Genetic algorithm-based improvement of robot hearing capabilities in separating and recognizing simultaneous speech signals

Shun'ichi Yamamoto, Kazuhiro Nakadai, Mikio Nakano, Hiroshi Tsujino, Jean Marc Valin, Ryu Takeda, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

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

6 Citations (Scopus)

Abstract

Since a robot usually hears a mixture of sounds, in particular, simultaneous speech signals, it should be able to localize, separate, and recognize each speech signal. Since separated speech signals suffer from spectral distortion, normal automatic speech recognition (ASR) may fail in recognizing such distorted speech signals. Yamamoto et al. proposed using the Missing Feature Theory to mask corrupt features in ASR, and developed the automatic missing-feature-mask generation (AMG) system by using information obtained by sound source separation (SSS). Our evaluations of recognition performance of the system indicate possibilities for improving it by optimizing many of its parameters. We used genetic algorithms to optimize these parameters. Each chromosome consists of a set of parameters for SSS and AMG, and each chromosome is evaluated by recognition rate of separated sounds. We obtained an optimized sets of parameters for each distance (from 50 cm to 250 cm by 50 cm) and direction (30, 60, and 90 degree intervals) for two simultaneous speech signals. The average isolated word recognition rates ranged from 84.9% to 94.7%.

Original languageEnglish
Title of host publicationAdvances in Applied Artificial Intelligence - 19th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2006, Proceedings
PublisherSpringer Verlag
Pages207-217
Number of pages11
ISBN (Print)3540354530, 9783540354536
Publication statusPublished - 2006 Jan 1
Externally publishedYes
Event19th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2006 - Annecy, France
Duration: 2006 Jun 272006 Jun 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4031 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2006
CountryFrance
CityAnnecy
Period06/6/2706/6/30

Keywords

  • Microphone array
  • Robot audition
  • Robot-human interaction
  • Simultaneous Speakers
  • Sound source separation
  • Speech recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yamamoto, S., Nakadai, K., Nakano, M., Tsujino, H., Valin, J. M., Takeda, R., Komatani, K., Ogata, T., & Okuno, H. G. (2006). Genetic algorithm-based improvement of robot hearing capabilities in separating and recognizing simultaneous speech signals. In Advances in Applied Artificial Intelligence - 19th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2006, Proceedings (pp. 207-217). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4031 LNAI). Springer Verlag.