Skip to main content
Springer Nature Link
Log in

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

  • Conference paper
  • First Online:
Independent Component Analysis and Blind Signal Separation (ICA 2004)

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Anemüler, J., Kollmeier, B.: Amplitude modulation decorrelation for convolutive blind source separation. In: Proceeding of ICA 2000 Conference, Helsinki, Finland, June 2000, pp. 215–220 (2000)

    Google Scholar 

  2. Mukai, R., Araki, S., Makino, S.: Separation and dereverberation performance of frequency domain blind source separation. In: Proceeding of ICA 2001 Conference, San- Diego, USA, December 2001, pp. 230–235 (2001)

    Google Scholar 

  3. Parra, L., Spence, C.: Convolutive blind source separation of non-stationary sources. IEEE Trans. on Speech and Audio Processing 8(3), 320–327 (2000)

    Article  Google Scholar 

  4. Pham, D.T.: Joint approximate diagonalization of positive definite matrices. SIAMJ. on Matrix Anal. and Appl. 22(4), 1136–1152 (2001)

    Article  MathSciNet  Google Scholar 

  5. Pham, D.T., Cardoso, J.-F.: Blind separation of instantaneous mixtures of non stationary sources. IEEE Trans. Signal Processing 49(9), 1837–1848 (2001)

    Article  MathSciNet  Google Scholar 

  6. Pham, D.T., Servière, C., Boumaraf, H.: Blind separation of convolutive audio mixtures using nonstationarity. In: Proceeding of ICA 2003 Conference, Nara, Japan (April 2003)

    Google Scholar 

  7. Pham, D.T., Servière, C., Boumaraf, H.: Blind separation of speech mixtures based on nonstationarity. In: Proceeding of the ISSPA 2003 Conference, Paris, France (July 2003)

    Google Scholar 

  8. Smaragdis, P.: Blind separation of convolved mixtures in the frequency domain. In: International Workshop on Independence & Artificial Neural Networks, University of La Laguna, Tenerife, Spain (February 1998)

    Google Scholar 

  9. Wu, H.-C., Principe, J.C.: Simultaneous diagonalization in the frequency domain (SDIF) for source separation. In: Proceeding of ICA 1999 Conference, Aussois, France, January 1999, pp. 245–250 (1999)

    Google Scholar 

Download references

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
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dinh-Tuan Pham
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

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

    Carlos G. Puntonet  & Alberto Prieto  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

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

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics