_02 |
transcript.pyannote[60].start |
186.53346875 |
transcript.pyannote[60].end |
187.52909375 |
transcript.pyannote[61].speaker |
SPEAKER_02 |
transcript.pyannote[61].start |
187.88346875 |
transcript.pyannote[61].end |
189.63846875 |
transcript.pyannote[62].speaker |
SPEAKER_00 |
transcript.pyannote[62].start |
191.02221875 |
transcript.pyannote[62].end |
195.15659375 |
transcript.pyannote[63].speaker |
SPEAKER_00 |
transcript.pyannote[63].start |
195.59534375 |
transcript.pyannote[63].end |
198.41346875 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
198.93659375 |
transcript.pyannote[64].end |
203.72909375 |
transcript.pyannote[65].speaker |
SPEAKER_02 |
transcript.pyannote[65].start |
202.88534375 |
transcript.pyannote[65].end |
203.88096875 |
transcript.pyannote[66].speaker |
SPEAKER_00 |
transcript.pyannote[66].start |
204.28596875 |
transcript.pyannote[66].end |
206.58096875 |
transcript.pyannote[67].speaker |
SPEAKER_00 |
transcript.pyannote[67].start |
207.00284375 |
transcript.pyannote[67].end |
207.05346875 |
transcript.pyannote[68].speaker |
SPEAKER_02 |
transcript.pyannote[68].start |
207.05346875 |
transcript.pyannote[68].end |
207.07034375 |
transcript.pyannote[69].speaker |
SPEAKER_00 |
transcript.pyannote[69].start |
207.07034375 |
transcript.pyannote[69].end |
207.40784375 |
transcript.pyannote[70].speaker |
SPEAKER_02 |
transcript.pyannote[70].start |
207.08721875 |
transcript.pyannote[70].end |
207.47534375 |
transcript.pyannote[71].speaker |
SPEAKER_00 |
transcript.pyannote[71].start |
207.45846875 |
transcript.pyannote[71].end |
207.99846875 |
transcript.pyannote[72].speaker |
SPEAKER_02 |
transcript.pyannote[72].start |
207.49221875 |
transcript.pyannote[72].end |
207.50909375 |
transcript.pyannote[73].speaker |
SPEAKER_00 |
transcript.pyannote[73].start |
208.57221875 |
transcript.pyannote[73].end |
217.19534375 |
transcript.pyannote[74].speaker |
SPEAKER_00 |
transcript.pyannote[74].start |
217.63409375 |
transcript.pyannote[74].end |
219.60846875 |
transcript.pyannote[75].speaker |
SPEAKER_02 |
transcript.pyannote[75].start |
219.32159375 |
transcript.pyannote[75].end |
221.83596875 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
221.83596875 |
transcript.pyannote[76].end |
221.92034375 |
transcript.pyannote[77].speaker |
SPEAKER_02 |
transcript.pyannote[77].start |
221.92034375 |
transcript.pyannote[77].end |
221.93721875 |
transcript.pyannote[78].speaker |
SPEAKER_02 |
transcript.pyannote[78].start |
222.73034375 |
transcript.pyannote[78].end |
226.93221875 |
transcript.pyannote[79].speaker |
SPEAKER_02 |
transcript.pyannote[79].start |
227.82659375 |
transcript.pyannote[79].end |
229.17659375 |
transcript.pyannote[80].speaker |
SPEAKER_02 |
transcript.pyannote[80].start |
229.96971875 |
transcript.pyannote[80].end |
231.94409375 |
transcript.pyannote[81].speaker |
SPEAKER_02 |
transcript.pyannote[81].start |
233.12534375 |
transcript.pyannote[81].end |
245.39346875 |
transcript.pyannote[82].speaker |
SPEAKER_02 |
transcript.pyannote[82].start |
