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Blind Source Separation of Convolutive Mixtures of Speech

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Adaptive Signal Processing

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

This chapter introduces the blind source separation (BSS) of convolutive mixtures of acoustic signals, especially speech. A statistical and computational technique, called independent component analysis (ICA), is examined. By achieving nonlinear decorrelation, nonstationary decorrelation, or time-delayed decorrelation, we can find source signals only from observed mixed signals. Particular attention is paid to the physical interpretation of BSS from the acoustical signal processing point of view. Frequency-domain BSS is shown to be equivalent to two sets of frequency domain adaptive microphone arrays, i.e., adaptive beamformers (ABFs). Although BSS can reduce reverberant sounds to some extent in the same way as ABF, it mainly removes the sounds from the jammer direction. This is why BSS has difficulties with long reverberation in the real world. If sources are not “independent,” the dependence results in bias noise when obtaining the correct unmixing filter coefficients. Therefore, the performance of BSS is limited by that of ABF. Although BSS is upper bounded by ABF, BSS has a strong advantage over ABF. BSS can be regarded as an intelligent version of ABF in the sense that it can adapt without any information on the array manifold or the target direction, and sources can be simultaneously active in BSS.

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Author information

Authors and Affiliations

  1. NTT Communication Science Laboratories, 2-4 Hikaridai, Seika-cho Soraku-gun, Kyoto, 619-0237, Japan

    Shoji Makino

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  1. Shoji Makino
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Editors and Affiliations

  1. Bell Labs, Lucent Technologies, 700 Mountain Avenue, 07974-0636, Murray Hill, NJ, USA

    Jacob Benesty  & Yiteng Huang  & 

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© 2003 Springer-Verlag Berlin Heidelberg

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Makino, S. (2003). Blind Source Separation of Convolutive Mixtures of Speech. In: Benesty, J., Huang, Y. (eds) Adaptive Signal Processing. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-11028-7_7

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  • DOI: https://doi.org/10.1007/978-3-662-11028-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05507-2

  • Online ISBN: 978-3-662-11028-7

  • eBook Packages: Springer Book Archive

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