A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation

Sharon Gannot, Emmanuel Vincent, Shmulik Markovich-Golan, Alexey Ozerov

Research output: Contribution to journalReview articlepeer-review

387 Scopus citations


Speech enhancement and separation are core problems in audio signal processing, with commercial applications in devices as diverse as mobile phones, conference call systems, hands-free systems, or hearing aids. In addition, they are crucial preprocessing steps for noise-robust automatic speech and speaker recognition. Many devices now have two to eight microphones. The enhancement and separation capabilities offered by these multichannel interfaces are usually greater than those of single-channel interfaces. Research in speech enhancement and separation has followed two convergent paths, starting with microphone array processing and blind source separation, respectively. These communities are now strongly interrelated and routinely borrow ideas from each other. Yet, a comprehensive overview of the common foundations and the differences between these approaches is lacking at present. In this paper, we propose to fill this gap by analyzing a large number of established and recent techniques according to four transverse axes: 1) the acoustic impulse response model, 2) the spatial filter design criterion, 3) the parameter estimation algorithm, and 4) optional postfiltering. We conclude this overview paper by providing a list of software and data resources and by discussing perspectives and future trends in the field.

Original languageEnglish
Pages (from-to)692-730
Number of pages39
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Issue number4
StatePublished - Apr 2017

Bibliographical note

Publisher Copyright:
© 2014 IEEE.


  • Array processing
  • Beamforming
  • Expectation-maximization
  • Independent component analysis
  • Multichannel
  • Postfiltering
  • Sparse component analysis
  • Wiener filter


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