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Time-Domain Beamforming and Blind Source Separation

Speech Input in the Car Environment

  • Book
  • © 2009

Overview

Editors:
  1. Julien Bourgeois

    1. Institut für Informationstechnik, Universität Ulm, Ulm, Germany

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  2. Wolfgang Minker

    1. Institut für Informationstechnik, Universität Ulm, Ulm, Germany

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  • Addresses the problem of separating spontaneous multi-party speech by way of microphone arrays and adaptive signal processing techniques
  • Presents continuous, uninterrupted adaptive algorithms that offer a simpler alternative to current methods

Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 3)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xii
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  2. Introduction

    Pages 1-5

  3. Source Separation as a Multichannel Linear Filtering Problem

    Pages 7-25

  4. Linearly Constrained Minimum Variance Beamforming

    Pages 27-38

  5. Implicit Adaptation Control for Beamforming

    Pages 39-62

  6. Second-Order Statistics Blind Source Separation

    Pages 63-79

  7. Implementation Issues in Blind Source Separation

    Pages 82-112

  8. On the Convergence and Stability in Second-Order Statistics BSS

    Pages 113-124

  9. Comparison of LCMV Beamforming and Second-Order Statistics BSS

    Pages 125-146

  10. Combining Second-Order Statistics BSS and LCMV Beamforming

    Pages 147-172

  11. Summary and Conclusions

    Pages 173-177

  12. Back Matter

    Pages 179-225
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Keywords

About this book

The development of computer and telecommunication technologies led to a revolutioninthewaythatpeopleworkandcommunicatewitheachother.One of the results is that large amount of information will increasingly be held in a form that is natural for users, as speech in natural language. In the presented work, we investigate the speech signal capture problem, which includes the separation of multiple interfering speakers using microphone arrays. Adaptive beamforming is a classical approach which has been developed since the seventies. However it requires a double-talk detector (DTD) that interrupts the adaptation when the target is active, since otherwise target cancelation occurs. The fact that several speakers may be active simulta- ouslymakesthisdetectiondi?cult,andifadditionalbackgroundnoiseoccurs, even less reliable. Our proposed approaches address this separation problem using continuous, uninterrupted adaptive algorithms. The advantage seems twofold:Firstly,thealgorithmdevelopmentismuchsimplersincenodetection mechanism needs to be designed and no threshold is to be tuned. Secondly, the performance may be improved due to the adaptation during periods of double-talk. In the ?rst part of the book, we investigate a modi?cation of the widely usedNLMSalgorithm,termedImplicitLMS(ILMS),whichimplicitlyincludes an adaptation control and does not require any threshold. Experimental ev- uations reveal that ILMS mitigates the target signal cancelation substantially with the distributed microphone array. However, in the more di?cult case of the compact microphone array, this algorithm does not su?ciently reduce the target signal cancelation. In this case, more sophisticated blind source se- ration techniques (BSS) seem necessary.

Editors and Affiliations

  • Institut für Informationstechnik, Universität Ulm, Ulm, Germany

    Julien Bourgeois, Wolfgang Minker

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