246.50721875 |
transcript.pyannote[82].end |
248.56596875 |
transcript.pyannote[83].speaker |
SPEAKER_01 |
transcript.pyannote[83].start |
249.00471875 |
transcript.pyannote[83].end |
249.35909375 |
transcript.pyannote[84].speaker |
SPEAKER_02 |
transcript.pyannote[84].start |
249.25784375 |
transcript.pyannote[84].end |
252.95346875 |
transcript.pyannote[85].speaker |
SPEAKER_02 |
transcript.pyannote[85].start |
253.39221875 |
transcript.pyannote[85].end |
258.84284375 |
transcript.pyannote[86].speaker |
SPEAKER_02 |
transcript.pyannote[86].start |
259.19721875 |
transcript.pyannote[86].end |
262.92659375 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
263.95596875 |
transcript.pyannote[87].end |
264.64784375 |
transcript.pyannote[88].speaker |
SPEAKER_02 |
transcript.pyannote[88].start |
264.64784375 |
transcript.pyannote[88].end |
265.20471875 |
transcript.pyannote[89].speaker |
SPEAKER_02 |
transcript.pyannote[89].start |
265.62659375 |
transcript.pyannote[89].end |
267.90471875 |
transcript.pyannote[90].speaker |
SPEAKER_02 |
transcript.pyannote[90].start |
268.57971875 |
transcript.pyannote[90].end |
271.58346875 |
transcript.pyannote[91].speaker |
SPEAKER_02 |
transcript.pyannote[91].start |
272.42721875 |
transcript.pyannote[91].end |
274.41846875 |
transcript.pyannote[92].speaker |
SPEAKER_02 |
transcript.pyannote[92].start |
275.32971875 |
transcript.pyannote[92].end |
285.04971875 |
transcript.pyannote[93].speaker |
SPEAKER_02 |
transcript.pyannote[93].start |
285.40409375 |
transcript.pyannote[93].end |
292.87971875 |
transcript.pyannote[94].speaker |
SPEAKER_02 |
transcript.pyannote[94].start |
293.65596875 |
transcript.pyannote[94].end |
295.68096875 |
transcript.pyannote[95].speaker |
SPEAKER_02 |
transcript.pyannote[95].start |
296.79471875 |
transcript.pyannote[95].end |
299.76471875 |
transcript.pyannote[96].speaker |
SPEAKER_02 |
transcript.pyannote[96].start |
301.11471875 |
transcript.pyannote[96].end |
308.48909375 |
transcript.pyannote[97].speaker |
SPEAKER_02 |
transcript.pyannote[97].start |
308.79284375 |
transcript.pyannote[97].end |
312.20159375 |
transcript.pyannote[98].speaker |
SPEAKER_02 |
transcript.pyannote[98].start |
315.89721875 |
transcript.pyannote[98].end |
316.40346875 |
transcript.pyannote[99].speaker |
SPEAKER_02 |
transcript.pyannote[99].start |
316.55534375 |
transcript.pyannote[99].end |
317.33159375 |
transcript.pyannote[100].speaker |
SPEAKER_02 |
transcript.pyannote[100].start |
317.80409375 |
transcript.pyannote[100].end |
320.35221875 |
transcript.pyannote[101].speaker |
SPEAKER_02 |
transcript.pyannote[101].start |
320.84159375 |
transcript.pyannote[101].end |
326.84909375 |
transcript.pyannote[102].speaker |
SPEAKER_02 |
transcript.pyannote[102].start |
327.30471875 |
transcript.pyannote[102].end |
331.89471875 |
transcript.pyannote[103].speaker |
SPEAKER_02 |
transcript.pyannote[103].start |
332.60346875 |
transcript.pyannote[103].end |
333.83534375 |
transcript.pyannote[104].speaker |
SPEAKER_02 |
transcript.pyannote[104].start |
