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Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation

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Book cover Blind Source Separation

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

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Abstract

Blind source separation (BSS) and beamforming are two well-known multiple microphone techniques for speech separation and extraction in cocktail-party environments. However, both of them perform limitedly in highly reverberant and dynamic scenarios. Emulating human auditory systems, this chapter proposes a combined method for better separation and extraction performance, which uses superdirective beamforming as a preprocessor of frequency-domain BSS. Based on spatial information only, superdirective beamforming presents abilities of dereverberation and noise reduction and performs robustly in time-varying environments. Using it as a preprocessor can mitigate the inherent “circular convolution approximation problem” of the frequency-domain BSS and enhances its robustness in dynamic environments. Meanwhile, utilizing statistical information only, BSS can further reduce the residual interferences after beamforming efficiently. The combined method can exploit both spatial information and statistical information about microphone signals and hence performs better than using either BSS or beamforming alone. The proposed method is applied to two specific challenging tasks, namely a separation task in highly reverberant environments with the positions of all sources known, and a target speech extraction task in highly dynamic cocktail-party environments with only the position of the target known. Experimental results prove the effectiveness of the proposed method.

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Notes

  1. 1.

    More details of the experiment can be found in Sect. 11.4.2.

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Acknowledgments

This work is partly supported by the Alexander von Humboldt Foundation.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China

    Lin Wang & Fuliang Yin

  2. Institute of Physics - Signal Processing Group, University of Oldenburg, Oldenburg, Germany

    Lin Wang

  3. Information and Communications Technology, National Research Council, Ottawa, Canada

    Heping Ding

Authors
  1. Lin Wang
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  3. Fuliang Yin
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Correspondence to Lin Wang .

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Editors and Affiliations

  1. University of Technology, Sydney, Sydney, Australia

    Ganesh R. Naik

  2. University of Surrey, Guildford, United Kingdom

    Wenwu Wang

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Wang, L., Ding, H., Yin, F. (2014). Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation. In: Naik, G., Wang, W. (eds) Blind Source Separation. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55016-4_11

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  • DOI: https://doi.org/10.1007/978-3-642-55016-4_11

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