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    Statistical voice activity detection using low-variance spectrum estimation and an adaptive threshold

    Access Status
    Fulltext not available
    Authors
    Davis, A.
    Nordholm, Sven
    Togneri, R.
    Date
    2006
    Type
    Journal Article
    
    Metadata
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    Citation
    Davis, Alan and Nordholm, Sven and Togneri, Roberto. 2006. Statistical voice activity detection using low-variance spectrum estimation and an adaptive threshold. IEEE Transactions on Audio, Speech, and Language Processing. 14 (2): pp. 412-423.
    Source Title
    IEEE Transactions on Audio, Speech, and Language Processing
    Additional URLs
    http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1597247
    ISSN
    1558-7916
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/37889
    Collection
    • Curtin Research Publications
    Abstract

    Traditionally voice activity detection algorithms are based on any combination of general speech properties such as temporal energy variations, periodicity, and spectrum. This paper describes a novel statistical method for voice activity detection using a signal to noise ratio measure. The method employs a low-variance spectrum estimate and determines an optimal threshold based on the estimated noise statistics. A possible implementation is presented and evaluated over a large test set and compared to current modern standardized algorithms. The evaluations indicate promising results with the proposed scheme being comparable or favorable over the whole test set.

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