Abstract
This paper presents a novel method for underdetermined acoustic source separation of convolutive mixtures. Multiple complex-valued Independent Component Analysis adaptations jointly estimate the mixing matrix and the temporal activities of multiple sources in each frequency. A structure based on a recursive temporal weighting of the gradient enforces each ICA adaptation to estimate mixing parameters related to sources having a disjoint temporal activity. Permutation problem is reduced imposing a multiresolution spatio-temporal correlation of the narrow-band components. Finally, aligned mixing parameters are used to recover the sources through L 0-norm minimization and a post-processing based on a single channel Wiener filtering. Promising results obtained over a public dataset show that the proposed method is an effective solution to the underdetermined source separation problem.
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References
Christensen, H., Barker, J., Ma, N., Green, P.: The chime corpus: a resource and a challenge for computational hearing in multisource environments. In: Proceedings of Interspeech, Makuhari, Japan (2010)
Duong, N.Q.K., Vincent, E., Gribonval, R.: Under-determined convolutive blind source separation using spatial covariance models. In: Proc. ICASSP (2010)
Araki, S., Nakatani, T., Sawada, H., Makino, S.: Stereo Source Separation and Source Counting with MAP Estimation with Dirichlet Prior Considering Spatial Aliasing Problem. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds.) ICA 2009. LNCS, vol. 5441, pp. 742–750. Springer, Heidelberg (2009)
Sawada, H., Araki, S., Mukai, R., Makino, S.: Blind extraction of dominant target sources using ICA and time-frequency masking. IEEE Trans. on Audio, Speech, and Language Processing 14(6), 2165–2173 (2006)
Ozerov, A., Fevotte, C.: Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation. IEEE Trans. on Audio, Speech and Language Processing 18(3), 550–563 (2010)
Nesta, F., Matassoni, M.: Robust automatic speech recognition through on-line semi-blind source extraction. In: Proceedings of CHIME, Florence, Italy (2011)
Vincent, E.: Complex Nonconvex l p Norm Minimization for Underdetermined Source Separation. In: Davies, M.E., James, C.J., Abdallah, S.A., Plumbley, M.D. (eds.) ICA 2007. LNCS, vol. 4666, pp. 430–437. Springer, Heidelberg (2007)
Takahashi, Y., Takatani, T., Osako, K., Saruwatari, H., Shikano, K.: Blind spatial subtraction array for speech enhancement in noisy environment. IEEE Trans. on Audio, Speech and Language Processing 17(4), 650–664 (2009)
Cichocki, A., Amari, S.-I.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. John Wiley & Sons, Inc., New York (2002)
Nesta, F., Svaizer, P., Omologo, M.: Convolutive BSS of short mixtures by ICA recursively regularized across frequencies. IEEE Transactions on Audio, Speech, and Language Processing 19(3), 624–639 (2011)
Nesta, F., Omologo, M.: Cooperative wiener-ICA for source localization and separation by distributed microphone arrays. In: Proc. of ICASSP (March 2010)
Nesta, F., Omologo, M.: Generalized state coherence transform for multidimensional TDOA estimation of multiple sources. IEEE Transactions on Audio, Speech, and Language Processing (2011)
Nesta, F., Omologo, M.: Enhanced multidimensional spatial functions for unambiguous localization of multiple sparse acoustic sources. In: Proc. of ICASSP, Kyoto, Japan (to appear, 2012)
Araki, S., Nesta, F., Vincent, E., Koldovsky, Z., Nolte, G., Ziehe, A., Benichoux, A.: The 2011 Signal Separation Evaluation Campaign (SiSEC2011):-Audio Source Separation. In: Theis, F., et al. (eds.) LVA/ICA 2012. LNCS, vol. 7191, pp. 414–422. Springer, Heidelberg (2012)
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Nesta, F., Omologo, M. (2012). Convolutive Underdetermined Source Separation through Weighted Interleaved ICA and Spatio-temporal Source Correlation. In: Theis, F., Cichocki, A., Yeredor, A., Zibulevsky, M. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2012. Lecture Notes in Computer Science, vol 7191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28551-6_28
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DOI: https://doi.org/10.1007/978-3-642-28551-6_28
Publisher Name: Springer, Berlin, Heidelberg
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