Abstract
Frequency domain blind source separation has the great advantage that the complicated convolution in time domain becomes multiple efficient multiplications in frequency domain. However, the inherent ambiguity of permutation of ICA becomes an important problem that the separated signals at different frequencies may be permuted in order. Mapping the separated signal at each frequency to a target source remains to be a difficult problem. In this paper, we first discuss the inter-frequency correlation based method [1], and propose a new method using the continuity in power between adjacent frequency components of same source. The proposed method also implicitly utilizes the information of inter-frequency correlation, as such has better performance than the previous method.
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References
Ikeda, S., Murata, N.: A method of blind separation based on temporal structure of signals. In: Proceedings of The Fifth International Conference on Neural Information Processing (ICONIP 1998, Kitakyushu), pp. 737–742 (1998)
Torkkola, K.: Blind separation for audio signals – are we there yet? In: Proc. Workshop on Independent Analysis and Blind Signal Separation (January 11-16, 1999)
Hu, X., Kobatake, H.: Blind source separation using ICA and beamforming. In: Proc. of ICA 2003, April 2003, pp. 597–602 (2003)
Sawada, H., Mukai, R., Araki, S., Makino, S.: A Robust and Precise Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation. In: Proc. of ICA 2003, April 2003, pp. 505–510 (2003)
Bell, A., Sejnowski, T.: An information maximization approach to blind separation and blind deconvolution. Neural Computation 7, 1129–1159 (1995)
Asano, F., Motomura, Y., Asoh, H., Matsui, T.: Effect of PCA filter in blind source separation. In: Proc. ICA 2000, June 2000, pp. 57–62 (2000)
Hu, X., Kobatake, H.: Blind speech separation - the low-independence problem and solution. In: Proc. of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), April 2003, vol. V, pp. 281–284 (2003)
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© 2004 Springer-Verlag Berlin Heidelberg
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Kamata, K., Hu, X., Kobatake, H. (2004). A New Approach to the Permutation Problem in Frequency Domain Blind Source Separation. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_107
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DOI: https://doi.org/10.1007/978-3-540-30110-3_107
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