iVOD / 149508

Field Value
IVOD_ID 149508
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/149508
日期 2024-03-07
會議資料.會議代碼 委員會-11-1-20-2
會議資料.會議代碼:str 第11屆第1會期財政委員會第2次全體委員會議
會議資料.屆 11
會議資料.會期 1
會議資料.會次 2
會議資料.種類 委員會
會議資料.委員會代碼[0] 20
會議資料.委員會代碼:str[0] 財政委員會
會議資料.標題 第11屆第1會期財政委員會第2次全體委員會議
影片種類 Clip
開始時間 2024-03-07T09:38:57+08:00
結束時間 2024-03-07T09:52:32+08:00
影片長度 00:13:35
支援功能[0] ai-transcript
支援功能[1] gazette
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/1441ba9c2015bdbe0c9902952b63f99ff84c29b94b9165f0f8ba9b0039caa7a6604f80897a2691b05ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 賴士葆
委員發言時間 09:38:57 - 09:52:32
會議時間 2024-03-07T09:00:00+08:00
會議名稱 立法院第11屆第1會期財政委員會第2次全體委員會議(事由:邀請財政部莊部長翠雲率所屬機關首長暨國營事業董事長、總經理(含各轉投資事業機構公股代表之董、監事)列席業務報告,並備質詢。 【3月4日及7日二天一次會】)
gazette.lineno 215
gazette.blocks[0][0] 賴委員士葆:(9時38分)謝謝主席以及各位先進。我們有請財政部的莊部長。
gazette.blocks[1][0] 主席:有請莊部長。
gazette.blocks[2][0] 莊部長翠雲:委員好。
gazette.blocks[3][0] 賴委員士葆:你早。我想先請問你……稍微停一下,電腦跑不出來。
gazette.blocks[4][0] 主席:等一下,我們時間暫停。
gazette.blocks[5][0] 主席(吳委員秉叡代):賴委員,抱歉,不然今天你就先質詢啦!
gazette.blocks[6][0] 賴委員士葆:好啦!就繼續修。
gazette.blocks[6][1] 金融營業稅5%,它的處理方式到年底到期嘛!財政部的立場是怎麼樣?是要繼續維持這樣子,3%營業稅、2%放在它的特別準備金那邊,那裡已經有兩、三千億了啦!你要怎麼處理?
gazette.blocks[7][0] 莊部長翠雲:跟委員報告,在營業稅法裡面是規定2%的金融營業稅免進入金融營業特別準備金,這是這個部分,並不是5%要落日。至於銀行業跟保險業經營專屬銀行保險本業的部分有一個5%,3%是歸國庫,2%還是進入金融營業稅,但是到今年底以後,這些金融營業稅都不進入特別準備金裡面,所以各界就開始討論這個5%的部分是不是要調整,因為在103年為了財政健全方案的時候說這個3%部分解繳國庫。
gazette.blocks[7][1] 我想這個部分,我們跟金管會也都一直密切地做一些討論,因為稅額、稅制的部分,第一個,我們會蒐集國際間對於金融業的相關稅收,不管是營業稅或其他的稅整個加起來,目前它的稅目是怎麼樣,將各個金融業的稅賦負擔跟我們的金融營業稅做一個比較,我們應該要讓我們的金融業有國際的競爭力。
gazette.blocks[8][0] 賴委員士葆:你的方向跟我們講一下吧!因為我問了黃天牧,黃天牧說問你,現在我問你,你又不知道在講一些什麼東西,我都不知道,到底是什麼?
gazette.blocks[9][0] 莊部長翠雲:沒有,我想這個部分……
gazette.blocks[10][0] 賴委員士葆:黃天牧就說問你,但你講一堆我都聽不懂。
gazette.blocks[11][0] 莊部長翠雲:這部分我們必須還要再跟金管會做詳細的研議……
gazette.blocks[12][0] 賴委員士葆:你又要找他?
gazette.blocks[13][0] 莊部長翠雲:因為今年底……
gazette.blocks[14][0] 賴委員士葆:他說你決定,但你又要找他,怎麼會變成這樣?
gazette.blocks[15][0] 莊部長翠雲:不會啦!我們兩個都互相地在密切討論,我們兩部都在……
gazette.blocks[16][0] 賴委員士葆:外面有兩種聲音啦!第一個聲音說大家營業稅都5%啊!為什麼金融業要特別去給它降?可是金融業就表示,全世界金融業的營業稅沒有這麼高,因為它沒有進項可以扣,那個5%是因為有進項可以扣,因為它沒有進項,所以不應該這麼高。對於這兩個聲音,你覺得怎麼樣?
gazette.blocks[17][0] 莊部長翠雲:跟委員報告,我們會跟國際間的稅賦來做一個比較……
gazette.blocks[18][0] 賴委員士葆:什麼時候會有答案?
gazette.blocks[19][0] 莊部長翠雲:會有答案啦!我們會跟金管會持續地努力。
gazette.blocks[20][0] 賴委員士葆:還是因為你現在是看守內閣,你不要做決定了,就拖給下一任部長?
gazette.blocks[21][0] 莊部長翠雲:沒有,我們一直都在做相關資料的蒐集跟討論。
gazette.blocks[22][0] 賴委員士葆:520之前可以出來嗎?
gazette.blocks[23][0] 莊部長翠雲:我沒有辦法做這樣的一個確定。
gazette.blocks[24][0] 賴委員士葆:討論也不要那麼久啦!這是很大的事情耶!
gazette.blocks[25][0] 莊部長翠雲:是。
gazette.blocks[26][0] 賴委員士葆:這是很大的事情耶!
gazette.blocks[27][0] 莊部長翠雲:對,但是因為時間一直到12月底嘛!
gazette.blocks[28][0] 賴委員士葆:我們看到美國眾議院在1月底通過了臺灣租稅協定,就是讓臺美關係往上升,臺美可以互相的免重複課稅,這個事情你掌握的怎麼樣?眾議院通過,參議院還要通過,再送總統簽署。
gazette.blocks[29][0] 莊部長翠雲:我們跟駐美代表處以及外交部一直持續密切關注,這個部分就如同委員簡報上的資料,1月31號美國眾議院已經通過了,還要經過參議院的通過,參議院通過以後要經過總統簽署,之後我們跟美國還要做一個國際文書的交換,我們要承諾我們提供互惠平等的租稅減免,這樣就可以生效。因為參議院還在做研議、審議當中,所以並沒有確定的時間,我們當然會密切地關注,我們的駐美代表處也持續努力在溝通。
gazette.blocks[30][0] 賴委員士葆:這個事情既然眾議院通過了,而且老實講,這也是美國對外、對臺灣的一個承諾,我的猜測,在他們的總統大選今年11月之前應該可以搞定,你同意嗎?你同意這種猜測嗎?
gazette.blocks[31][0] 莊部長翠雲:我們希望,我們也非常希望這樣。
gazette.blocks[32][0] 賴委員士葆:非常希望這個事情?
gazette.blocks[33][0] 莊部長翠雲:對。
gazette.blocks[34][0] 賴委員士葆:這個審議老實講也沒有什麼太了不起,因為它是放在其他的案子裡面,它並不是寫你是眾議院這樣子,可是參議院出來的,不是!是勞工法案裡面的租稅減免之類的,放在那個……
gazette.blocks[35][0] 莊部長翠雲:對,勞工家庭員工的租稅減免。
gazette.blocks[36][0] 賴委員士葆:對,放在那個案子裡面,裡面才談到這一段,有談一小段,對吧?
gazette.blocks[37][0] 莊部長翠雲:對,是其中的項目啦!
gazette.blocks[38][0] 賴委員士葆:對。
gazette.blocks[39][0] 莊部長翠雲:但是目前……
gazette.blocks[40][0] 賴委員士葆:它並不是有一個法案是這個法,不是的,是美國有一個法案,但是會牽涉到有關於臺灣租稅相關的免重複課稅,所以放在裡面。
gazette.blocks[41][0] 莊部長翠雲:對,它有兩個,一個就是……
gazette.blocks[42][0] 賴委員士葆:它是一個專章。
gazette.blocks[43][0] 莊部長翠雲:一個專章,是修國內稅法的部分……
gazette.blocks[44][0] 賴委員士葆:對,他們的國內稅法裡面有個專章。
gazette.blocks[45][0] 莊部長翠雲:另外還有一個授權法的法。
gazette.blocks[46][0] 賴委員士葆:對。
gazette.blocks[47][0] 莊部長翠雲:大概是這樣,所以我們會持續地關注,也會跟駐美代表處跟美國財政部……
gazette.blocks[48][0] 賴委員士葆:再push一下嘛!我想他們選舉……
gazette.blocks[49][0] 莊部長翠雲:當然、當然。
gazette.blocks[50][0] 賴委員士葆:選舉也需要華人的票嘛!
