A language model for conversational speech recognition using information designed for speech translation

Hirofumi Yamamoto, Kouichi Tanigaki, Yoshinori Sagisaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a new language model is proposed for speech recognition in conversational speech translation. In conversation, speech strongly depends on the previous utterance of the other participant. Applying this dependency in language modeling, we can reduce the speech recognition error rate. To this end, we propose the following new language model where the content of the previous utterance is expressed by an interlingual representation which is widely used in the spoken language translation research group C-star. The proposed method reduces word error rate by 6% (from 14.7% to 13.9%), confirming our expectations.

Original languageEnglish
Title of host publication6th International Conference on Spoken Language Processing, ICSLP 2000
PublisherInternational Speech Communication Association
ISBN (Electronic)7801501144, 9787801501141
Publication statusPublished - 2000
Externally publishedYes
Event6th International Conference on Spoken Language Processing, ICSLP 2000 - Beijing, China
Duration: 2000 Oct 162000 Oct 20

Other

Other6th International Conference on Spoken Language Processing, ICSLP 2000
CountryChina
CityBeijing
Period00/10/1600/10/20

ASJC Scopus subject areas

  • Linguistics and Language
  • Language and Linguistics

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  • Cite this

    Yamamoto, H., Tanigaki, K., & Sagisaka, Y. (2000). A language model for conversational speech recognition using information designed for speech translation. In 6th International Conference on Spoken Language Processing, ICSLP 2000 International Speech Communication Association.