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TRINICON-based Blind System Identification with Application to Multiple-Source Localization and Separation

  • Chapter
Blind Speech Separation

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

This contribution treats blind system identification approaches and how they can be used to localize multiple sources in environments where multipath propagation cannot be neglected, e.g., acoustic sources in reverberant environments. Based on TRINICON, a general framework for broadband adaptive MIMO signal processing, we first derive a versatile blind MIMO system identification method. For this purpose, the basics of TRINICON will be reviewed to the extent needed for this application, and some new algorithmic aspects will be emphasized. The generic approach then allows us to study various illustrative relations to other algorithms and applications. In particular, it is shown that the optimization criteria used for blind system identification allow a generalization of the well-known Adaptive Eigenvalue Decomposition (AED) algorithm for source localization: Instead of one source as with AED, several sources can be localized simultaneously. Performance evaluation in realistic scenarios will show that this method compares favourably with other state-of-the-art methods for source localization.

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Author information

Authors and Affiliations

  1. Deutsche Telekom Laboratories, Technical University Berlin, Ernst-Reuter-Platz 7, D-10587, Berlin, Germany

    Herbert Buchner

  2. Multimedia Communications and Signal Processing, University of Erlangen-Nuremberg, Cauerstr. 7, D-91058, Erlangen, Germany

    Robert Aichner & Walter Kellermann

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  1. Herbert Buchner
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  2. Robert Aichner
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  3. Walter Kellermann
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Editors and Affiliations

  1. NTT Corporation, 2-4 Hikaridai, 619-0237, Soraku-gun, Kyoto, Japan

    Shoji Makino  & Hiroshi Sawada  & 

  2. University of California, San Diego, 9500 Gilman Drive, 0523, 92093-0523, La Jolla, CA, USA

    Te-Won Lee

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Buchner, H., Aichner, R., Kellermann, W. (2007). TRINICON-based Blind System Identification with Application to Multiple-Source Localization and Separation. In: Makino, S., Sawada, H., Lee, TW. (eds) Blind Speech Separation. Signals and Communication Technology. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6479-1_4

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  • DOI: https://doi.org/10.1007/978-1-4020-6479-1_4

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  • Online ISBN: 978-1-4020-6479-1

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