A Novel Normalization and Regularization Scheme for Broadband Convolutive Blind Source Separation

  • Robert Aichner
  • Herbert Buchner
  • Walter Kellermann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3889)

Abstract

In this paper we propose a novel blind source separation (BSS) algorithm for convolutive mixtures combining advantages of broadband algorithms with the computational efficiency of narrowband techniques. It is based on a recently presented generic broadband algorithm. By selective application of the Szegö theorem which relates properties of Toeplitz and circulant matrices, a new normalization is derived which approximates well the exact normalization of the generic broadband algorithm presented in [2]. The new scheme thus results in a computationally efficient and fast converging algorithm while still avoiding typical narrowband problems such as the internal permutation problem or circularity effects. Moreover, a novel regularization method for the generic broadband algorithm is proposed and subsequently also derived for the proposed algorithm. Experimental results in realistic acoustic environments show improved performance of the novel algorithm compared to previous approximations.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aichner, R., Buchner, H., Yan, F., Kellermann, W.: A real-time blind source separation scheme and its application to reverberant and noisy acoustic environments. Signal Processing (2005) (to appear)Google Scholar
  2. 2.
    Buchner, H., Aichner, R., Kellermann, W.: A generalization of blind source separation algorithms for convolutive mixtures based on second-order statistics. IEEE Trans. Speech Audio Processing 13(1), 120–134 (2005)CrossRefGoogle Scholar
  3. 3.
    Gray, R.M.: On the asymptotic eigenvalue distribution of Toeplitz matrices. IEEE Trans. on Information Theory 18(6), 725–730 (1972)MATHCrossRefGoogle Scholar
  4. 4.
    Hyvaerinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)CrossRefGoogle Scholar
  5. 5.
    Markel, J.D., Gray, A.H.: Linear Prediction of Speech. Springer, Berlin (1976)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Robert Aichner
    • 1
  • Herbert Buchner
    • 1
  • Walter Kellermann
    • 1
  1. 1.Multimedia Communications and Signal ProcessingUniversity of Erlangen-NurembergErlangenGermany

Personalised recommendations