Abstract
A new two-stage blind source separation (BSS) for convolutive mixtures of speech is proposed, in which a Single-Input Multiple-Output (SIMO)-model-based ICA and binary mask processing are combined. SIMO-model-based ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to the attractive property, binary mask processing can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results using small directional microphone array reveal that the separation performance can be considerably improved by using the proposed method in comparison to the conventional source separation methods.
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© 2006 Springer-Verlag Berlin Heidelberg
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Mori, Y., Saruwatari, H., Takatani, T., Shikano, K., Hiekata, T., Morita, T. (2006). ICA and Binary-Mask-Based Blind Source Separation with Small Directional Microphones. In: Rosca, J., Erdogmus, D., PrÃncipe, 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_81
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DOI: https://doi.org/10.1007/11679363_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
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