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    Source separation employing beamforming and SRP-PHAT localization in three-speaker room environments

    Access Status
    Open access via publisher
    Authors
    Nordholm, Sven
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Nordholm, S. 2017. Source separation employing beamforming and SRP-PHAT localization in three-speaker room environments. Vietnam Journal of computer Science. 4: pp. 161-170.
    Source Title
    Vietnam Journal of computer Science
    DOI
    10.1007/s40595-016-0085-x
    ISSN
    2196-8896
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/65741
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new blind speech separation algorithm using beamforming technique that is capable of extracting each individual speech signal from a mixture of three speech sources in a room. The speech separation algorithm utilizes the steered response power phase transform for obtaining a localization estimate for each individual speech source in the frequency domain. Based on those estimates each desired speech signal is extracted from the speech mixture using an optimal beamforming technique. To solve the permutation problem, a permutation alignment algorithm based on the mutual output correlation is employed to group the output signals into the correct sources from each frequency bin. Evaluations using real speech recordings in a room environment show that the proposed blind speech separation algorithm offers high interference suppression level whilst maintaining low distortion level for each desired signal.

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