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A second-order-statistics-based solution for online multichannel noise tracking and reduction

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We propose a second-order-statistics-based approach to online multichannel noise tracking and reduction. We combine the multichannel speech presence probability (MC-SPP) that we proposed in [1] with an alternative formulation of the minima-controlled recursive averaging (MCRA) technique that we generalize from the single- to the multichannel case. Then, we demonstrate the effectiveness of the proposed MC-SPP and multichannel noise estimator by integrating them into variants of the multichannel noise-reduction Wiener filter.

Original languageEnglish
Title of host publicationConference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
PublisherIEEE Computer Society
Pages1410-1414
Number of pages5
ISBN (Print)9781424497218
DOIs
StatePublished - 2010

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Keywords

  • Microphone array
  • minima controlled recursive averaging (MCRA)
  • multichannel noise reduction
  • multichannel speech presence probability (MC-SPP)
  • noise estimation

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