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Preprocessing of Independent Vector Analysis Using Feed-Forward Network for Robust Speech Recognition

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Neural Information Processing (ICONIP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7063))

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Abstract

This paper describes an algorithm to preprocess independent vector analysis (IVA) using feed-forward network for robust speech recognition. In the framework of IVA, a feed-forward network is able to be used as an separating system to accomplish successful separation of highly reverberated mixtures. For robust speech recognition, we make use of the cluster-based missing feature reconstruction based on log-spectral features of separated speech in the process of extracting mel-frequency cepstral coefficients. The algorithm identifies corrupted time-frequency segments with low signal-to-noise ratios calculated from the log-spectral features of the separated speech and observed noisy speech. The corrupted segments are filled by employing bounded estimation based on the possibly reliable log-spectral features and on the knowledge of the pre-trained log-spectral feature clusters. Experimental results demonstrate that the proposed method enhances recognition performance in noisy environments significantly.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering, Sogang University, #1 Shinsu-dong, Mapo-gu, Seoul, 121-742, Republic of Korea

    Myungwoo Oh & Hyung-Min Park

Authors
  1. Myungwoo Oh
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  2. Hyung-Min Park
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu  & Liqing Zhang  & 

  2. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

    James Kwok

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© 2011 Springer-Verlag Berlin Heidelberg

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Oh, M., Park, HM. (2011). Preprocessing of Independent Vector Analysis Using Feed-Forward Network for Robust Speech Recognition. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24958-7_43

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  • DOI: https://doi.org/10.1007/978-3-642-24958-7_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24957-0

  • Online ISBN: 978-3-642-24958-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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