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Single-speaker/multi-speaker co-channel speech classification

Abstract : The demand for content-based management and real-time manipulation of audio data is constantly increasing. This paper presents a method to identify temporal regions, in a segment of co-channel speech, as being either single-speaker or multi- speaker speech. The state of the art approach for this purpose is the kurtosis. In this paper, a set of complementary time- domain and frequency-domain features is studied. The employed classification scheme is the one-class SVM classifier. A recognition rate of 94.75 % is reached. The set of features providing the best performance is determined.
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Submitted on : Thursday, January 6, 2011 - 11:29:16 AM
Last modification on : Monday, December 14, 2020 - 2:10:02 PM


  • HAL Id : hal-00552948, version 1



Stéphane Rossignol, Olivier Pietquin. Single-speaker/multi-speaker co-channel speech classification. Interspeech 2010, Sep 2010, Makuhari, Japan. pp.2322-2325. ⟨hal-00552948⟩



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