gazette.blocks[51][0] 莊部長翠雲:是。
gazette.blocks[52][0] 賴委員士葆:這個東西老實講是蠻重要的。
gazette.blocks[53][0] 莊部長翠雲:是的。
gazette.blocks[54][0] 賴委員士葆:我們再看外面所關心的,根據關務署所查的資料,現在最夯的食安題目叫蘇丹紅,結果我一看嚇一跳,沒有看都不知道,看了嚇一跳,111年、112年,你看,蘇丹紅1號到4號總共數量多少?160公克,一點點啦!怎麼這麼少?我再查另外一個資料才看到,番椒屬就等於是辣椒粉、辣椒粒,這個就不一樣囉!三千多公噸喔!等於300萬公斤啦!因為1公噸等於1,000公斤,然後現在看到高雄地檢署在查,哇!不得了,查兩家公司,只有查到3萬,這是多少?這是301萬公斤啊!它只有查3萬公斤而已。我現在問你這個,你們資料都有,海關來的話,從海關、大盤商、小盤商到食品業者,每一個階段都有發票,對吧?部長,是不是?
gazette.blocks[55][0] 莊部長翠雲:如果正常應該有發票,這部分……
gazette.blocks[56][0] 賴委員士葆:都有發票啊!
gazette.blocks[57][0] 莊部長翠雲:我是不是請我們關務署或者是賦稅署回答一下?
gazette.blocks[58][0] 賴委員士葆:賦稅署來回答一下,都有發票,對不對?
gazette.blocks[59][0] 宋署長秀玲:報告委員,如果它進口有去申報我們講的營業稅、關稅,就會有發票。
gazette.blocks[60][0] 賴委員士葆:它進口進來絕對是有申報啊!然後它領出來給大盤商絕對有發票啊!
gazette.blocks[61][0] 宋署長秀玲:它如果……
gazette.blocks[62][0] 賴委員士葆:大盤給小盤也有發票啊!小盤給這些食品業者也是有發票啊!
gazette.blocks[63][0] 宋署長秀玲:如果它每一環都沒有斷鏈,就是每一環都有開立發票,確實在我們的發票資料上會有。
gazette.blocks[64][0] 賴委員士葆:對啊!以現在來講的話,我覺得現在的衛福部還有所謂的食安幾環有這個迷思,其實我們財政部可以提供很大的幫助,給它發票、給衛福部相關的發票資料、給我們地方政府的衛生局發票資料,他們幫忙勾稽,很快就抓到了,否則現在人心惶惶啊!大家想說之前好像有去吃八方雲集或其他什麼的,裡面有辣油,一次吃一包,不知道吃進肚會怎麼樣?而且還要保留發票,消費者要保留發票,到時候求償要用的啦!你要補充嗎?
gazette.blocks[65][0] 莊部長翠雲:委員,我想這個部分……
gazette.blocks[66][0] 賴委員士葆:我就問你……
gazette.blocks[67][0] 莊部長翠雲:食安溯源很重要,所以發票資料我們可以提供給衛福部去做……
gazette.blocks[68][0] 賴委員士葆:可以吧!請你主動提供給衛福部、主動提供給各縣市政府,告訴他們這個可以幫助勾稽,去抓到還有哪一些有蘇丹紅,可以嗎?
gazette.blocks[69][0] 莊部長翠雲:可以,我們可以提供發票,請他們去溯源。
gazette.blocks[70][0] 賴委員士葆:馬上做、馬上做喔!
gazette.blocks[71][0] 莊部長翠雲:好。
gazette.blocks[72][0] 賴委員士葆:回去就做了,這個絕對是有幫助的。
gazette.blocks[73][0] 莊部長翠雲:是。
gazette.blocks[74][0] 賴委員士葆:要不然的話,現在檢察官查了半天就只查了3萬,現在有301萬公斤耶!你要想這樣耶!不要只有去看蘇丹紅,蘇丹紅只有一點點而已啦!
gazette.blocks[75][0] 莊部長翠雲:品名的部分我們跟衛福部再討論。
gazette.blocks[76][0] 賴委員士葆:好。過去大家也關心的,有很多國家隊啦!我就舉三個,雞蛋國家隊,補助了34億;綠能國家隊,補助了256億;電動大客車國家隊,補助了600億。請問這些帶給國家多少的營所稅?
gazette.blocks[77][0] 莊部長翠雲:沒有做這方面的統計。
gazette.blocks[78][0] 賴委員士葆:你統計一下可以嗎?回去統計國家隊。
gazette.blocks[79][0] 莊部長翠雲:我們要去瞭解一下……
gazette.blocks[80][0] 賴委員士葆:對啊!這也不用補助,除了疫情期間,他沒有免稅,還是有繳稅的喔!要繳稅。
gazette.blocks[81][0] 莊部長翠雲:我們去瞭解一下這個行業別是什麼,來瞭解一下,可以嗎?
gazette.blocks[82][0] 賴委員士葆:去瞭解。
gazette.blocks[83][0] 莊部長翠雲:好。
gazette.blocks[84][0] 賴委員士葆:其實你們財政部都有資料,沒有那個的話就按照書面,你們抓他的獲利是8%,營所稅20%,所以就是1.6%,Google一下都有這樣的資料,我就告訴你,是可以這樣陳報,就是1.6%。
gazette.blocks[85][0] 莊部長翠雲:好。
gazette.blocks[86][0] 賴委員士葆:部長,剛剛那個資料2個禮拜內給我,可以嗎?
gazette.blocks[87][0] 莊部長翠雲:是,我們……
gazette.blocks[88][0] 賴委員士葆:1個月好了。
gazette.blocks[89][0] 莊部長翠雲:第一個,我們要先確認那個資料要有用,就是什麼把它挑出來……
gazette.blocks[90][0] 賴委員士葆:好,最後一點也是很重要的,今天八大行庫都在這裡,軍公教加10%,一銀和臺企銀、合庫、華銀都是4%,彰銀沒有4%,他用獎金的方式給付。彰銀董事長在不在,能不能來一下?兆豐平均有4.5%,比average高,都是4%,臺銀跟土銀是因為另外的制度,那就不在這裡面。彰銀就不調底薪,我就請問部長要不要責成彰銀,真的這些勞工、員工都很辛苦,大家打拚了,你就不要用什麼獎金方式,那個另外算,但是你調薪就調底薪,可不可以?
gazette.blocks[91][0] 莊部長翠雲:這個是不是我們讓董事長說明一下?
gazette.blocks[92][0] 賴委員士葆:董事長說明一下,可不可以?
gazette.blocks[93][0] 凌董事長忠嫄:報告委員,其實我們每一年都有調薪了,因為我們薪資的制度跟其他行庫的標準不太一樣,其他的行庫他們都是用職級的方式,每年就會自動跳薪,但是我們是整體性調薪。另外我們也希望透過獎金的方式,對於同仁的獎勵……
gazette.blocks[94][0] 賴委員士葆:那個獎金,公會在意的很簡單,大家都很清楚,沒有放底薪會影響到他的退休金,就是這樣而已,差在這裡啦!所以你回去研究一下,好不好?
