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Frequency Domain Blind Source Separation Based on Independent Vector Analysis with a Multivariate Generalized Gaussian Source Prior

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Blind Source Separation

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

Independent vector analysis (IVA) is designed for retaining the dependency contained in each source vector, while removing the dependency between different source vectors during the source separation process. It can theoretically avoid the permutation problem inherent to independent component analysis (ICA). The dependency in each source vector is maintained by adopting a multivariate source prior instead of a univariate source prior. In this chapter, a multivariate generalized Gaussian distribution is proposed to be the source prior, which can exploit the energy correlation within each source vector. It can preserve the dependency between different frequency bins better to achieve an improved separation performance, and is suitable for the whole family of IVA algorithms. Experimental results on real speech signals confirm the advantage of adopting the new source prior on three types of IVA algorithms.

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Acknowledgments

Some of the material of this chapter is under review for publication in Signal Processing as “Independent Vector Analysis with a Generalized Multivariate Gaussian Source Prior for Frequency Domain Blind Source Separation,” in October 2013.

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Authors and Affiliations

  1. Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK

    Yanfeng Liang, Syed Mohsen Naqvi & Jonathon A. Chambers

  2. University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Wenwu Wang

Authors
  1. Yanfeng Liang
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  2. Syed Mohsen Naqvi
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  3. Wenwu Wang
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  4. Jonathon A. Chambers
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Corresponding author

Correspondence to Yanfeng Liang .

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Editors and Affiliations

  1. University of Technology, Sydney, Sydney, Australia

    Ganesh R. Naik

  2. University of Surrey, Guildford, United Kingdom

    Wenwu Wang

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Liang, Y., Naqvi, S.M., Wang, W., Chambers, J.A. (2014). Frequency Domain Blind Source Separation Based on Independent Vector Analysis with a Multivariate Generalized Gaussian Source Prior. In: Naik, G., Wang, W. (eds) Blind Source Separation. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55016-4_5

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  • DOI: https://doi.org/10.1007/978-3-642-55016-4_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55015-7

  • Online ISBN: 978-3-642-55016-4

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