Application of topic tracking model to language model adaptation and meeting analysis

Shinji Watanabe*, Tomoharu Iwata, Takaaki Hori, Atsushi Sako, Yasuo Ariki

*この研究の対応する著者

研究成果: Conference contribution

抄録

In a real environment, acoustic and language features often vary depending on the speakers, speaking styles and topic changes. This paper focuses on changes in the language environment, and applies a topic tracking model to language model adaptation for speech recognition and topic word extraction for meeting analysis. The topic tracking model can adaptively track changes in topics based on current text information and previously estimated topic models in an online manner. The effectiveness of the proposed method is shown experimentally by the improvement in speech recognition performance achieved with the Corpus of Spontaneous Japanese and by providing appropriate topic information in an automatic meeting analyzer.

本文言語English
ホスト出版物のタイトル2010 IEEE Workshop on Spoken Language Technology, SLT 2010 - Proceedings
ページ378-383
ページ数6
DOI
出版ステータスPublished - 2010
外部発表はい
イベント2010 IEEE Workshop on Spoken Language Technology, SLT 2010 - Berkeley, CA, United States
継続期間: 2010 12月 122010 12月 15

出版物シリーズ

名前2010 IEEE Workshop on Spoken Language Technology, SLT 2010 - Proceedings

Other

Other2010 IEEE Workshop on Spoken Language Technology, SLT 2010
国/地域United States
CityBerkeley, CA
Period10/12/1210/12/15

ASJC Scopus subject areas

  • 言語および言語学

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