gazette.blocks[95][0] 凌董事長忠嫄:好。
gazette.blocks[96][0] 賴委員士葆:其實不僅僅只有彰銀,所有行庫的勞工都有這樣的心聲。今年的話,其他的行庫都調4%,下一次說不定有樣看樣啊!下一次看彰銀這樣子,他也學彰銀,都通通調獎金,那樣感覺不好、感覺不好。好不好?謝謝。
gazette.blocks[97][0] 凌董事長忠嫄:好。
gazette.blocks[98][0] 莊部長翠雲:謝謝委員。
gazette.blocks[99][0] 主席:謝謝賴士葆委員。
gazette.blocks[99][1] 下一位請郭國文委員。
gazette.agenda.page_end 378
gazette.agenda.meet_id 委員會-11-1-20-2
gazette.agenda.speakers[0] 郭國文
gazette.agenda.speakers[1] 林德福
gazette.agenda.speakers[2] 吳秉叡
gazette.agenda.speakers[3] 賴士葆
gazette.agenda.speakers[4] 李彥秀
gazette.agenda.speakers[5] 王世堅
gazette.agenda.speakers[6] 王鴻薇
gazette.agenda.speakers[7] 賴惠員
gazette.agenda.speakers[8] 顏寬恒
gazette.agenda.speakers[9] 黃珊珊
gazette.agenda.speakers[10] 李坤城
gazette.agenda.speakers[11] 伍麗華Saidhai‧Tahovecahe
gazette.agenda.speakers[12] 謝衣鳯
gazette.agenda.speakers[13] 黃國昌
gazette.agenda.speakers[14] 鄭天財Sra Kacaw
gazette.agenda.speakers[15] 羅廷瑋
gazette.agenda.speakers[16] 陳培瑜
gazette.agenda.speakers[17] 羅明才
gazette.agenda.speakers[18] 陳玉珍
gazette.agenda.page_start 323
gazette.agenda.meetingDate[0] 2024-03-07
gazette.agenda.gazette_id 1130701
gazette.agenda.agenda_lcidc_ids[0] 1130701_00007
gazette.agenda.meet_name 立法院第11屆第1會期財政委員會第2次全體委員會議紀錄
gazette.agenda.content 邀請財政部莊部長翠雲率所屬機關首長暨國營事業董事長、總經理(含各轉投資事業機構公股代 表之董、監事)列席業務報告,並備質詢
gazette.agenda.agenda_id 1130701_00006
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 0.94221875
transcript.pyannote[1].speaker SPEAKER_03
transcript.pyannote[1].start 1.92096875
transcript.pyannote[1].end 2.03909375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 2.03909375
transcript.pyannote[2].end 2.54534375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 6.40971875
transcript.pyannote[3].end 6.94971875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 7.64159375
transcript.pyannote[4].end 8.23221875
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 10.03784375
transcript.pyannote[5].end 11.35409375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 11.79284375
transcript.pyannote[6].end 12.33284375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 16.01159375
transcript.pyannote[7].end 17.42909375
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 18.40784375
transcript.pyannote[8].end 19.13346875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 19.57221875
transcript.pyannote[9].end 20.24721875
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 20.53409375
transcript.pyannote[10].end 21.64784375
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 55.61721875
transcript.pyannote[11].end 56.02221875
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 56.96721875
transcript.pyannote[12].end 58.01346875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 58.51971875
transcript.pyannote[13].end 58.60409375
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 59.97096875
transcript.pyannote[14].end 60.40971875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 60.67971875
transcript.pyannote[15].end 61.32096875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 65.87721875
transcript.pyannote[16].end 66.21471875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 82.53284375
transcript.pyannote[17].end 83.17409375
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 83.84909375
transcript.pyannote[18].end 84.60846875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 84.97971875
transcript.pyannote[19].end 88.27034375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 88.38846875
transcript.pyannote[20].end 89.97471875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 91.52721875
transcript.pyannote[21].end 92.11784375
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 92.55659375
transcript.pyannote[22].end 94.15971875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 94.80096875
transcript.pyannote[23].end 95.61096875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 96.57284375
transcript.pyannote[24].end 99.37409375
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 100.20096875
transcript.pyannote[25].end 102.81659375
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 103.08659375
transcript.pyannote[26].end 105.29721875
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 106.17471875
transcript.pyannote[27].end 110.84909375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 111.16971875
transcript.pyannote[28].end 112.70534375
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 113.68409375
transcript.pyannote[29].end 113.97096875
transcript.pyannote[30].speaker SPEAKER_04
transcript.pyannote[30].start 113.97096875
transcript.pyannote[30].end 114.30846875
transcript.pyannote[31].speaker SPEAKER_04
transcript.pyannote[31].start 114.83159375
transcript.pyannote[31].end 116.13096875
transcript.pyannote[32].speaker SPEAKER_04
transcript.pyannote[32].start 116.38409375
transcript.pyannote[32].end 116.90721875
transcript.pyannote[33].speaker SPEAKER_04
transcript.pyannote[33].start 116.97471875
transcript.pyannote[33].end 117.04221875
transcript.pyannote[34].speaker SPEAKER_04
transcript.pyannote[34].start 117.07596875
transcript.pyannote[34].end 177.31971875
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 175.37909375
transcript.pyannote[35].end 176.02034375
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 177.31971875
transcript.pyannote[36].end 177.52221875
transcript.pyannote[37].speaker SPEAKER_04
transcript.pyannote[37].start 177.52221875
transcript.pyannote[37].end 178.02846875
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 178.02846875
transcript.pyannote[38].end 189.01409375
transcript.pyannote[39].speaker SPEAKER_04
transcript.pyannote[39].start 189.14909375
transcript.pyannote[39].end 189.43596875
transcript.pyannote[40].speaker SPEAKER_04
transcript.pyannote[40].start 189.92534375
transcript.pyannote[40].end 195.34221875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 192.77721875
transcript.pyannote[41].end 196.67534375
transcript.pyannote[42].speaker SPEAKER_04
transcript.pyannote[42].start 197.33346875
transcript.pyannote[42].end 202.86846875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 201.50159375
transcript.pyannote[43].end 203.25659375
transcript.pyannote[44].speaker SPEAKER_04
transcript.pyannote[44].start 203.17221875
transcript.pyannote[44].end 203.18909375
transcript.pyannote[45].speaker SPEAKER_04
transcript.pyannote[45].start 203.20596875
transcript.pyannote[45].end 204.89346875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 203.74596875
transcript.pyannote[46].end 206.02409375
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 206.05784375
transcript.pyannote[47].end 207.13784375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 207.47534375
transcript.pyannote[48].end 207.74534375
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 208.11659375
transcript.pyannote[49].end 209.75346875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 210.10784375
transcript.pyannote[50].end 212.58846875
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 213.22971875
transcript.pyannote[51].end 214.54596875
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 215.40659375
transcript.pyannote[52].end 217.83659375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 218.27534375
transcript.pyannote[53].end 218.93346875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 219.11909375
transcript.pyannote[54].end 219.92909375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 220.33409375
transcript.pyannote[55].end 221.93721875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 222.37596875
transcript.pyannote[56].end 222.54471875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 222.54471875
transcript.pyannote[57].end 226.39221875
transcript.pyannote[58].speaker SPEAKER_04
transcript.pyannote[58].start 226.39221875
transcript.pyannote[58].end 226.45971875
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 226.57784375
transcript.pyannote[59].end 226.61159375
transcript.pyannote[60].speaker SPEAKER_04
transcript.pyannote[60].start 226.61159375
transcript.pyannote[60].end 226.72971875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 226.72971875
transcript.pyannote[61].end 226.78034375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 226.78034375
transcript.pyannote[62].end 226.81409375