334.86471875 |
transcript.pyannote[104].end |
336.61971875 |
transcript.pyannote[105].speaker |
SPEAKER_02 |
transcript.pyannote[105].start |
337.15971875 |
transcript.pyannote[105].end |
338.88096875 |
transcript.pyannote[106].speaker |
SPEAKER_02 |
transcript.pyannote[106].start |
339.45471875 |
transcript.pyannote[106].end |
341.07471875 |
transcript.pyannote[107].speaker |
SPEAKER_02 |
transcript.pyannote[107].start |
341.68221875 |
transcript.pyannote[107].end |
342.96471875 |
transcript.pyannote[108].speaker |
SPEAKER_02 |
transcript.pyannote[108].start |
343.74096875 |
transcript.pyannote[108].end |
345.27659375 |
transcript.pyannote[109].speaker |
SPEAKER_02 |
transcript.pyannote[109].start |
346.23846875 |
transcript.pyannote[109].end |
348.63471875 |
transcript.pyannote[110].speaker |
SPEAKER_02 |
transcript.pyannote[110].start |
349.10721875 |
transcript.pyannote[110].end |
351.45284375 |
transcript.pyannote[111].speaker |
SPEAKER_02 |
transcript.pyannote[111].start |
352.14471875 |
transcript.pyannote[111].end |
352.48221875 |
transcript.pyannote[112].speaker |
SPEAKER_02 |
transcript.pyannote[112].start |
352.98846875 |
transcript.pyannote[112].end |
353.93346875 |
transcript.pyannote[113].speaker |
SPEAKER_02 |
transcript.pyannote[113].start |
354.62534375 |
transcript.pyannote[113].end |
356.61659375 |
transcript.pyannote[114].speaker |
SPEAKER_02 |
transcript.pyannote[114].start |
356.93721875 |
transcript.pyannote[114].end |
357.93284375 |
transcript.pyannote[115].speaker |
SPEAKER_02 |
transcript.pyannote[115].start |
358.00034375 |
transcript.pyannote[115].end |
359.99159375 |
transcript.pyannote[116].speaker |
SPEAKER_02 |
transcript.pyannote[116].start |
360.41346875 |
transcript.pyannote[116].end |
361.54409375 |
transcript.pyannote[117].speaker |
SPEAKER_02 |
transcript.pyannote[117].start |
362.99534375 |
transcript.pyannote[117].end |
364.90221875 |
transcript.pyannote[118].speaker |
SPEAKER_02 |
transcript.pyannote[118].start |
365.77971875 |
transcript.pyannote[118].end |
367.33221875 |
transcript.pyannote[119].speaker |
SPEAKER_02 |
transcript.pyannote[119].start |
367.75409375 |
transcript.pyannote[119].end |
369.77909375 |
transcript.pyannote[120].speaker |
SPEAKER_00 |
transcript.pyannote[120].start |
371.24721875 |
transcript.pyannote[120].end |
372.15846875 |
transcript.pyannote[121].speaker |
SPEAKER_00 |
transcript.pyannote[121].start |
372.41159375 |
transcript.pyannote[121].end |
373.59284375 |
transcript.pyannote[122].speaker |
SPEAKER_00 |
transcript.pyannote[122].start |
374.21721875 |
transcript.pyannote[122].end |
375.22971875 |
transcript.pyannote[123].speaker |
SPEAKER_00 |
transcript.pyannote[123].start |
376.51221875 |
transcript.pyannote[123].end |
383.95409375 |
transcript.pyannote[124].speaker |
SPEAKER_00 |
transcript.pyannote[124].start |
384.56159375 |
transcript.pyannote[124].end |
385.20284375 |
transcript.pyannote[125].speaker |
SPEAKER_00 |
transcript.pyannote[125].start |
385.50659375 |
transcript.pyannote[125].end |
