Multi-channel audio segmentation for continuous observation and archival of large spaces

Gordon Wichern, Harvey Thornburg, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In most real-world situations, a single microphone is insuffi-cient for the characterization of an entire auditory scene. This often occurs in places such as office environments which consist of several interconnected spaces that are at least partially acoustically isolated from one another. To this end, we extend our previous work on segmentation of natural sounds to perform scene characterization using a sparse array of microphones, strategically placed to ensure that all parts of the environment are within range of at least one microphone. By accounting for which microphones are active for a given sound event, we perform a multi-channel segmentation that captures sound events occurring in any part of the space. The segmentation is inferred from a custom dynamic Bayesian network (DBN) that models how event boundaries influence changes in audio features. Example recordings illustrate the utility of our approach in a noisy office environment.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages237-240
Number of pages4
ISBN (Print)9781424423545
DOIs
StatePublished - Jan 1 2009
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: Apr 19 2009Apr 24 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/TerritoryTaiwan, Province of China
CityTaipei
Period4/19/094/24/09

Keywords

  • Acoustic arrays
  • Acoustic signal analysis
  • Acoustic signal detection
  • Bayes procedures

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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