Application of variational Bayesian approach to speech recognition

Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda

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

17 Citations (Scopus)

Abstract

In this paper, we propose a Bayesian framework, which constructs shared-state triphone HMMs based on a variational Bayesian approach, and recognizes speech based on the Bayesian prediction classification; variational Bayesian estimation and clustering for speech recognition (VBEC). An appropriate model structure with high recognition performance can be found within a VBEC framework. Unlike conventional methods, including BIC or MDL criterion based on the maximum likelihood approach, the proposed model selection is valid in principle, even when there are insufficient amounts of data, because it does not use an asymptotic assumption. In isolated word recognition experiments, we show the advantage of VBEC over conventional methods, especially when dealing with small amounts of data.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 15 - Proceedings of the 2002 Conference, NIPS 2002
PublisherNeural information processing systems foundation
ISBN (Print)0262025507, 9780262025508
Publication statusPublished - 2003 Jan 1
Externally publishedYes
Event16th Annual Neural Information Processing Systems Conference, NIPS 2002 - Vancouver, BC, Canada
Duration: 2002 Dec 92002 Dec 14

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Other

Other16th Annual Neural Information Processing Systems Conference, NIPS 2002
CountryCanada
CityVancouver, BC
Period02/12/902/12/14

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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  • Cite this

    Watanabe, S., Minami, Y., Nakamura, A., & Ueda, N. (2003). Application of variational Bayesian approach to speech recognition. In Advances in Neural Information Processing Systems 15 - Proceedings of the 2002 Conference, NIPS 2002 (Advances in Neural Information Processing Systems). Neural information processing systems foundation.