transcript.pyannote[63].speaker SPEAKER_04
transcript.pyannote[63].start 226.81409375
transcript.pyannote[63].end 229.85159375
transcript.pyannote[64].speaker SPEAKER_04
transcript.pyannote[64].start 230.00346875
transcript.pyannote[64].end 236.87159375
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 235.08284375
transcript.pyannote[65].end 235.84221875
transcript.pyannote[66].speaker SPEAKER_04
transcript.pyannote[66].start 237.25971875
transcript.pyannote[66].end 241.90034375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 241.14096875
transcript.pyannote[67].end 245.79846875
transcript.pyannote[68].speaker SPEAKER_04
transcript.pyannote[68].start 245.79846875
transcript.pyannote[68].end 250.27034375
transcript.pyannote[69].speaker SPEAKER_04
transcript.pyannote[69].start 250.92846875
transcript.pyannote[69].end 251.40096875
transcript.pyannote[70].speaker SPEAKER_04
transcript.pyannote[70].start 251.63721875
transcript.pyannote[70].end 253.07159375
transcript.pyannote[71].speaker SPEAKER_04
transcript.pyannote[71].start 253.44284375
transcript.pyannote[71].end 256.93596875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 256.93596875
transcript.pyannote[72].end 257.77971875
transcript.pyannote[73].speaker SPEAKER_04
transcript.pyannote[73].start 257.45909375
transcript.pyannote[73].end 257.61096875
transcript.pyannote[74].speaker SPEAKER_04
transcript.pyannote[74].start 257.77971875
transcript.pyannote[74].end 258.03284375
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 258.03284375
transcript.pyannote[75].end 258.13409375
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 258.31971875
transcript.pyannote[76].end 258.37034375
transcript.pyannote[77].speaker SPEAKER_04
transcript.pyannote[77].start 258.37034375
transcript.pyannote[77].end 259.53471875
transcript.pyannote[78].speaker SPEAKER_04
transcript.pyannote[78].start 260.19284375
transcript.pyannote[78].end 264.71534375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 265.12034375
transcript.pyannote[79].end 265.35659375
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 266.95971875
transcript.pyannote[80].end 267.70221875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 268.30971875
transcript.pyannote[81].end 270.50346875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 270.89159375
transcript.pyannote[82].end 273.22034375
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 273.92909375
transcript.pyannote[83].end 274.65471875
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 275.70096875
transcript.pyannote[84].end 277.11846875
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 277.55721875
transcript.pyannote[85].end 278.01284375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 278.33346875
transcript.pyannote[86].end 279.21096875
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 279.78471875
transcript.pyannote[87].end 281.45534375
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 281.75909375
transcript.pyannote[88].end 282.58596875
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 283.21034375
transcript.pyannote[89].end 284.57721875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 284.77971875
transcript.pyannote[90].end 285.40409375
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 285.72471875
transcript.pyannote[91].end 286.50096875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 287.22659375
transcript.pyannote[92].end 288.28971875
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 288.50909375
transcript.pyannote[93].end 289.90971875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 290.11221875
transcript.pyannote[94].end 292.33971875
transcript.pyannote[95].speaker SPEAKER_04
transcript.pyannote[95].start 292.33971875
transcript.pyannote[95].end 292.50846875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 292.50846875
transcript.pyannote[96].end 292.96409375
transcript.pyannote[97].speaker SPEAKER_04
transcript.pyannote[97].start 292.96409375
transcript.pyannote[97].end 293.55471875
transcript.pyannote[98].speaker SPEAKER_04
transcript.pyannote[98].start 293.95971875
transcript.pyannote[98].end 329.83596875
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 327.62534375
transcript.pyannote[99].end 329.14409375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 330.39284375
transcript.pyannote[100].end 336.24846875
transcript.pyannote[101].speaker SPEAKER_04
transcript.pyannote[101].start 330.74721875
transcript.pyannote[101].end 331.27034375
transcript.pyannote[102].speaker SPEAKER_04
transcript.pyannote[102].start 331.91159375
transcript.pyannote[102].end 332.65409375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 337.36221875
transcript.pyannote[103].end 338.45909375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 339.23534375
transcript.pyannote[104].end 341.76659375
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 342.40784375
transcript.pyannote[105].end 343.26846875
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 344.06159375
transcript.pyannote[106].end 345.34409375
transcript.pyannote[107].speaker SPEAKER_04
transcript.pyannote[107].start 345.14159375
transcript.pyannote[107].end 345.32721875
transcript.pyannote[108].speaker SPEAKER_04
transcript.pyannote[108].start 345.34409375
transcript.pyannote[108].end 349.12409375
transcript.pyannote[109].speaker SPEAKER_04
transcript.pyannote[109].start 349.36034375
transcript.pyannote[109].end 349.98471875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 349.98471875
transcript.pyannote[110].end 351.62159375
transcript.pyannote[111].speaker SPEAKER_04
transcript.pyannote[111].start 350.17034375
transcript.pyannote[111].end 350.55846875
transcript.pyannote[112].speaker SPEAKER_04
transcript.pyannote[112].start 350.86221875
transcript.pyannote[112].end 351.60471875
transcript.pyannote[113].speaker SPEAKER_04
transcript.pyannote[113].start 351.62159375
transcript.pyannote[113].end 352.34721875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 351.73971875
transcript.pyannote[114].end 352.22909375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 352.34721875
transcript.pyannote[115].end 352.36409375
transcript.pyannote[116].speaker SPEAKER_04
transcript.pyannote[116].start 352.36409375
transcript.pyannote[116].end 352.38096875
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 352.38096875
transcript.pyannote[117].end 352.44846875
transcript.pyannote[118].speaker SPEAKER_04
transcript.pyannote[118].start 352.63409375
transcript.pyannote[118].end 352.70159375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 352.70159375
transcript.pyannote[119].end 352.71846875
transcript.pyannote[120].speaker SPEAKER_04
transcript.pyannote[120].start 352.71846875
transcript.pyannote[120].end 353.07284375
transcript.pyannote[121].speaker SPEAKER_02
transcript.pyannote[121].start 353.07284375
transcript.pyannote[121].end 353.10659375
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 353.46096875
transcript.pyannote[122].end 353.79846875
transcript.pyannote[123].speaker SPEAKER_02
transcript.pyannote[123].start 354.10221875
transcript.pyannote[123].end 369.76221875
transcript.pyannote[124].speaker SPEAKER_04
transcript.pyannote[124].start 366.79221875
transcript.pyannote[124].end 379.38096875
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 370.15034375
transcript.pyannote[125].end 371.58471875
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 377.94659375
transcript.pyannote[126].end 378.28409375
transcript.pyannote[127].speaker SPEAKER_04
transcript.pyannote[127].start 379.44846875
transcript.pyannote[127].end 380.02221875
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 379.58346875
transcript.pyannote[128].end 387.88596875
transcript.pyannote[129].speaker SPEAKER_04
transcript.pyannote[129].start 380.12346875
transcript.pyannote[129].end 380.14034375
transcript.pyannote[130].speaker SPEAKER_04
transcript.pyannote[130].start 380.30909375
transcript.pyannote[130].end 380.39346875
transcript.pyannote[131].speaker SPEAKER_04
transcript.pyannote[131].start 380.41034375
transcript.pyannote[131].end 380.46096875
transcript.pyannote[132].speaker SPEAKER_04
transcript.pyannote[132].start 380.66346875
transcript.pyannote[132].end 380.71409375
transcript.pyannote[133].speaker SPEAKER_04
