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Multichannel Speech Separation Using Adaptive Parameterization of Source PDFs

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Book cover Independent Component Analysis and Blind Signal Separation (ICA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3195))

Abstract

Convolutive and temporally correlated mixtures of speech are tackled with an LP-based temporal pre-whitening stage combined with the natural gradient algorithm (NGA), to essentially perform spatial separation by maximizing entropy at the output of a nonlinear function. In the past, speech sources have been parameterized by the generalized Gaussian density (GGD) model, in which the exponent parameter directly relates to the exponent of the corresponding optimal nonlinear function. In this paper, we present an adaptive, source dependent estimation of this parameter, controlled exclusively by the statistics of the output source estimates. Comparative experimental results illustrate the inherent flexibility of the proposed method, as well as an overall increase in convergence speed and separation performance over existing approaches.

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Author information

Authors and Affiliations

  1. Signal Processing and Communications Group, Department of Electrical Engineering and Electronics, The University of Liverpool, Brownlow Hill, Liverpool, L69 3GJ, UK

    Kostas Kokkinakis & Asoke K. Nandi

Authors
  1. Kostas Kokkinakis
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  2. Asoke K. Nandi
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Editor information

Editors and Affiliations

  1. Dept. of Architecture and Computer Technology, University of Granada, Spain

    Carlos G. Puntonet  & Alberto Prieto  & 

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© 2004 Springer-Verlag Berlin Heidelberg

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Kokkinakis, K., Nandi, A.K. (2004). Multichannel Speech Separation Using Adaptive Parameterization of Source PDFs. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_62

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_62

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

  • eBook Packages: Springer Book Archive

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