386.94096875 |
transcript.pyannote[126].speaker |
SPEAKER_00 |
transcript.pyannote[126].start |
387.39659375 |
transcript.pyannote[126].end |
393.43784375 |
transcript.pyannote[127].speaker |
SPEAKER_00 |
transcript.pyannote[127].start |
393.64034375 |
transcript.pyannote[127].end |
396.07034375 |
transcript.pyannote[128].speaker |
SPEAKER_00 |
transcript.pyannote[128].start |
396.23909375 |
transcript.pyannote[128].end |
399.17534375 |
transcript.pyannote[129].speaker |
SPEAKER_00 |
transcript.pyannote[129].start |
399.44534375 |
transcript.pyannote[129].end |
403.93409375 |
transcript.pyannote[130].speaker |
SPEAKER_00 |
transcript.pyannote[130].start |
404.11971875 |
transcript.pyannote[130].end |
417.90659375 |
transcript.pyannote[131].speaker |
SPEAKER_02 |
transcript.pyannote[131].start |
418.15971875 |
transcript.pyannote[131].end |
419.50971875 |
transcript.pyannote[132].speaker |
SPEAKER_02 |
transcript.pyannote[132].start |
419.83034375 |
transcript.pyannote[132].end |
421.95659375 |
transcript.pyannote[133].speaker |
SPEAKER_02 |
transcript.pyannote[133].start |
422.58096875 |
transcript.pyannote[133].end |
430.03971875 |
transcript.pyannote[134].speaker |
SPEAKER_02 |
transcript.pyannote[134].start |
430.42784375 |
transcript.pyannote[134].end |
431.40659375 |
transcript.pyannote[135].speaker |
SPEAKER_02 |
transcript.pyannote[135].start |
432.28409375 |
transcript.pyannote[135].end |
435.13596875 |
transcript.pyannote[136].speaker |
SPEAKER_02 |
transcript.pyannote[136].start |
436.62096875 |
transcript.pyannote[136].end |
438.37596875 |
transcript.pyannote[137].speaker |
SPEAKER_02 |
transcript.pyannote[137].start |
438.69659375 |
transcript.pyannote[137].end |
442.42596875 |
transcript.pyannote[138].speaker |
SPEAKER_02 |
transcript.pyannote[138].start |
443.52284375 |
transcript.pyannote[138].end |
446.40846875 |
transcript.pyannote[139].speaker |
SPEAKER_02 |
transcript.pyannote[139].start |
446.50971875 |
transcript.pyannote[139].end |
447.91034375 |
transcript.pyannote[140].speaker |
SPEAKER_02 |
transcript.pyannote[140].start |
449.12534375 |
transcript.pyannote[140].end |
451.09971875 |
transcript.pyannote[141].speaker |
SPEAKER_02 |
transcript.pyannote[141].start |
452.04471875 |
transcript.pyannote[141].end |
459.97596875 |
transcript.pyannote[142].speaker |
SPEAKER_00 |
transcript.pyannote[142].start |
460.54971875 |
transcript.pyannote[142].end |
462.00096875 |
transcript.pyannote[143].speaker |
SPEAKER_00 |
transcript.pyannote[143].start |
462.47346875 |
transcript.pyannote[143].end |
470.42159375 |
transcript.pyannote[144].speaker |
SPEAKER_02 |
transcript.pyannote[144].start |
469.57784375 |
transcript.pyannote[144].end |
475.51784375 |
transcript.pyannote[145].speaker |
SPEAKER_00 |
transcript.pyannote[145].start |
475.75409375 |
transcript.pyannote[145].end |
479.09534375 |
transcript.pyannote[146].speaker |
SPEAKER_00 |
transcript.pyannote[146].start |
479.50034375 |
transcript.pyannote[146].end |
482.47034375 |
transcript.pyannote[147].speaker |