transcript.pyannote[133].start 380.79846875
transcript.pyannote[133].end 380.81534375
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 387.91971875
transcript.pyannote[134].end 388.40909375
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 388.94909375
transcript.pyannote[135].end 390.68721875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 390.92346875
transcript.pyannote[136].end 391.34534375
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 391.75034375
transcript.pyannote[137].end 394.46721875
transcript.pyannote[138].speaker SPEAKER_04
transcript.pyannote[138].start 393.38721875
transcript.pyannote[138].end 403.78221875
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 395.24346875
transcript.pyannote[139].end 396.17159375
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 399.37784375
transcript.pyannote[140].end 399.96846875
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 399.98534375
transcript.pyannote[141].end 400.42409375
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 401.58846875
transcript.pyannote[142].end 401.97659375
transcript.pyannote[143].speaker SPEAKER_04
transcript.pyannote[143].start 404.23784375
transcript.pyannote[143].end 416.38784375
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 404.37284375
transcript.pyannote[144].end 404.71034375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 408.37221875
transcript.pyannote[145].end 416.11784375
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 416.37096875
transcript.pyannote[146].end 417.78846875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 418.49721875
transcript.pyannote[147].end 420.40409375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 421.07909375
transcript.pyannote[148].end 423.10409375
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 423.44159375
transcript.pyannote[149].end 424.94346875
transcript.pyannote[150].speaker SPEAKER_02
transcript.pyannote[150].start 425.36534375
transcript.pyannote[150].end 427.33971875
transcript.pyannote[151].speaker SPEAKER_03
transcript.pyannote[151].start 427.72784375
transcript.pyannote[151].end 428.06534375
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 428.47034375
transcript.pyannote[152].end 430.25909375
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 431.22096875
transcript.pyannote[153].end 433.49909375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 435.77721875
transcript.pyannote[154].end 437.61659375
transcript.pyannote[155].speaker SPEAKER_02
transcript.pyannote[155].start 438.08909375
transcript.pyannote[155].end 442.42596875
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 442.59471875
transcript.pyannote[156].end 443.87721875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 444.18096875
transcript.pyannote[157].end 444.90659375
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 445.31159375
transcript.pyannote[158].end 446.45909375
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 447.60659375
transcript.pyannote[159].end 449.74971875
transcript.pyannote[160].speaker SPEAKER_02
transcript.pyannote[160].start 450.15471875
transcript.pyannote[160].end 450.54284375
transcript.pyannote[161].speaker SPEAKER_02
transcript.pyannote[161].start 451.30221875
transcript.pyannote[161].end 453.58034375
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 453.95159375
transcript.pyannote[162].end 456.11159375
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 456.33096875
transcript.pyannote[163].end 461.15721875
transcript.pyannote[164].speaker SPEAKER_02
transcript.pyannote[164].start 461.52846875
transcript.pyannote[164].end 462.55784375
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 463.50284375
transcript.pyannote[165].end 464.85284375
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 465.46034375
transcript.pyannote[166].end 467.33346875
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 467.83971875
transcript.pyannote[167].end 468.22784375
transcript.pyannote[168].speaker SPEAKER_02
transcript.pyannote[168].start 468.51471875
transcript.pyannote[168].end 471.28221875
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 471.48471875
transcript.pyannote[169].end 474.62346875
transcript.pyannote[170].speaker SPEAKER_02
transcript.pyannote[170].start 474.87659375
transcript.pyannote[170].end 478.96034375
transcript.pyannote[171].speaker SPEAKER_02
transcript.pyannote[171].start 479.46659375
transcript.pyannote[171].end 480.19221875
transcript.pyannote[172].speaker SPEAKER_02
transcript.pyannote[172].start 480.64784375
transcript.pyannote[172].end 482.36909375
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 482.62221875
transcript.pyannote[173].end 484.73159375
transcript.pyannote[174].speaker SPEAKER_02
transcript.pyannote[174].start 485.40659375
transcript.pyannote[174].end 490.87409375
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 491.59971875
transcript.pyannote[175].end 493.74284375
transcript.pyannote[176].speaker SPEAKER_04
transcript.pyannote[176].start 493.74284375
transcript.pyannote[176].end 493.75971875
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 494.40096875
transcript.pyannote[177].end 494.75534375
transcript.pyannote[178].speaker SPEAKER_04
transcript.pyannote[178].start 494.75534375
transcript.pyannote[178].end 494.78909375
transcript.pyannote[179].speaker SPEAKER_02
transcript.pyannote[179].start 495.54846875
transcript.pyannote[179].end 495.76784375
transcript.pyannote[180].speaker SPEAKER_04
transcript.pyannote[180].start 495.76784375
transcript.pyannote[180].end 495.91971875
transcript.pyannote[181].speaker SPEAKER_02
transcript.pyannote[181].start 495.91971875
transcript.pyannote[181].end 495.97034375
transcript.pyannote[182].speaker SPEAKER_04
transcript.pyannote[182].start 495.97034375
transcript.pyannote[182].end 496.78034375
transcript.pyannote[183].speaker SPEAKER_04
transcript.pyannote[183].start 497.16846875
transcript.pyannote[183].end 503.54721875
transcript.pyannote[184].speaker SPEAKER_04
transcript.pyannote[184].start 503.96909375
transcript.pyannote[184].end 504.86346875
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 505.79159375
transcript.pyannote[185].end 512.94659375
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 512.94659375
transcript.pyannote[186].end 518.73471875
transcript.pyannote[187].speaker SPEAKER_02
transcript.pyannote[187].start 519.57846875
transcript.pyannote[187].end 528.92721875
transcript.pyannote[188].speaker SPEAKER_01
transcript.pyannote[188].start 528.08346875
transcript.pyannote[188].end 528.58971875
transcript.pyannote[189].speaker SPEAKER_01
transcript.pyannote[189].start 528.75846875
transcript.pyannote[189].end 528.80909375
transcript.pyannote[190].speaker SPEAKER_01
transcript.pyannote[190].start 528.92721875
transcript.pyannote[190].end 529.01159375
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 529.21409375
transcript.pyannote[191].end 537.14534375
transcript.pyannote[192].speaker SPEAKER_02
transcript.pyannote[192].start 533.16284375
transcript.pyannote[192].end 533.58471875
transcript.pyannote[193].speaker SPEAKER_02
transcript.pyannote[193].start 535.32284375
transcript.pyannote[193].end 536.72346875
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 537.31409375
transcript.pyannote[194].end 545.31284375
transcript.pyannote[195].speaker SPEAKER_02
transcript.pyannote[195].start 545.66721875
transcript.pyannote[195].end 546.64596875
transcript.pyannote[196].speaker SPEAKER_02
transcript.pyannote[196].start 547.06784375
transcript.pyannote[196].end 549.68346875
transcript.pyannote[197].speaker SPEAKER_02
transcript.pyannote[197].start 549.90284375
transcript.pyannote[197].end 554.27346875
transcript.pyannote[198].speaker SPEAKER_02
transcript.pyannote[198].start 555.20159375
transcript.pyannote[198].end 557.63159375
transcript.pyannote[199].speaker SPEAKER_02
transcript.pyannote[199].start 558.07034375
transcript.pyannote[199].end 559.69034375
transcript.pyannote[200].speaker SPEAKER_02
transcript.pyannote[200].start 560.34846875
transcript.pyannote[200].end 568.58346875
transcript.pyannote[201].speaker SPEAKER_02
transcript.pyannote[201].start 569.37659375
transcript.pyannote[201].end 572.43096875
transcript.pyannote[202].speaker SPEAKER_04
