On the Use of Kernel PCA for Feature Extraction in Speech Recognition(Speech and Hearing)
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概要
- 論文の詳細を見る
This paper describes an approach to feature extraction in speech recognition systems using kernel principal component analysis (KPCA). This approach represents speech features as the projection of the mel-cepstral coefficients mapped into a feature space via a non-linear mapping onto the principal components. The non-linear mapping is implicitly performed using the kernel-trick, which is a useful way of not mapping the input space into a feature space explicitly, making this mapping computationally feasible. It is shown that the application of dynamic (Δ) and acceleration (ΔΔ) coefficients, before and/or after the KPCA feature extraction procedure, is essential in order to obtain higher classification performance. Better results were obtained by using this approach when compared to the standard technique.
- 社団法人電子情報通信学会の論文
- 2004-12-01
著者
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ZEN Heiga
Department of Computer Science and Engineering, Nagoya Institute of Technology
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TOKUDA Keiichi
Department of Computer Science and Engineering, Nagoya Institute of Technology
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Zen Heiga
Department Of Computer Science And Engineering Nagoya Institute Of Technology
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Tokuda Keiichi
Department Of Computer Science And Engineering Nagoya Institute Of Technology
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Lima Amaro
Department Of Computer Science And Engineering Nagoya Institute Of Technology
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NANKAKU Yoshihiko
Department of Computer Science and Engineering, Nagoya Institute of Technology
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KITAMURA Tadashi
Department of Computer Science and Engineering, Nagoya Institute of Technology
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MIYAJIMA Chiyomi
Department of Computer Science and Engineering, Nagoya Institute of Technology
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Miyajima Chiyomi
Department Of Media Science Nagoya University
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Kitamura Tadashi
Department Of Computer Science And Engineering Nagoya Institute Of Technology
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Kitamura Tadashi
Department Of Cardiothoracic Surgery The University Of Tokyo
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Nankaku Yoshihiko
Department Of Computer Science And Engineering Nagoya Institute Of Technology
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Tokuda Keiichi
Department Of Computer Science Naogya Institute Of Technology
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Zen Heiga
Department Of Computer Science Naogya Institute Of Technology
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Kitamura Tadashi
Department Of Cardiothoracic Surgery Faculty Of Medicine University Of Tokyo
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