Abstract
In this paper, we introduce a new blind source separation (BSS) method for linear instantaneous mixtures, which only assumes the sources to be uncorrelated. It is based on the time-segmented frequency- dependent real coherence function of the observed signals. This parameter makes it possible to detect time-frequency zones where only one source is active. Such zones are then used to identify the required separating coefficients by means of ratios of power spectral densities of the observed signals. This BSS method yields very high performance for mixtures of speech and/or noise signals, i.e. SNR improvements range from 50 dB to more than 90 dB.
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References
J.F. Cardoso: Blind Signal Separation: Statistical Principles, Proceedings of the IEEE, vol. 86, no. 10, 1998.
A. Hyvarinen, J. Karhunen, E. Oja: Independent Component Analysis, John Wiley, 2001.
A. Belouchrani, M.G. Amin: Blind source separation using time-frequency distributions: algorithm and asymptotic performance, Proc. ICASSP’97, pp. 3469–3472, Munich, Germany, April 31–24, 1997.
A. Holobar, C. Fevotte, C. Doncarli, D. Zazula: Single autoterms selection for blind source separation in time-frequency plane, Proc. EUSIPCO’2002, Toulouse, France, Sept. 3–6, 1997.
L. Giulieri, N. Thirion-Moreau, P.-Y Arquès: Blind sources separation using bilinear and quadratic time-frequency representations, Proc. ICA’2001, pp. 486–491, San Diego, California, Dec. 9–13, 2001.
A. Jourjine, S. Rickard, O. Yilmaz: Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures, Proc. ICASSP’2000, vol. 5, pp. 2985–2988, Istanbul, Turkey, June 18–22, 2000.
S. Rickard, R. Balan, J. Rosca: Real-time time-frequency based blind source separation, Proc. ICA’2001, pp. 651–656, San Diego, California, Dec. 9–13, 2001.
F. Abrard, Y. Deville, P. White: A new source separation approach based on timefrequency analysis for instantaneous mixtrures, Proc. ECM2S’2001, pp. 259–267, Toulouse, France, May 30–June 1, 2001.
F. Abrard, Y. Deville, P. White: From blind source separation to blind source cancellation in the underdetermined case: a new approach based on time-frequency analysis, Proc. ICA’2001, pp. 734–739, San Diego, California, Dec. 9–13, 2001.
M. Durnerin, N. Martin: Démarche d’analyse spectrale en vue d’une interprétation automatique, application à un signal d’engrenages, Proc. GRETSI’1997, vol. 1, pp. 539–542, Grenoble, France, sept. 1997.
B. Albouy, Y. Deville: Segmentation and separation of speech and/or noise signals, using coherence functions and power spectra, Proc. ICA’2003, Nara, Japan, April 1–4, 2003.
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Albouy, B., Deville, Y. (2003). A time-frequency blind source separation method based on segmented coherence function. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_37
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DOI: https://doi.org/10.1007/3-540-44869-1_37
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