SPEAKER_02 |
transcript.pyannote[147].start |
482.82471875 |
transcript.pyannote[147].end |
495.61596875 |
transcript.pyannote[148].speaker |
SPEAKER_02 |
transcript.pyannote[148].start |
495.98721875 |
transcript.pyannote[148].end |
503.10846875 |
transcript.pyannote[149].speaker |
SPEAKER_02 |
transcript.pyannote[149].start |
503.95221875 |
transcript.pyannote[149].end |
504.98159375 |
transcript.pyannote[150].speaker |
SPEAKER_02 |
transcript.pyannote[150].start |
506.12909375 |
transcript.pyannote[150].end |
508.17096875 |
transcript.pyannote[151].speaker |
SPEAKER_02 |
transcript.pyannote[151].start |
510.31409375 |
transcript.pyannote[151].end |
512.89596875 |
transcript.pyannote[152].speaker |
SPEAKER_02 |
transcript.pyannote[152].start |
515.29221875 |
transcript.pyannote[152].end |
516.59159375 |
transcript.pyannote[153].speaker |
SPEAKER_00 |
transcript.pyannote[153].start |
518.00909375 |
transcript.pyannote[153].end |
518.24534375 |
transcript.pyannote[154].speaker |
SPEAKER_00 |
transcript.pyannote[154].start |
519.24096875 |
transcript.pyannote[154].end |
538.68096875 |
transcript.pyannote[155].speaker |
SPEAKER_02 |
transcript.pyannote[155].start |
538.30971875 |
transcript.pyannote[155].end |
543.70971875 |
transcript.pyannote[156].speaker |
SPEAKER_02 |
transcript.pyannote[156].start |
544.21596875 |
transcript.pyannote[156].end |
545.02596875 |
transcript.pyannote[157].speaker |
SPEAKER_02 |
transcript.pyannote[157].start |
545.29596875 |
transcript.pyannote[157].end |
552.82221875 |
transcript.pyannote[158].speaker |
SPEAKER_02 |
transcript.pyannote[158].start |
554.02034375 |
transcript.pyannote[158].end |
555.18471875 |
transcript.pyannote[159].speaker |
SPEAKER_02 |
transcript.pyannote[159].start |
555.30284375 |
transcript.pyannote[159].end |
557.49659375 |
transcript.pyannote[160].speaker |
SPEAKER_02 |
transcript.pyannote[160].start |
558.20534375 |
transcript.pyannote[160].end |
564.12846875 |
transcript.pyannote[161].speaker |
SPEAKER_02 |
transcript.pyannote[161].start |
565.29284375 |
transcript.pyannote[161].end |
566.03534375 |
transcript.pyannote[162].speaker |
SPEAKER_02 |
transcript.pyannote[162].start |
566.74409375 |
transcript.pyannote[162].end |
572.70096875 |
transcript.pyannote[163].speaker |
SPEAKER_02 |
transcript.pyannote[163].start |
573.51096875 |
transcript.pyannote[163].end |
575.40096875 |
transcript.pyannote[164].speaker |
SPEAKER_02 |
transcript.pyannote[164].start |
576.58221875 |
transcript.pyannote[164].end |
577.71284375 |
transcript.pyannote[165].speaker |
SPEAKER_02 |
transcript.pyannote[165].start |
578.28659375 |
transcript.pyannote[165].end |
580.63221875 |
transcript.pyannote[166].speaker |
SPEAKER_02 |
transcript.pyannote[166].start |
581.47596875 |
transcript.pyannote[166].end |
582.72471875 |
transcript.pyannote[167].speaker |
SPEAKER_02 |
transcript.pyannote[167].start |
584.20971875 |
transcript.pyannote[167].end |
585.79596875 |
transcript.pyannote[168].speaker |
SPEAKER_02 |
transcript.pyannote[168].start |
587.06159375 |
