LPC-based speech dereverberation using Kalman-EM algorithm

Boaz Schwartz, Sharon Gannot, Emanuel A.P. Habets

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

An algorithm for multichannel speech dereverberation is proposed that simultaneously estimates the clean signal, the linear prediction (LP) parameters of speech, and the acoustic parameters of the room. The received signals are processed in short segments to reduce the algorithm latency, and several expectation-maximization (EM) iterations are carried out on each segment to improve the signal estimation. In the expectation step, the fixed-lag Kalman smoother (FLKS) is applied to extract the clean signal from the data utilizing the estimated parameters. In the maximization step, the LP and room pa-rameters are updated using the output of the FLKS. Experimental results show that multiple EM iterations and the application of the LP model improve the quality of the output signal.

Original languageEnglish
Title of host publication2014 14th International Workshop on Acoustic Signal Enhancement, IWAENC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-34
Number of pages5
ISBN (Electronic)9781479968084
DOIs
StatePublished - 11 Nov 2014
Event2014 14th International Workshop on Acoustic Signal Enhancement, IWAENC 2014 - Juan-les-Pins, France
Duration: 8 Sep 201411 Sep 2014

Publication series

Name2014 14th International Workshop on Acoustic Signal Enhancement, IWAENC 2014

Conference

Conference2014 14th International Workshop on Acoustic Signal Enhancement, IWAENC 2014
Country/TerritoryFrance
CityJuan-les-Pins
Period8/09/1411/09/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Acoustics
  • Conferences
  • Kalman filters
  • Noise
  • Speech
  • Speech enhancement

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