Blind sampling rate offset estimation and compensation in wireless acoustic sensor networks with application to beamforming

Shmulik Markovich-Golan, Sharon Gannot, Israel Cohen

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

Abstract

Beamforming methods for speech enhancement in wireless acoustic sensor networks (WASNs) have recently attracted the attention of the research community. One of the major obstacles in implementing speech processing algorithms in WASN is the sampling rate offsets between the nodes. As nodes utilize individual clock sources, sampling rate offsets are inevitable and may cause severe performance degradation. In this paper, a blind procedure for estimating the sampling rate offsets is derived. The procedure is applicable to speech-absent time segments with slow time-varying interference statistics. The proposed procedure is based on the phase drift of the coherence between two signals sampled at different sampling rates. Resampling the signals with Lagrange polynomials interpolation method compensates for the sampling rate offsets. An extensive experimental study, utilizing the transfer function generalized sidelobe canceller (TFGSC), exemplifies the problem and its solution.

Original languageEnglish
Title of host publicationInternational Workshop on Acoustic Signal Enhancement, IWAENC 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783800734511
StatePublished - 2012
EventInternational Workshop on Acoustic Signal Enhancement, IWAENC 2012 - Aachen, Germany
Duration: 4 Sep 20126 Sep 2012

Publication series

NameInternational Workshop on Acoustic Signal Enhancement, IWAENC 2012

Conference

ConferenceInternational Workshop on Acoustic Signal Enhancement, IWAENC 2012
Country/TerritoryGermany
CityAachen
Period4/09/126/09/12

Keywords

  • Beamforming
  • Synchronization
  • WASN

All Science Journal Classification (ASJC) codes

  • Software
  • Acoustics and Ultrasonics
  • Computer Networks and Communications
  • Signal Processing

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