transcript.pyannote[202].start 572.43096875
transcript.pyannote[202].end 572.48159375
transcript.pyannote[203].speaker SPEAKER_04
transcript.pyannote[203].start 572.65034375
transcript.pyannote[203].end 572.68409375
transcript.pyannote[204].speaker SPEAKER_02
transcript.pyannote[204].start 572.68409375
transcript.pyannote[204].end 573.76409375
transcript.pyannote[205].speaker SPEAKER_04
transcript.pyannote[205].start 573.76409375
transcript.pyannote[205].end 573.79784375
transcript.pyannote[206].speaker SPEAKER_04
transcript.pyannote[206].start 574.47284375
transcript.pyannote[206].end 574.55721875
transcript.pyannote[207].speaker SPEAKER_02
transcript.pyannote[207].start 574.55721875
transcript.pyannote[207].end 574.59096875
transcript.pyannote[208].speaker SPEAKER_04
transcript.pyannote[208].start 574.59096875
transcript.pyannote[208].end 583.90596875
transcript.pyannote[209].speaker SPEAKER_02
transcript.pyannote[209].start 577.17284375
transcript.pyannote[209].end 577.96596875
transcript.pyannote[210].speaker SPEAKER_00
transcript.pyannote[210].start 577.96596875
transcript.pyannote[210].end 578.86034375
transcript.pyannote[211].speaker SPEAKER_02
transcript.pyannote[211].start 582.62346875
transcript.pyannote[211].end 583.72034375
transcript.pyannote[212].speaker SPEAKER_02
transcript.pyannote[212].start 583.90596875
transcript.pyannote[212].end 587.48346875
transcript.pyannote[213].speaker SPEAKER_02
transcript.pyannote[213].start 587.73659375
transcript.pyannote[213].end 588.69846875
transcript.pyannote[214].speaker SPEAKER_02
transcript.pyannote[214].start 588.85034375
transcript.pyannote[214].end 593.76096875
transcript.pyannote[215].speaker SPEAKER_04
transcript.pyannote[215].start 594.04784375
transcript.pyannote[215].end 597.82784375
transcript.pyannote[216].speaker SPEAKER_02
transcript.pyannote[216].start 596.68034375
transcript.pyannote[216].end 598.55346875
transcript.pyannote[217].speaker SPEAKER_02
transcript.pyannote[217].start 598.63784375
transcript.pyannote[217].end 610.14659375
transcript.pyannote[218].speaker SPEAKER_04
transcript.pyannote[218].start 606.09659375
transcript.pyannote[218].end 606.34971875
transcript.pyannote[219].speaker SPEAKER_04
transcript.pyannote[219].start 610.14659375
transcript.pyannote[219].end 610.31534375
transcript.pyannote[220].speaker SPEAKER_02
transcript.pyannote[220].start 610.31534375
transcript.pyannote[220].end 615.93471875
transcript.pyannote[221].speaker SPEAKER_04
transcript.pyannote[221].start 610.33221875
transcript.pyannote[221].end 610.46721875
transcript.pyannote[222].speaker SPEAKER_02
transcript.pyannote[222].start 616.28909375
transcript.pyannote[222].end 616.62659375
transcript.pyannote[223].speaker SPEAKER_04
transcript.pyannote[223].start 616.76159375
transcript.pyannote[223].end 620.10284375
transcript.pyannote[224].speaker SPEAKER_04
transcript.pyannote[224].start 621.89159375
transcript.pyannote[224].end 621.94221875
transcript.pyannote[225].speaker SPEAKER_02
transcript.pyannote[225].start 621.94221875
transcript.pyannote[225].end 621.97596875
transcript.pyannote[226].speaker SPEAKER_04
transcript.pyannote[226].start 621.97596875
transcript.pyannote[226].end 622.02659375
transcript.pyannote[227].speaker SPEAKER_02
transcript.pyannote[227].start 622.02659375
transcript.pyannote[227].end 622.19534375
transcript.pyannote[228].speaker SPEAKER_04
transcript.pyannote[228].start 622.19534375
transcript.pyannote[228].end 623.03909375
transcript.pyannote[229].speaker SPEAKER_02
transcript.pyannote[229].start 623.03909375
transcript.pyannote[229].end 623.30909375
transcript.pyannote[230].speaker SPEAKER_04
transcript.pyannote[230].start 623.79846875
transcript.pyannote[230].end 624.03471875
transcript.pyannote[231].speaker SPEAKER_02
transcript.pyannote[231].start 624.03471875
transcript.pyannote[231].end 625.84034375
transcript.pyannote[232].speaker SPEAKER_02
transcript.pyannote[232].start 626.48159375
transcript.pyannote[232].end 627.02159375
transcript.pyannote[233].speaker SPEAKER_02
transcript.pyannote[233].start 627.89909375
transcript.pyannote[233].end 629.82284375
transcript.pyannote[234].speaker SPEAKER_02
transcript.pyannote[234].start 630.37971875
transcript.pyannote[234].end 633.07971875
transcript.pyannote[235].speaker SPEAKER_02
transcript.pyannote[235].start 633.85596875
transcript.pyannote[235].end 636.45471875
transcript.pyannote[236].speaker SPEAKER_02
transcript.pyannote[236].start 636.64034375
transcript.pyannote[236].end 637.48409375
transcript.pyannote[237].speaker SPEAKER_02
transcript.pyannote[237].start 638.26034375
transcript.pyannote[237].end 640.38659375
transcript.pyannote[238].speaker SPEAKER_02
transcript.pyannote[238].start 640.57221875
transcript.pyannote[238].end 642.02346875
transcript.pyannote[239].speaker SPEAKER_04
transcript.pyannote[239].start 643.49159375
transcript.pyannote[239].end 645.12846875
transcript.pyannote[240].speaker SPEAKER_02
transcript.pyannote[240].start 645.12846875
transcript.pyannote[240].end 645.92159375
transcript.pyannote[241].speaker SPEAKER_04
transcript.pyannote[241].start 645.92159375
transcript.pyannote[241].end 645.93846875
transcript.pyannote[242].speaker SPEAKER_04
transcript.pyannote[242].start 646.44471875
transcript.pyannote[242].end 646.46159375
transcript.pyannote[243].speaker SPEAKER_02
transcript.pyannote[243].start 646.46159375
transcript.pyannote[243].end 646.96784375
transcript.pyannote[244].speaker SPEAKER_04
transcript.pyannote[244].start 646.96784375
transcript.pyannote[244].end 647.03534375
transcript.pyannote[245].speaker SPEAKER_02
transcript.pyannote[245].start 647.03534375
transcript.pyannote[245].end 647.94659375
transcript.pyannote[246].speaker SPEAKER_04
transcript.pyannote[246].start 647.94659375
transcript.pyannote[246].end 647.98034375
transcript.pyannote[247].speaker SPEAKER_04
transcript.pyannote[247].start 648.33471875
transcript.pyannote[247].end 649.04346875
transcript.pyannote[248].speaker SPEAKER_04
transcript.pyannote[248].start 649.36409375
transcript.pyannote[248].end 650.42721875
transcript.pyannote[249].speaker SPEAKER_02
transcript.pyannote[249].start 650.42721875
transcript.pyannote[249].end 650.62971875
transcript.pyannote[250].speaker SPEAKER_04
transcript.pyannote[250].start 650.62971875
transcript.pyannote[250].end 650.68034375
transcript.pyannote[251].speaker SPEAKER_02
transcript.pyannote[251].start 651.01784375
transcript.pyannote[251].end 652.11471875
transcript.pyannote[252].speaker SPEAKER_02
transcript.pyannote[252].start 652.58721875
transcript.pyannote[252].end 656.65409375
transcript.pyannote[253].speaker SPEAKER_04
transcript.pyannote[253].start 655.38846875
transcript.pyannote[253].end 655.70909375
transcript.pyannote[254].speaker SPEAKER_04
transcript.pyannote[254].start 656.95784375
transcript.pyannote[254].end 662.29034375
transcript.pyannote[255].speaker SPEAKER_02
transcript.pyannote[255].start 657.49784375
transcript.pyannote[255].end 657.88596875
transcript.pyannote[256].speaker SPEAKER_04
transcript.pyannote[256].start 662.42534375
transcript.pyannote[256].end 662.91471875
transcript.pyannote[257].speaker SPEAKER_02
transcript.pyannote[257].start 662.91471875
transcript.pyannote[257].end 666.37409375
transcript.pyannote[258].speaker SPEAKER_02
transcript.pyannote[258].start 666.93096875
transcript.pyannote[258].end 667.87596875
transcript.pyannote[259].speaker SPEAKER_02
transcript.pyannote[259].start 668.23034375
transcript.pyannote[259].end 670.06971875
transcript.pyannote[260].speaker SPEAKER_02
transcript.pyannote[260].start 670.35659375
transcript.pyannote[260].end 672.56721875
transcript.pyannote[261].speaker SPEAKER_02
transcript.pyannote[261].start 673.14096875
transcript.pyannote[261].end 675.67221875
transcript.pyannote[262].speaker SPEAKER_02
transcript.pyannote[262].start 676.34721875
transcript.pyannote[262].end 678.70971875
transcript.pyannote[263].speaker SPEAKER_02
transcript.pyannote[263].start 678.92909375
transcript.pyannote[263].end 679.62096875
transcript.pyannote[264].speaker SPEAKER_02
transcript.pyannote[264].start 679.84034375
transcript.pyannote[264].end 680.65034375
transcript.pyannote[265].speaker SPEAKER_02
transcript.pyannote[265].start 681.00471875
