google speech research, history and a local …contextual conditioning and discriminatively training...

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アクセス こちらのアドレスまたは右記QRよりご確認ください。 https://www.eng.tohoku.ac.jp/map/?menu=campus&area=d 電子情報システム・応物系 101大講義室 (15:30開場、17:30質疑終了) 第3回 講演会のお知らせ 人工知能エレクトロニクス卓越大学院プログラム Google Speech Research, 8 2020 THU 20  16 : 00 Google Research Senior Staff Research Scientist Dr.Michiel Bacchiani 略歴:Michiel Bacchiani has been a speech researcher with Google for the past 15 years. He currently manages a research group in Google Tokyo focused on jointly modeling speech and natural language understanding. Previously he managed the acoustic modeling team responsible for developing novel algorithms and training infrastructure for all speech recognition applications backing Google services. Before joining Google, Michiel Bacchiani worked as a member of technical staff at IBM Research, as a technical staff member at AT\&T Labs Research and as a research associate at Advanced Telecommunications Research labs in Kyoto, Japan.Michiel Bacchiani is an active member of the academic community. He served as the chair of the IEEE Spoken Language Technical Committee. He is a Senior Area Editor and board member for the IEEE/ACM Transactions on Audio, Speech, and Language. He is a subject editor and board member of the Speech Communication journal. He has served as an organizing committee member or technical chair on numerous workshop committees like ASRU and SLT. He has served as an area chair for several large international conferences like ICASSP and Interspeech. As an active participant with the academic community as an author, he has published more than 50 scientific publications. 主 催 人工知能エレクトロニクス卓越大学院プログラム 本講演会はどなたでも参加できます。参加希望の方は以下の ウェブページから参加登録して下さい。 http://www.aie.tohoku.ac.jp 講 師 参加申込 Recent years have shown a large scale adoption of speech recognition by the public, in particular around mobile devices. The speech group at Google started in earnest in 2005 as a research project with a handful of members. Today the speech group at Google has over 350 members and our systems process centuries of speech each week. This talk will discuss some of the history of this remarkable transformation from a Google perspective.The second half of the talk will focus on novel neural modeling for speech recognition. It will briefly discuss how we tackled a number of challenges to make such models feasible for use in real-life applications. Issues such as latency, use of external text-only corpora, contextual conditioning and discriminatively training will be presented. Finally, building on these results, some early work and motivations for the new research effort that is growing in the Tokyo office will be presented. 事務局: 東北大学電子情報システム・応物系 2号館404号室 TEL 022-795-5667 MAIL aie-offi[email protected] 17 : 00 history and a local perspective

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Page 1: Google Speech Research, history and a local …contextual conditioning and discriminatively training will be presented. Finally, building on these results, some early work and motivations

アクセス こちらのアドレスまたは右記QRよりご確認ください。

https://www.eng.tohoku.ac.jp/map/?menu=campus&area=d

電子情報システム・応物系101大講義室

(15:30開場、17:30質疑終了)

     第3回 講演会のお知らせ

人工知能エレクトロニクス卓越大学院プログラム

G o o g l e S p e e c h R e s e a r c h ,

8 2020

THU 20 

16:00

Goog l e R e s e a r c hS en i o r S t aff R e s e a r c h S c i e n t i s t

Dr .Michiel Bacchiani略歴:Michie l Bacchiani has been a speech researcher wi th Google for the past 15 years . He cu r rent l y manages a re sea rch g roup in Goog le Tokyo focused on jo in t l y mode l ing s pee ch and n a t u r a l l a nguage unde r s t and i ng . P r e v i ou s l y h e managed t h e a cou s t i c model ing team respons ib le for developing novel a lgor i thms and t ra in ing inf rast ructure for a l l speech recognit ion appl icat ions back ing Google serv ices . Before jo in ing Google , Michie l Bacchiani worked as a member of technica l s taff at IBM Research , as a technica l s t a ff m emb e r a t A T \ & T L a b s R e s e a r c h a n d a s a r e s e a r c h a s s o c i a t e a t A d v a n c e d T e l e c ommun i c a t i o n s R e s e a r c h l a b s i n K yo t o , J a p an .M i c h i e l B a c ch i a n i i s a n a c t i v e membe r o f t h e a c a d em i c c ommun i t y . H e s e r v e d a s t h e c h a i r o f t h e I E E E S p o k e n Language Techn ica l Commit tee . He i s a Sen io r A rea Ed i to r and board member fo r the I E EE /ACM T r an sac t i on s on Aud io , Speech , and Language . He i s a sub j e c t ed i t o r and board member o f the Speech Communica t ion journa l . He has se rved as an o rgan iz ing commi t tee member o r t echn i ca l cha i r on numerous work shop commi t tees l i ke ASRU and SLT . He has served as an area cha i r for severa l la rge internat iona l conferences l i ke ICASSP and In te r speech . As an ac t i ve pa r t i c ipant w i th the academic communi ty as an author , he has publ ished more than 50 sc ient ific publ icat ions .

主 催 人工知能エレクトロニクス卓越大学院プログラム

本講演会はどなたでも参加できます。参加希望の方は以下のウェブページから参加登録して下さい。http://www.aie .tohoku.ac. jp

講 師

参加申込

 Recent years have shown a large scale adoption of speech recognition by the public, in particular

around mobile devices. The speech group at Google started in earnest in 2005 as a research project with a handful of members. Today the speech group at Google has over 350 members and our systems process centuries of speech each week. This talk will discuss some of the history of this remarkable transformation from a Google perspective.The second half of the talk will focus on novel neural modeling for speech recognition. It wil l briefly discuss how we tackled a number of challenges to make such models feasible for use in real-life applications. Issues such as latency, use of external text-only corpora, contextual conditioning and discriminatively training will be presented. Finally, building on these results, some early work and motivations for the new research effort that is growing in the Tokyo office will be presented.

事務局:東北大学電子情報システム・応物系 2号館404号室 |TEL 022-795-5667 MAIL [email protected]

17:00

h i s t o r y a n d a l o c a l p e r s p e c t i v e