Bi-Spectral Acoustic Features for Robust Speech Recognition
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概要
- 論文の詳細を見る
The extraction of acoustic features for robust speech recognition is very important for improving its performance in realistic environments. The bi-spectrum based on the Fourier transformation of the third-order cumulants expresses the non-Gaussianity and the phase information of the speech signal, showing the dependency between frequency components. In this letter, we propose a method of extracting short-time bispectral acoustic features with averaging features in a single frame. Merged with the conventional Mel frequency cepstral coefficients (MFCC) based on the power spectrum by the principal component analysis (PCA), the proposed features gave a 6.9% relative lower a word error rate in Japanese broadcast news transcription experiments.
- （社）電子情報通信学会の論文
- 2008-03-01
著者
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KAWABE Akira
Department of Biotechnology, Graduate School of Engineering, Osaka University
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Kobayashi A
National Inst. Advanced Industrial Sci. And Technol. Ibaraki Jpn
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Imai Toru
Nhk Science And Technical Research Laboratories
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Imai T
Nhk Science And Technical Research Laboratories
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Takagi Tohru
Science And Technical Research Laboratories
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Kobayashi Akio
Dep. Of Biotechnology Graduate School Of Engineering Osaka Univ.
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Kobayashi A
Laboratory Of Bioresources Chemistry Faculty Of Agriculture Okayama University
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Kobayashi A
Ochanomizu Univ. Tokyo Jpn
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Takagi Tohru
Nhk Science And Technical Research Laboratories
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Kobayashi A
Dep. Of Biotechnology Graduate School Of Engineering Osaka Univ.
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Kawabe Akira
Department Of Biotechnology Graduate School Of Engineering Osaka University
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ONOE Kazuo
NHK Science and Technical Research Laboratories
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SATO Shoei
NHK Science and Technical Research Laboratories
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HOMMA Shinichi
NHK Science and Technical Research Laboratories
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KOBAYASHI Akio
NHK Science and Technical Research Laboratories
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Homma Shinich
Nhk Science And Technical Research Laboratories
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