transcript.pyannote[265].end 681.91596875
transcript.pyannote[266].speaker SPEAKER_02
transcript.pyannote[266].start 682.47284375
transcript.pyannote[266].end 682.75971875
transcript.pyannote[267].speaker SPEAKER_02
transcript.pyannote[267].start 683.08034375
transcript.pyannote[267].end 684.32909375
transcript.pyannote[268].speaker SPEAKER_02
transcript.pyannote[268].start 685.15596875
transcript.pyannote[268].end 686.52284375
transcript.pyannote[269].speaker SPEAKER_02
transcript.pyannote[269].start 687.46784375
transcript.pyannote[269].end 689.37471875
transcript.pyannote[270].speaker SPEAKER_02
transcript.pyannote[270].start 689.71221875
transcript.pyannote[270].end 690.97784375
transcript.pyannote[271].speaker SPEAKER_02
transcript.pyannote[271].start 691.23096875
transcript.pyannote[271].end 691.46721875
transcript.pyannote[272].speaker SPEAKER_04
transcript.pyannote[272].start 691.46721875
transcript.pyannote[272].end 691.61909375
transcript.pyannote[273].speaker SPEAKER_02
transcript.pyannote[273].start 691.61909375
transcript.pyannote[273].end 691.68659375
transcript.pyannote[274].speaker SPEAKER_04
transcript.pyannote[274].start 691.68659375
transcript.pyannote[274].end 695.98971875
transcript.pyannote[275].speaker SPEAKER_02
transcript.pyannote[275].start 694.99409375
transcript.pyannote[275].end 698.08221875
transcript.pyannote[276].speaker SPEAKER_02
transcript.pyannote[276].start 698.82471875
transcript.pyannote[276].end 699.63471875
transcript.pyannote[277].speaker SPEAKER_02
transcript.pyannote[277].start 700.66409375
transcript.pyannote[277].end 702.72284375
transcript.pyannote[278].speaker SPEAKER_02
transcript.pyannote[278].start 703.75221875
transcript.pyannote[278].end 704.89971875
transcript.pyannote[279].speaker SPEAKER_02
transcript.pyannote[279].start 705.30471875
transcript.pyannote[279].end 705.72659375
transcript.pyannote[280].speaker SPEAKER_02
transcript.pyannote[280].start 706.90784375
transcript.pyannote[280].end 708.20721875
transcript.pyannote[281].speaker SPEAKER_02
transcript.pyannote[281].start 708.52784375
transcript.pyannote[281].end 710.78909375
transcript.pyannote[282].speaker SPEAKER_02
transcript.pyannote[282].start 712.20659375
transcript.pyannote[282].end 713.62409375
transcript.pyannote[283].speaker SPEAKER_02
transcript.pyannote[283].start 714.77159375
transcript.pyannote[283].end 718.33221875
transcript.pyannote[284].speaker SPEAKER_02
transcript.pyannote[284].start 719.10846875
transcript.pyannote[284].end 721.06596875
transcript.pyannote[285].speaker SPEAKER_02
transcript.pyannote[285].start 721.36971875
transcript.pyannote[285].end 723.29346875
transcript.pyannote[286].speaker SPEAKER_02
transcript.pyannote[286].start 723.58034375
transcript.pyannote[286].end 725.01471875
transcript.pyannote[287].speaker SPEAKER_02
transcript.pyannote[287].start 725.25096875
transcript.pyannote[287].end 726.19596875
transcript.pyannote[288].speaker SPEAKER_02
transcript.pyannote[288].start 727.59659375
transcript.pyannote[288].end 731.29221875
transcript.pyannote[289].speaker SPEAKER_02
transcript.pyannote[289].start 732.03471875
transcript.pyannote[289].end 732.96284375
transcript.pyannote[290].speaker SPEAKER_02
transcript.pyannote[290].start 733.95846875
transcript.pyannote[290].end 738.59909375
transcript.pyannote[291].speaker SPEAKER_02
transcript.pyannote[291].start 739.12221875
transcript.pyannote[291].end 739.98284375
transcript.pyannote[292].speaker SPEAKER_02
transcript.pyannote[292].start 740.13471875
transcript.pyannote[292].end 741.50159375
transcript.pyannote[293].speaker SPEAKER_02
transcript.pyannote[293].start 741.73784375
transcript.pyannote[293].end 742.73346875
transcript.pyannote[294].speaker SPEAKER_02
transcript.pyannote[294].start 743.15534375
transcript.pyannote[294].end 748.08284375
transcript.pyannote[295].speaker SPEAKER_04
transcript.pyannote[295].start 748.08284375
transcript.pyannote[295].end 748.09971875
transcript.pyannote[296].speaker SPEAKER_04
transcript.pyannote[296].start 748.40346875
transcript.pyannote[296].end 751.72784375
transcript.pyannote[297].speaker SPEAKER_02
transcript.pyannote[297].start 749.44971875
transcript.pyannote[297].end 749.78721875
transcript.pyannote[298].speaker SPEAKER_02
transcript.pyannote[298].start 750.88409375
transcript.pyannote[298].end 751.03596875
transcript.pyannote[299].speaker SPEAKER_02
transcript.pyannote[299].start 751.72784375
transcript.pyannote[299].end 751.79534375
transcript.pyannote[300].speaker SPEAKER_03
transcript.pyannote[300].start 753.21284375
transcript.pyannote[300].end 767.69159375
transcript.pyannote[301].speaker SPEAKER_03
transcript.pyannote[301].start 767.80971875
transcript.pyannote[301].end 772.21409375
transcript.pyannote[302].speaker SPEAKER_03
transcript.pyannote[302].start 772.93971875
transcript.pyannote[302].end 774.96471875
transcript.pyannote[303].speaker SPEAKER_02
transcript.pyannote[303].start 774.96471875
transcript.pyannote[303].end 775.67346875
transcript.pyannote[304].speaker SPEAKER_03
transcript.pyannote[304].start 776.60159375
transcript.pyannote[304].end 776.61846875
transcript.pyannote[305].speaker SPEAKER_02
transcript.pyannote[305].start 776.61846875
transcript.pyannote[305].end 779.72346875
transcript.pyannote[306].speaker SPEAKER_02
transcript.pyannote[306].start 779.94284375
transcript.pyannote[306].end 781.59659375
transcript.pyannote[307].speaker SPEAKER_02
transcript.pyannote[307].start 782.01846875
transcript.pyannote[307].end 790.15221875
transcript.pyannote[308].speaker SPEAKER_02
transcript.pyannote[308].start 790.92846875
transcript.pyannote[308].end 793.27409375
transcript.pyannote[309].speaker SPEAKER_02
transcript.pyannote[309].start 793.71284375
transcript.pyannote[309].end 801.10409375
transcript.pyannote[310].speaker SPEAKER_02
transcript.pyannote[310].start 801.25596875
transcript.pyannote[310].end 801.86346875
transcript.pyannote[311].speaker SPEAKER_02
transcript.pyannote[311].start 802.20096875
transcript.pyannote[311].end 803.14596875
transcript.pyannote[312].speaker SPEAKER_02
transcript.pyannote[312].start 803.77034375
transcript.pyannote[312].end 805.10346875
transcript.pyannote[313].speaker SPEAKER_04
transcript.pyannote[313].start 805.10346875
transcript.pyannote[313].end 805.12034375
transcript.pyannote[314].speaker SPEAKER_04
transcript.pyannote[314].start 805.20471875
transcript.pyannote[314].end 805.45784375
transcript.pyannote[315].speaker SPEAKER_02
transcript.pyannote[315].start 805.45784375
transcript.pyannote[315].end 805.47471875
transcript.pyannote[316].speaker SPEAKER_04
transcript.pyannote[316].start 805.47471875
transcript.pyannote[316].end 805.49159375
transcript.pyannote[317].speaker SPEAKER_04
transcript.pyannote[317].start 806.80784375
transcript.pyannote[317].end 809.15346875
transcript.pyannote[318].speaker SPEAKER_04
transcript.pyannote[318].start 809.87909375
transcript.pyannote[318].end 812.22471875
transcript.whisperx[0].start 0.269
transcript.whisperx[0].end 12.138
transcript.whisperx[0].text 有請莊部長有請莊部長委員好你早啊我想先請問你啊這個稍微停一下吧這電腦把我問出來來等一下喔等一下我們時間暫停
transcript.whisperx[1].start 57.129
transcript.whisperx[1].end 57.369
transcript.whisperx[1].text 主席
transcript.whisperx[2].start 83.888
transcript.whisperx[2].end 88.111
transcript.whisperx[2].text 財政部的立場是怎麼樣是說要繼續維持這樣子3%營業稅2%放在他的特別的準備金那邊那裡只有兩三千億了
transcript.whisperx[3].start 113.84
transcript.whisperx[3].end 129.571
transcript.whisperx[3].text 為什麼處理?跟委員報告是在營業稅法裡面是規定那個2%的金融營業稅免進入金融營業特別準備金這是這個部分並不是5%要落日那至於銀行業跟保險業經營專屬銀行保險本業的部分
transcript.whisperx[4].start 132.253
transcript.whisperx[4].end 138.638
transcript.whisperx[4].text 他有一個5%那3%是歸國庫2%還是進入金融營業稅但是到今年底以後這些金融營業稅都不進入特別準備金裡面去那所以各界就開始去討論這個5%的部分是不是要調整因為在103年為了財政健全方案的時候說這個3%部分結繳國庫那在討論我想這個部分呢我們跟金管會也都一直在密切的一些討論因為這個稅額稅制的部分第一個我們會收集國際間對於金融
transcript.whisperx[5].start 160.314
transcript.whisperx[5].end 160.815
transcript.whisperx[5].text 您的方向跟我們講一下吧因為
transcript.whisperx[6].start 177.629
transcript.whisperx[6].end 205.16
transcript.whisperx[6].text 我問了黃天牧黃天牧說問你啊你現在我問你你又不知道講一些什麼東西我都不知道到底是什麼黃天牧就說問你啊你就你這講幾句都聽不懂這樣對這部分就是我們必須還要再跟金管會的演繹因為他今年底你決定啊你早要找他你變成這樣不會啦我們兩個都都是互相的在密切的討論我們兩部都在外面有兩種聲音啦外面有兩種聲音啦第一個聲音說
transcript.whisperx[7].start 207.521
transcript.whisperx[7].end 209.182
transcript.whisperx[7].text 什麼時候會有答案啊?什麼時候會有答案?
