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.
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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)
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)
Gray, R.M.: On the asymptotic eigenvalue distribution of Toeplitz matrices. IEEE Trans. on Information Theory 18(6), 725–730 (1972)
Hyvaerinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)
Markel, J.D., Gray, A.H.: Linear Prediction of Speech. Springer, Berlin (1976)
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© 2006 Springer-Verlag Berlin Heidelberg
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Aichner, R., Buchner, H., Kellermann, W. (2006). A Novel Normalization and Regularization Scheme for Broadband Convolutive Blind Source Separation. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_66
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DOI: https://doi.org/10.1007/11679363_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
Online ISBN: 978-3-540-32631-1
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