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Signal Enhancement with Variable Span Linear Filters

  • Book
  • © 2016

Overview

Authors:
  1. Jacob Benesty

    1. INRS-EMT, University of Quebec, Quebec, Canada

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  2. Mads G. Christensen

    1. Aalborg University, Aalborg, Denmark

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    You can also search for this author in PubMed   Google Scholar

  3. Jesper R. Jensen

    1. Aalborg University, Aalborg, Denmark

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  • Presents the novel concept of variable span
  • speech enhancement filters
  • Shows various ways in which the concept can be
  • used to achieve noise reduction
  • Includes Matlab code so that all of the main ideas can be easily implemented
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Topics in Signal Processing (STSP, volume 7)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Introduction

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 1-6

  3. General Concept with Filtering Vectors

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 7-24

  4. General Concept with Filtering Matrices

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 25-39

  5. Single-Channel Signal Enhancement in the STFT Domain

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 41-74

  6. Multichannel Signal Enhancement in the Time Domain

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 75-113

  7. Multichannel Signal Enhancement in the STFT Domain

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 115-147

  8. Binaural Signal Enhancement in the Time Domain

    • Jacob Benesty, Mads G. Christensen, Jesper R. Jensen
    Pages 149-163

  9. Back Matter

    Pages 165-172
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Keywords

About this book

This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.

Authors and Affiliations

  • INRS-EMT, University of Quebec, Quebec, Canada

    Jacob Benesty

  • Aalborg University, Aalborg, Denmark

    Mads G. Christensen, Jesper R. Jensen

Bibliographic Information

  • Book Title: Signal Enhancement with Variable Span Linear Filters

  • Authors: Jacob Benesty, Mads G. Christensen, Jesper R. Jensen

  • Series Title: Springer Topics in Signal Processing

  • DOI: https://doi.org/10.1007/978-981-287-739-0

  • Publisher: Springer Singapore

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2016

  • Hardcover ISBN: 978-981-287-738-3Published: 16 February 2016

  • Softcover ISBN: 978-981-13-5709-1Published: 09 December 2018

  • eBook ISBN: 978-981-287-739-0Published: 05 February 2016

  • Series ISSN: 1866-2609

  • Series E-ISSN: 1866-2617

  • Edition Number: 1

  • Number of Pages: IX, 172

  • Number of Illustrations: 25 b/w illustrations

  • Topics: Signal, Image and Speech Processing

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