New language models using phrase structures extracted from parse trees

Takatoshi Jitsuhiro, Hirofumi Yamamoto, Setsuo Yamada, Yoshinori Sagisaka

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

Abstract

This paper proposes a new speech recognition scheme using three linguistic constraints. Multi-class composite bigram models [1] are used in the first and second passes to reflect word-neighboring characteristics as an extension of conventional word n-gram models. Trigram models with constituent boundary markers and word pattern models are both used in the third pass to utilize phrasal constraints and headword co-occurrences, respectively. These two models are made using a training text corpus with phrase structures given by an example based Transfer-Driven Machine Translation (TDMT) parser [2]. Speech recognition experiments show that the new recognition scheme reduces word errors 9.50% from the conventional scheme by using word-neighboring characteristics, that is only the multi-class composite bigram models.

Original languageEnglish
Title of host publicationEUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology
PublisherInternational Speech Communication Association
Pages697-700
Number of pages4
ISBN (Electronic)8790834100, 9788790834104
Publication statusPublished - 2001
Externally publishedYes
Event7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001 - Aalborg, Denmark
Duration: 2001 Sep 32001 Sep 7

Other

Other7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001
CountryDenmark
CityAalborg
Period01/9/301/9/7

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ASJC Scopus subject areas

  • Communication
  • Linguistics and Language
  • Computer Science Applications
  • Software

Cite this

Jitsuhiro, T., Yamamoto, H., Yamada, S., & Sagisaka, Y. (2001). New language models using phrase structures extracted from parse trees. In EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology (pp. 697-700). International Speech Communication Association.