An Online Blind Source Separation for Convolutive Acoustic Signals in Frequency-Domain

  • Wu Wenyan
  • Zhang Liming
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4221)


In this paper we propose a scheme for online convolutive blind acoustic source separation in frequency domain. A restriction term of DOA (Direction of Arrival) for sources is added to the cost function of mutual information. Minimizing the modified mutual information in each frequency bin, the source order can be adjusted on line. So the problem of permutation ambiguity can be settled on line, and it does not need the location information of receivers like classical DOA method. Simulation results show that the proposed algorithm has better performance than other existing methods.


Mutual Information Independent Component Analysis Independent Component Analysis Blind Source Separation Microphone Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bell, A., Sejnowski, T.: An information-maximization approach to blind separation and blind deconvolution. Nerualcomputing 7, 1129–1159 (1995)Google Scholar
  2. 2.
    Amari, S.: Natural gradient works efficiency in learning. Neuralcomputing 10, 251–276 (1998)Google Scholar
  3. 3.
    Smaragdis, P.: Blind separation of convolved mixtures in the frequency domain. Neurocomputing 22, 21–34 (1998)MATHCrossRefGoogle Scholar
  4. 4.
    Jiang, W.D.: Blind source separation of speech signals based on the amplitude correlation of neighbor bins. Journals of Circuits and System, 1–4 (2005)Google Scholar
  5. 5.
    Ikram, M.Z., Morgan, D.R.: A beamforming approach to permutation alignment for multichannel frequency-domain blind speech separation. In: Proc. ICASSP, pp. 881–884 (2002)Google Scholar
  6. 6.
    Sawada, H., Mukai, R., Araki, S., Makino, S.: A robust and precise method for solving the permutation problem of frequency-domain blind source separation. Speech and Audio Processing, IEEE Transaction 12, 530–538 (2004)CrossRefGoogle Scholar
  7. 7.
    Tang, H.W., Qin, X.Z.: Practical Optimization Method, pp. 202–205. Dalian University of Technology Press (2004)Google Scholar
  8. 8.
    Araki, S., Mukai, R., Makino, S., Nishikawa, T., Saruwatari, H.: The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech. Speech and Audio Processing, IEEE Transaction 11, 109–116 (2003)CrossRefGoogle Scholar
  9. 9.
    Convolutive mixturesII (in a virtual room),

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wu Wenyan
    • 1
  • Zhang Liming
    • 1
  1. 1.Department of Electronics EngineeringFudan UniversityShanghai

Personalised recommendations