Topic tracking language model for speech recognition

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

研究成果: Article

25 引用 (Scopus)

抄録

In a real environment, acoustic and language features often vary depending on the speakers, speaking styles and topic changes. To accommodate these changes, speech recognition approaches that include the incremental tracking of changing environments have attracted attention. This paper proposes a topic tracking language model that can adaptively track changes in topics based on current text information and previously estimated topic models in an on-line manner. The proposed model is applied to language model adaptation in speech recognition. We use the MIT OpenCourseWare corpus and Corpus of Spontaneous Japanese in speech recognition experiments, and show the effectiveness of the proposed method.

元の言語English
ページ(範囲)440-461
ページ数22
ジャーナルComputer Speech and Language
25
発行部数2
DOI
出版物ステータスPublished - 2011 4
外部発表Yes

Fingerprint

Language Model
Speech Recognition
Speech recognition
Acoustics
Vary
Model
Experiment
Corpus
Experiments

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Theoretical Computer Science

これを引用

Topic tracking language model for speech recognition. / Watanabe, Shinji; Iwata, Tomoharu; Hori, Takaaki; Sako, Atsushi; Ariki, Yasuo.

:: Computer Speech and Language, 巻 25, 番号 2, 04.2011, p. 440-461.

研究成果: Article

Watanabe, Shinji ; Iwata, Tomoharu ; Hori, Takaaki ; Sako, Atsushi ; Ariki, Yasuo. / Topic tracking language model for speech recognition. :: Computer Speech and Language. 2011 ; 巻 25, 番号 2. pp. 440-461.
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