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International Conference on Independent Component Analysis and Signal Separation

ICA 2004: Independent Component Analysis and Blind Signal Separation pp 807–815Cite as

A Novel Method for Permutation Correction in Frequency-Domain in Blind Separation of Speech Mixtures

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

Abstract

This paper presents a method for blind separation of convolutive mixtures of speech signals, based on the joint diagonalization of the time varying spectral matrices of the observation records and a novel technique to handle the problem of permutation ambiguity in the frequency domain. Simulations show that our method works well even for rather realistic mixtures in which the mixing filter has a quite long impulse response and strong echoes.

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References

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Author information

Authors and Affiliations

  1. Laboratoire des Images et des signaux, BP 46, 38402, St Martin d’Hère Cedex, France

    Christine Serviere

  2. Laboratoire de Modélisation et Calcul, BP 53, 38041, Grenoble Cedex, France

    Dinh-Tuan Pham

Authors
  1. Christine Serviere
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  2. Dinh-Tuan Pham
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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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Serviere, C., Pham, DT. (2004). A Novel Method for Permutation Correction in Frequency-Domain in Blind Separation of Speech Mixtures. 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_102

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_102

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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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