transcript.whisperx[8].start 237.442
transcript.whisperx[8].end 264.572
transcript.whisperx[8].text 會有答案啦那我想我們會跟金管會持續的努力還是還是因為你現在是看守內閣你不要做決定了就拖給下一任部長沒有我們一直都在相關的資料收集跟討論那520之前可以出來嗎這個我沒有辦法做這樣的一個確定討論的不要那麼久啦討論這是很大的事情欸這是很大的事情欸對但是因為時間一直到12月底嘛
transcript.whisperx[9].start 266.991
transcript.whisperx[9].end 290.415
transcript.whisperx[9].text 我們看到美國眾議院在1月1通過了臺灣租稅的協定就是讓臺美關係往上升了臺美可以互相免重複課稅的事情這個事情你掌握得怎麼樣參議院還要通過、眾議院通過、參議院還要通過再總統簽署
transcript.whisperx[10].start 294.076
transcript.whisperx[10].end 303.481
transcript.whisperx[10].text 是,我們一直持續的密切關注跟駐美代表處以及外交部那這個部分就如同委員的簡報上1月31號美國眾院已經通過了那還要經過參院的通過那參院通過以後要經過總統簽署以後我們跟美國還要做一個國際文書的交換我們要承諾我們提供
transcript.whisperx[11].start 314.286
transcript.whisperx[11].end 317.308
transcript.whisperx[11].text 我猜測啦在他們的總統大選今年11月之前應該可以搞定
transcript.whisperx[12].start 344.116
transcript.whisperx[12].end 368.403
transcript.whisperx[12].text 有同意嗎?你同意董災社嗎?我們希望,我們也非常希望這樣,是。非常希望這個事情?對。因為這個審議老實講也沒有什麼太了不起的,因為它是放在其他的案子裡面,它不是,它並不是寫你是中院這樣子可是參院出來的不是勞工什麼法案裡面租稅的減免什麼之類的,放在那個。
transcript.whisperx[13].start 370.043
transcript.whisperx[13].end 370.403
transcript.whisperx[13].text 主席董事長
transcript.whisperx[14].start 391.778
transcript.whisperx[14].end 392.858
transcript.whisperx[14].text 我們再看這個二月五關性的這個
transcript.whisperx[15].start 421.104
transcript.whisperx[15].end 443.75
transcript.whisperx[15].text 根據我關務署查的資料現在最夯的一個慈安的一個庭屋叫蘇丹宏結果我一看嚇一跳沒有可能不知道一看嚇一跳一百一十一年一百二十二一百一十二年你看蘇丹宏一號到四號總共數量多少一百六十公克一點點這麼少
transcript.whisperx[16].start 447.642
transcript.whisperx[16].end 460.831
transcript.whisperx[16].text 我再查另外一個資料才看到了番薑酥就是等於辣椒粉啦辣椒粒啦這個呢就不一樣喔3000多公噸喔等於300
transcript.whisperx[17].start 463.573
transcript.whisperx[17].end 484.456
transcript.whisperx[17].text 三百萬公斤了因為一公噸等於一千公斤了所以然後現在看到有高雄關的地檢署查哇不得了查兩家公司有三萬結果查到三萬這是多少這是三百零一萬公斤了他只有查三萬公斤而已我現在問你這個你沒吃到多餘喔
transcript.whisperx[18].start 485.489
transcript.whisperx[18].end 501.682
transcript.whisperx[18].text 海關來的話從海關大盤商大盤小盤商到食品業者每一個階段都有發票對吧來來來部長是不是呃如果正式的正常應該有發票這不等於是負稅署回答一下負稅署來來來回答一下
transcript.whisperx[19].start 506.079
transcript.whisperx[19].end 528.526
transcript.whisperx[19].text 大牌委員如果他進口他有些申報我們講的業學關稅我們就會有發票他進口進來絕對是有申報啊然後大牌商他賣給領出來給大牌商絕對有發票啊大牌給小牌也有發票啊小牌給這些的食品業者也是有發票啊
transcript.whisperx[20].start 529.326
transcript.whisperx[20].end 554.014
transcript.whisperx[20].text 現在如果他每一環都沒有斷鏈就每一環都沒有開立發票確實讓我們發票會有我覺得現在的衛福部還有所謂的死安擠環這個迷思其實我們財政部可以提供很大的幫助給他發票給衛福部相關的發票資料給我們地方政府的衛生局發票的資料
transcript.whisperx[21].start 555.234
transcript.whisperx[21].end 573.652
transcript.whisperx[21].text 他們幫忙攻擊,很快就抓到了,否則現在人心惶惶啊,大家想說哎喲我整個感覺去吃那個包放飲料,去吃三回,啊裡面會有辣油,吃一包一包,應該吃得到就不知道要怎樣,而且保留包票,他說消費者保留包票,他說球場用的。
transcript.whisperx[22].start 574.552
transcript.whisperx[22].end 593.302
transcript.whisperx[22].text 你還沒有補充嗎?委員我想這個部份 呃 呃 這個我實在安理說做員很重要 所以發派資料我們可以提供給衛福部去做事可以吧 請你主動提供給衛福部 主動提供給各縣市政府告訴他們說 這個可以幫助你攻擊去抓到海耳那一些蘇丹農
transcript.whisperx[23].start 595.703
transcript.whisperx[23].end 618.957
transcript.whisperx[23].text 可以嗎?馬上做喔!就是回去就做了齁!這個絕對是有幫助的喔!要不然呢現在檢察官查了半天就查到3萬你現在3千有301萬公斤勒!你要想這樣勒!不要去看那個只有什麼蘇丹農蘇丹農今天一點點而已啦!我們看下一頁那品名的部分我們跟那個衛生部再討論
transcript.whisperx[24].start 622.089
transcript.whisperx[24].end 630.872
transcript.whisperx[24].text 過去大家有關心的有很多國家隊啦我就舉3個雞蛋國家隊補助了34億綠能國家隊補助了256億電動大客車國家隊補助了600億請問這些帶給國家多少的營所稅有沒有
transcript.whisperx[25].start 643.507
transcript.whisperx[25].end 665.914
transcript.whisperx[25].text 我沒有做這方面的統計你統計一下可以嗎?合計統計國家對我們要去了解一下這個補助出來疫情期間他沒有免稅喔還是要繳稅的喔我們去了解一下這個行業別是什麼來了解一下可以嗎?去了解我再告訴你們資料其實你們才這麼多資料
transcript.whisperx[26].start 666.974
transcript.whisperx[26].end 667.134
transcript.whisperx[26].text 拜訪委員會議長
transcript.whisperx[27].start 687.698
transcript.whisperx[27].end 696.562
transcript.whisperx[27].text 部長,剛剛那個資料兩個禮拜內給我可以嗎?可以好了。好,最後一點也是很重要的今天八大航庫都在這裡我們軍工教加4%一營、台切一營、核庫、華營都是4%張營張營沒有4%
transcript.whisperx[28].start 714.81
transcript.whisperx[28].end 732.138
transcript.whisperx[28].text 他用搶金的方式幾乎:章雲董事長在不在啊?你們來一下我證明我都知道趙鋒還拼了4.5%比Average高了24%台銀跟土銀是因為另外的制度那就不在這裡面了章銀
transcript.whisperx[29].start 734.351
transcript.whisperx[29].end 750.784
transcript.whisperx[29].text 這個就不調底薪我就請問部長要不要責成張文啊真的這些老公員工都很辛苦啊大家打拼了你就不要用什麼獎金高手那個另外算但是你調薪就調底薪可不可以這個是不是我們讓董事長說明一下可不可以
transcript.whisperx[30].start 753.614
transcript.whisperx[30].end 775.529
transcript.whisperx[30].text 報告委員其實我們每一年都有調薪因為我們的薪資的制度跟其他的行庫的標準不太一樣因為其他的行庫他們都是用這個直擊的方式那每年就會自動調薪但是我們是整體性的調薪另外我們也希望說透過獎金的方式對同仁的獎金公會在意的很簡單大家都很清楚
transcript.whisperx[31].start 776.71
transcript.whisperx[31].end 776.95
transcript.whisperx[31].text 主席
transcript.whisperx[32].start 807.14
transcript.whisperx[32].end 811.906
transcript.whisperx[32].text 謝謝委員謝謝賴士葆的委員下一位請郭國文郭委員