Evaluation of two simultaneous continuous speech recognition with ICA BSS and MFT-based ASR

Ryu Takeda, Shun'ichi Yamamoto, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

An adaptation of independent component analysis (ICA) and missing feature theory (MFT)-based ASR for two simultaneous continuous speech recognition is described. We have reported on the utility of a system with isolated word recognition, but the performance of the MFT-based ASR is affected by the configuration, such as an acoustic model. The system needs to be evaluated under a more general condition. It first separates the sound sources using ICA. Then, spectral distortion in the separated sounds is estimated to generate missing feature masks (MFMs). Finally, the separated sounds are recognized by MFT-based ASR. We estimate spectral distortion in the temporal-frequency domain in terms of feature vectors, and we generate MFMs. We tested an isolated word and the continuous speech recognition with a cepstral and spectral feature. The resulting system outperformed the baseline robot audition system by 13 and 6 points respectively on the spectral features.

本文言語English
ホスト出版物のタイトルNew Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
出版社Springer Verlag
ページ384-394
ページ数11
ISBN(印刷版)9783540733225
DOI
出版ステータスPublished - 2007
外部発表はい
イベント20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007 - Kyoto, Japan
継続期間: 2007 6 262007 6 29

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4570 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
CountryJapan
CityKyoto
Period07/6/2607/6/29

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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