Speech Recognition Under the Unstationary Noise Based on the Noise Markov Model and Spectral-Subtraction

Tetsunori Kobayashi*, Ryuji Mine, Katsuhiko Shirai

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

In this paper, mechanisms to recognize speech in time varying noise are proposed. In these methods, the noise source and the speech source are modeled independently. The probabilities that these two models emit observed data sequence are calculated. We tested two methods. The first one uses HMMs to model both of noise and speech. The second one uses a normal Morkov model for noise representation. Adopting normal Markov model, the noise model itself become rather complex, however, the dynamical features such as delta cepstrum can be easily and precisely considered. Using these methods, 100 word recognition tests in car noise environment are performed. As the results, the performances are improved by 23 % and 26 % using the first and the second method, respectively, as compared with normal spectral subtraction.

Original languageEnglish
Pages833-836
Number of pages4
Publication statusPublished - 1993
Event3rd European Conference on Speech Communication and Technology, EUROSPEECH 1993 - Berlin, Germany
Duration: 1993 Sep 221993 Sep 25

Conference

Conference3rd European Conference on Speech Communication and Technology, EUROSPEECH 1993
Country/TerritoryGermany
CityBerlin
Period93/9/2293/9/25

Keywords

  • Hidden Markov Model
  • Noise Reduction
  • Speech Recognition
  • Unstationary Noise

ASJC Scopus subject areas

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

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