Multimicrophone MMSE-based speech source separation

Shmulik Markovich-Golan, Israel Cohen, Sharon Gannot

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Beamforming methods using a microphone array successfully utilize spatial diversity for speech separation and noise reduction. Adaptive design of the beamformer based on various minimum mean squared error (MMSE) criteria significantly improves performance compared to fixed, and data-independent design. These criteria differ in their considerations to noise minimization and desired speech distortion. Three common data-dependent beamformers, namely, matched filter (MF), MWF and LCMV are presented and analyzed. Estimation methods for implementing the various beamformers are surveyed. Simple examples of applying the various beamformers to simulated narrowband signals in an anechoic environment and to speech signals in a real-life reverberant environment are presented and discussed.

Original languageEnglish
Title of host publicationSignals and Communication Technology
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages31
StatePublished - 2018

Publication series

NameSignals and Communication Technology
ISSN (Print)1860-4862
ISSN (Electronic)1860-4870

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2018.


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