transcript.pyannote[168].end |
587.75346875 |
transcript.pyannote[169].speaker |
SPEAKER_02 |
transcript.pyannote[169].start |
588.24284375 |
transcript.pyannote[169].end |
591.48284375 |
transcript.pyannote[170].speaker |
SPEAKER_02 |
transcript.pyannote[170].start |
592.02284375 |
transcript.pyannote[170].end |
592.49534375 |
transcript.pyannote[171].speaker |
SPEAKER_02 |
transcript.pyannote[171].start |
592.84971875 |
transcript.pyannote[171].end |
594.79034375 |
transcript.pyannote[172].speaker |
SPEAKER_02 |
transcript.pyannote[172].start |
594.97596875 |
transcript.pyannote[172].end |
596.19096875 |
transcript.pyannote[173].speaker |
SPEAKER_02 |
transcript.pyannote[173].start |
596.56221875 |
transcript.pyannote[173].end |
600.30846875 |
transcript.pyannote[174].speaker |
SPEAKER_02 |
transcript.pyannote[174].start |
600.96659375 |
transcript.pyannote[174].end |
601.99596875 |
transcript.pyannote[175].speaker |
SPEAKER_02 |
transcript.pyannote[175].start |
602.58659375 |
transcript.pyannote[175].end |
603.05909375 |
transcript.pyannote[176].speaker |
SPEAKER_02 |
transcript.pyannote[176].start |
603.61596875 |
transcript.pyannote[176].end |
605.26971875 |
transcript.pyannote[177].speaker |
SPEAKER_02 |
transcript.pyannote[177].start |
606.24846875 |
transcript.pyannote[177].end |
618.82034375 |
transcript.pyannote[178].speaker |
SPEAKER_02 |
transcript.pyannote[178].start |
619.12409375 |
transcript.pyannote[178].end |
623.27534375 |
transcript.pyannote[179].speaker |
SPEAKER_01 |
transcript.pyannote[179].start |
623.84909375 |
transcript.pyannote[179].end |
642.31034375 |
transcript.pyannote[180].speaker |
SPEAKER_02 |
transcript.pyannote[180].start |
641.21346875 |
transcript.pyannote[180].end |
646.02284375 |
transcript.pyannote[181].speaker |
SPEAKER_01 |
transcript.pyannote[181].start |
642.96846875 |
transcript.pyannote[181].end |
643.01909375 |
transcript.pyannote[182].speaker |
SPEAKER_02 |
transcript.pyannote[182].start |
646.47846875 |
transcript.pyannote[182].end |
649.66784375 |
transcript.pyannote[183].speaker |
SPEAKER_02 |
transcript.pyannote[183].start |
650.69721875 |
transcript.pyannote[183].end |
654.40971875 |
transcript.pyannote[184].speaker |
SPEAKER_02 |
transcript.pyannote[184].start |
654.96659375 |
transcript.pyannote[184].end |
662.05409375 |
transcript.pyannote[185].speaker |
SPEAKER_01 |
transcript.pyannote[185].start |
662.05409375 |
transcript.pyannote[185].end |
667.97721875 |
transcript.pyannote[186].speaker |
SPEAKER_02 |
transcript.pyannote[186].start |
663.42096875 |
transcript.pyannote[186].end |
666.15471875 |
transcript.pyannote[187].speaker |
SPEAKER_02 |
transcript.pyannote[187].start |
667.45409375 |
transcript.pyannote[187].end |
671.74034375 |
transcript.pyannote[188].speaker |
SPEAKER_01 |
transcript.pyannote[188].start |
671.80784375 |
transcript.pyannote[188].end |
672.61784375 |
transcript.pyannote[189].speaker |
SPEAKER_02 |
transcript.pyannote[189].start |
675.55409375 |
transcript.pyannote[189].end |
678.50721875 |
