Speech Enhancement in the STFT Domain

  • Jacob Benesty
  • Jingdong Chen
  • Emanuël A.P. Habets

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

Table of contents

  1. Front Matter
    Pages i-vii
  2. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 1-13
  3. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 15-28
  4. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 29-49
  5. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 51-75
  6. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 77-92
  7. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 93-101
  8. Jacob Benesty, Jingdong Chen, Emanuël A. P. Habets
    Pages 103-106
  9. Back Matter
    Pages 107-109

About this book

Introduction

This work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain.
The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.

Keywords

Speech enhancement Wiener filter linearly constrained minimum variance (LCMV) filter maximum signal-to-noise ratio (SNR) filter microphone arrays minimum variance distortionless response (MVDR) filter prediction filter short-time Fourier transform (STFT) domain single-channel and multichannel tradeoff filter

Authors and affiliations

  • Jacob Benesty
    • 1
  • Jingdong Chen
    • 2
  • Emanuël A.P. Habets
    • 3
  1. 1., University of QuebecINRS-EMTMontrealCanada
  2. 2.Northwestern Polytechnical UniversityXi'anChina, People's Republic
  3. 3., International Audio LaboratoriesUniveristy of Erlangen-NurembergErlangenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-23250-3
  • Copyright Information The Author(s) 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-23249-7
  • Online ISBN 978-3-642-23250-3
  • About this book