Impact of microphone placement errors on speech intelligibility

Arulkumaran Muthukumarasamy, Kevin D. Donohue

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

3 Scopus citations

Abstract

The speech of a person speaking in a noisy environment can be enhanced through electronic beamforming with spatially distributed microphones. The need to precisely determine microphone locations, however, can limit the application of this approach, especially where microphones must be placed quickly or changed on a regular basis. A precise calibration or measurement process can be tedious and time consuming. In order to understand acceptable limits on the calibration process, this paper examines the impact of microphone position error on the intelligibility. Microphone position error is modeled as a zero-mean uniform distribution in 3 dimensions, and analytical expressions for its impact on beamformed signal power are derived. Experimental and simulation results also are presented to show relationships between the precision of the position measurement and loss in intelligibility for a variety of microphone distributions and distracting sources (other speech and white noise). Results show that for speech near the threshold of intelligibility, microphone position errors with standard deviations less than 1.5cm, limit losses in intelligibility to within 10% of the case for zero position error.

Original languageEnglish
Title of host publicationIEEE SoutheastCon 2009, Technical Proceedings
Pages323-328
Number of pages6
DOIs
StatePublished - 2009
EventIEEE Southeastcon 2009 - Atlanta, GA, United States
Duration: Mar 5 2009Mar 8 2009

Publication series

NameConference Proceedings - IEEE SOUTHEASTCON
ISSN (Print)1091-0050
ISSN (Electronic)1558-058X

Conference

ConferenceIEEE Southeastcon 2009
Country/TerritoryUnited States
CityAtlanta, GA
Period3/5/093/8/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Signal Processing

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