transcript.whisperx[0].start |
0.009 |
transcript.whisperx[0].end |
2.212 |
transcript.whisperx[0].text |
現在美國的汽車如果進口到台灣,總共要付多少稅金? |
transcript.whisperx[1].start |
16.345 |
transcript.whisperx[1].end |
37.34 |
transcript.whisperx[1].text |
目前就是進口的關稅是17.5%然後再加上我們的貨物稅如果是小客車的話他有25%或30%2000cc以下是25%然後2000cc以上是30%那當然加起來就是最高就是47.5%然後如果再加上我們的營業稅5%的話那就是大概52.5% |
transcript.whisperx[2].start |
40.962 |
transcript.whisperx[2].end |
52.324 |
transcript.whisperx[2].text |
最高是52.5那台灣賣去美國的相同的汽車假設是油車的話假設是2000CC以上的話進到美國去要付多少關稅 |
transcript.whisperx[3].start |
53.874 |
transcript.whisperx[3].end |
72.088 |
transcript.whisperx[3].text |
付多少稅金?關稅是2.5%但是因為他們也是有課徵貨物稅加起來多少?加起來多少這個我們沒有辦法講因為貨物稅的金額我們只有一個區間區間可以區間講啊那就是你們那個我只能講大概是 |
transcript.whisperx[4].start |
77.069 |
transcript.whisperx[4].end |
103.757 |
transcript.whisperx[4].text |
對 它對於那個高耗油量的汽車的話它是以這個每輛車以行駛公里9.1以上的話是每公升課三萬三千塊錢的這叫什麼 美元嗎每公升 你有沒有弄錯單位換算台幣是每公升三萬三千元的貨物稅然後最高可以課到二十五萬四千一百元每公升是值 |
transcript.whisperx[5].start |
105.612 |
transcript.whisperx[5].end |
131.015 |
transcript.whisperx[5].text |
每公升耗油啦對不是吧它是以每公升行駛的里程數9公里以上的話它就是計算只是它這個我們因為我們從搜尋到的資料是一個數額所以這個部分可能還沒辦法詳細的跟人報告我們可能會後看就是我們的稅比人家多了多嘛對不對 |
transcript.whisperx[6].start |
132.076 |
transcript.whisperx[6].end |
157.242 |
transcript.whisperx[6].text |
坦白講就是以關稅來看是相對高但是後稅總體加在一起啦我要總體比我不要因為我們自己把人家稅分成好幾項然後說我只有拿關稅跟你比我覺得這樣不好啊是 了解我說是不是比人家高是確實是有稍微是偏高如果以關稅來看就已經偏高了台灣是貿易順差國呢了解 |
transcript.whisperx[7].start |
157.95 |
transcript.whisperx[7].end |
182.348 |
transcript.whisperx[7].text |
但是因為也跟我們報告因為我們從美國進口的車子很多都是電動車電動車現在都是只有關稅17.5而已電動車是整車輸入嗎對對整車輸入好那另外要請教那個懲罰署陳副署長每次提到這個汽車的這個關稅啊貨物稅啊就尤其是關稅的部分經濟部就一直在講說這個台灣有多少人靠這個汽車產業在 |
transcript.whisperx[8].start |
184.535 |
transcript.whisperx[8].end |
203.094 |
transcript.whisperx[8].text |
從事這個汽車產業靠這個才有工作到底真正的人數是多少報告委員汽車除了整車廠還有零件廠那整車廠目前是一萬就業人數零件廠是七萬合計八萬但是呢那組裝廠呢組裝廠就是整車廠一萬 |
transcript.whisperx[9].start |
208.659 |
transcript.whisperx[9].end |
230.987 |
transcript.whisperx[9].text |
除了這個以外因為有很多模具相關的供應商像什麼塑膠零件等等那些整體加起來整個約有30萬的那你乾脆把那個煉油廠也都算進來好了啦你連那個汽車這個零件的模具連開模具你就算那我現在問一個問題啦齁 |
transcript.whisperx[10].start |
233.168 |
transcript.whisperx[10].end |
262.751 |
transcript.whisperx[10].text |
台灣的市場就算你飽和他總共的量數也是有限所以台灣的零件廠必須要走向全世界其實台灣有很多的汽車零件他是行銷全世界他賣的很好那種反而是希望雙方都降低稅金嘛最好我們出口的國家稅金也降低台灣的稅金也降低讓台灣的零件既然可以行銷全世界這樣才能養活更多的人啊 |
transcript.whisperx[11].start |
264.742 |
transcript.whisperx[11].end |
292.268 |
transcript.whisperx[11].text |
所以每次講的時候你都把它混為一談會影響的就是只有汽車的組裝廠嘛就是所謂的整車廠這一部分嘛所以我是覺得這個大家講的時候要講清楚好不好你每次都就 憨不啷噹就講說三十幾萬然後現在跟我講說組裝廠的這個整車廠的一萬人然後汽車零件廠的七萬人然後再加上你有沒有沒啊 開沒啊 什麼的這個全部加在一起三十幾萬 |
transcript.whisperx[12].start |
293.717 |
transcript.whisperx[12].end |
312.126 |
transcript.whisperx[12].text |
我覺得你們這樣的講法不好欸經濟部應該就是就事論事啦齁這個事情如果弄清楚之後希望以後不要再聽到說啊這個如果怎麼樣的話會影響到三十幾萬人如果你這樣講的話哪一天跟美國談關稅降低了你是不是要救助這三十幾萬人啊 |
transcript.whisperx[13].start |
315.973 |
transcript.whisperx[13].end |
344.685 |
transcript.whisperx[13].text |
所以要在事實的基礎上談論問題啦這是我的希望第二個我上次也問過財政部部長你也回答我這個問題現在我們定義說只要在台灣加值超過35%的就算沒得贏台灣但是美國那一邊啊他說只要原料產品有35%以上是從中國來的他就算是中國的產品 |
transcript.whisperx[14].start |
346.274 |
transcript.whisperx[14].end |
374.916 |
