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    A multi-filter system for speech enhancement under low signal-to-noise ratios

    Access Status
    Open access via publisher
    Authors
    Yiu, Ka Fai
    Chan, Kit Yan
    Low, Siow
    Nordholm, Sven
    Date
    2009
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Yiu, K. and Chan, K. and Low, S. and Nordholm, S. 2009. A multi-filter system for speech enhancement under low signal-to-noise ratios. Journal of Industrial and Management Optimization. 5 (3): pp. 671-682.
    Source Title
    Journal of Industrial and management optimization
    DOI
    10.3934/jimo.2009.5.671
    ISSN
    1547-5816
    Faculty
    Curtin Business School
    The Digital Ecosystems and Business Intelligence Institute (DEBII)
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/32975
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, the problem of deteriorating performance of speech recognition under very low signal-to-noise ratios (SNR) is considered. In particular, for a given pre-trained speech recognizer and for a finite set of speech commands, we show that popular noise reduction methods have a mixed performance in speech recognition accuracy under very low SNR. Although most noise reduction methods are attempting to reduce speech distortion or to increase noise suppression, it does not necessarily improve speech recognition accuracy very much due to the complexity of the recognizer. We propose a new hybrid algorithm to optimize on the speech recognition accuracy directly by mixing different noise reduction methods together. We show that this method can indeed improve the accuracy significantly.

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