Speaker tracking in reverberant environments using multiple directions of arrival

Christine Evers, Boaz Rafaely, Patrick A. Naylor

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

4 Scopus citations

Abstract

Accurate estimation of the Direction of Arrival (DOA) of a sound source is an important prerequisite for a wide range of acoustic signal processing applications. However, in enclosed environments, early reflections and late reverberation often lead to localization errors. Recent work demonstrated that improved robustness against reverberation can be achieved by clustering only the DOAs from direct-path bins in the short-term Fourier transform of a speech signal of several seconds duration from a static talker. Nevertheless, for moving talkers, short blocks of at most several hundred milliseconds are required to capture the spatio-temporal variation of the source direction. Processing of short blocks of data in reverberant environment can lead to clusters whose centroids correspond to spurious DOAs away from the source direction. We therefore propose in this paper a novel multi-detection source tracking approach that estimates the smoothed trajectory of the source DOAs. Results for realistic room simulations validate the proposed approach and demonstrate significant improvements in estimation accuracy compared to single-detection tracking.

Original languageEnglish
Title of host publication2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages91-95
Number of pages5
ISBN (Electronic)9781509059256
DOIs
StatePublished - 10 Apr 2017
Event2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - San Francisco, United States
Duration: 1 Mar 20173 Mar 2017

Publication series

Name2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings

Conference

Conference2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017
Country/TerritoryUnited States
CitySan Francisco
Period1/03/173/03/17

Keywords

  • Bayes methods
  • Direction-of-arrival estimation
  • Motion estimation
  • Speech processing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Acoustics and Ultrasonics
  • Instrumentation
  • Communication

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