transcript.whisperx[14].text |
那我就要問一個問題當然這個問題是你現在是不是邏輯上給他推理有中國的零件或是中國的原料百分之五十在台灣加值百分之五十輸出到美國去台灣說這是台灣made in Taiwan美國說是made in China那到底是made in Taiwan還是made in China報告委員我們現在第一點就是 |
transcript.whisperx[15].start |
377.01 |
transcript.whisperx[15].end |
401.624 |
transcript.whisperx[15].text |
貨物的原產地由進口國海關來認定所以是哪一個國家進口那個國家的海關來認定第二點根據世界海關組織官務組織他們有規定就是現在台灣的原產地規則是follow這個世界官務組織的一個規定就是使用進口原材料你如果在台灣附加價值達到35% |
transcript.whisperx[16].start |
404.245 |
transcript.whisperx[16].end |
430.761 |
transcript.whisperx[16].text |
或者你的稅則有轉換所以我使用進口的原料在台灣附加價值超過35%你就可以視同是台灣原產這是我們目前的規定啊就是這個規定喔對台灣帶來莫大的危機啊所以當台灣的廠商信誓旦旦說對啊我沒得贏台灣啊我出口當然沒得贏台灣所以我出口要台灣出口是台灣製造 |
transcript.whisperx[17].start |
432.521 |
transcript.whisperx[17].end |
459.673 |
transcript.whisperx[17].text |
從美國的觀點就是你就台灣在替中國洗產地對不對進口國認為35%的原料來自中國他就認為是中國製造結果我們這邊的廠商在我們政府的規定我這是台灣製造啊我台灣製造所以我出口去美國啊那美國就剛好用那個標準說你看你這就是台灣在替中國洗產地所以我直接要問說這個問題到底要如何解決啊 |
transcript.whisperx[18].start |
460.972 |
transcript.whisperx[18].end |
478.04 |
transcript.whisperx[18].text |
報告委員 我們進口國認定這個原產地規則是各國的通則那我們這個部分我們會來跟我跟你講川普就是要改變世界的貿易規則嘛你看不懂他在改變世界的貿易規則嗎是 我們理解那我們會來研議說怎麼來處理這個我們進口原產地的規則 |
transcript.whisperx[19].start |
483.004 |
transcript.whisperx[19].end |
501.115 |
transcript.whisperx[19].text |
對啊 這個我是覺得這個是我們一個很大的危機我現在看一看那個洗產地的問題我們台灣用35%實在是太寬鬆了我跟你講中國的這個電動車現在全世界大家都在想辦法要防堵它如果照你的標準我弄65%的中國的電動車來然後我台灣給你組裝加值超過35%你們沒得贏台灣啊台灣人能相信這是沒得贏台灣嗎 |
transcript.whisperx[20].start |
510.353 |
transcript.whisperx[20].end |
516.142 |
transcript.whisperx[20].text |
那中國用你台灣這個標準給你弄進來那台灣就要接受嗎 |
transcript.whisperx[21].start |
519.561 |
transcript.whisperx[21].end |
539.713 |
transcript.whisperx[21].text |
委員我們除了我剛剛講的那兩個原則六月碼轉換跟35%的這個附加價值其實還有一個叫做實質轉型的認定如果你認為特別的製程要在台灣發生這個都可以去規範我們可以來討論如何來認定針對我們MIT的產品如何來認定它是台灣我跟你講現在其實有兩個問題啦齁你所謂照全世界的標準 |
transcript.whisperx[22].start |
544.275 |
transcript.whisperx[22].end |
572.016 |
transcript.whisperx[22].text |
有兩個大國現在不準備照選制的標準第一個就是中國他不準備照世界的標準他參加WTO之後他從來就沒有照世界標準他到處在犯規所以才引起美國對他的制裁嘛那再來就是美國川普因為上台之後為了要解決這個問題所以他現在要改變世界貿易規則就像你台灣就夾在兩個中間然後就假裝說沒有我就照世界規則我跟你講你現在照世界規則你會死的 |
transcript.whisperx[23].start |
573.55 |
transcript.whisperx[23].end |
585.375 |
transcript.whisperx[23].text |
在現在這個時空環境之下你對中國要特別對待他因為他不照WTO來的那你對待美國要怎麼樣好好的跟他談 |
transcript.whisperx[24].start |
587.113 |
transcript.whisperx[24].end |
604.865 |
transcript.whisperx[24].text |
假設台灣的關稅談判會失敗我認為最大的可能性就是美國一直懷疑你台灣在替中國洗慘地這是最大的危機所以我一直問財政部說你們那個小額小額包裹對不對美國現在都在制裁 |
transcript.whisperx[25].start |
606.291 |
transcript.whisperx[25].end |
623.117 |
transcript.whisperx[25].text |
要把那個小兒包裹要加到官司要加到120%從墨西哥去的從加拿大去的都一樣所以我們到底是要用什麼樣的態度我們希望他們不要多把他賴給說我現在在談判我現在在談判自己好好趕快想清楚因為我們問了這個問題問了好久了都沒答案啊 |
transcript.whisperx[26].start |
624.917 |
transcript.whisperx[26].end |
649.304 |
transcript.whisperx[26].text |
報告委員那基本上當然就是剛才就是針對那個中國藉由台灣洗產業這件事情我們一定是會嚴格查核的那至於剛才講到那個小兒包裹那個要不要就是考慮他的免稅取消的部分這個部分目前我們已經在積極的不是我是跟你講說你所謂的嚴格查核應該是要去把你那個標準到底是什麼重新 |
transcript.whisperx[27].start |
650.731 |
transcript.whisperx[27].end |
672.483 |
transcript.whisperx[27].text |
你如果照法令標準底下再來執行那你法令跟標準是錯的大前提是錯的時候你底下這個再怎麼執行結論也會是錯的啦所以我剛剛講的就是前提的檢討拜託加油啦我們台灣很大的危機在這個地方加油謝謝謝謝吳秉瑞吳委員來我們賴昭偉來 |