Canonical Correlation Analysis in Speech Enhancement

  • Jacob Benesty
  • Israel Cohen

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Jacob Benesty, Israel Cohen
    Pages 1-3
  3. Jacob Benesty, Israel Cohen
    Pages 5-14
  4. Jacob Benesty, Israel Cohen
    Pages 15-35
  5. Jacob Benesty, Israel Cohen
    Pages 37-57
  6. Jacob Benesty, Israel Cohen
    Pages 59-77
  7. Jacob Benesty, Israel Cohen
    Pages 79-101
  8. Jacob Benesty, Israel Cohen
    Pages 103-117
  9. Back Matter
    Pages 119-121

About this book

Introduction

This book focuses on the application of canonical correlation analysis (CCA) to speech enhancement using the filtering approach. The authors explain how to derive different classes of time-domain and time-frequency-domain noise reduction filters, which are optimal from the CCA perspective for both single-channel and multichannel speech enhancement. Enhancement of noisy speech has been a challenging problem for many researchers over the past few decades and remains an active research area. Typically, speech enhancement algorithms operate in the short-time Fourier transform (STFT) domain, where the clean speech spectral coefficients are estimated using a multiplicative gain function. A filtering approach, which can be performed in the time domain or in the subband domain, obtains an estimate of the clean speech sample at every time instant or time-frequency bin by applying a filtering vector to the noisy speech vector.

Compared to the multiplicative gain approach, the filtering approach more naturally takes into account the correlation of the speech signal in adjacent time frames. In this study, the authors pursue the filtering approach and show how to apply CCA to the speech enhancement problem. They also address the problem of adaptive beamforming from the CCA perspective, and show that the well-known Wiener and minimum variance distortionless response (MVDR) beamformers are particular cases of a general class of CCA-based adaptive beamformers.

Keywords

CCA Canonical Correlation Analysis Time-frequency-domain Noise Reduction Single-channel speech enhancement Multichannel speech enhancement Adaptive beamforming Minimum variance distortionless response Wiener distortionless response CCA-based adaptive beamformers

Authors and affiliations

  • Jacob Benesty
    • 1
  • Israel Cohen
    • 2
  1. 1.INRS-EMTUniversity of QuebecMontréalCanada
  2. 2.Technion—Israel Institute of TechnologyHaifaIsrael

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-67020-1
  • Copyright Information The Author(s) 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-67019-5
  • Online ISBN 978-3-319-67020-1
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book