Distributed Expectation-Maximization Algorithm for Speaker Localization in Reverberant Environments

Yuval Dorfan, Axel Plinge, Gershon Hazan, Sharon Gannot

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Localization of acoustic sources has attracted a considerable amount of research attention in recent years. A major obstacle to achieving high localization accuracy is the presence of reverberation, the influence of which obviously increases with the number of active speakers in the room. Human hearing is capable of localizing acoustic sources even in extreme conditions. In this study, we propose to combine a method based on human hearing mechanisms and a modified incremental distributed expectation-maximization (IDEM) algorithm. Rather than using phase difference measurements that are modeled by a mixture of complex-valued Gaussians, as proposed in the original IDEM framework, we propose to use time difference of arrival measurements in multiple subbands and model them by a mixture of real-valued truncated Gaussians. Moreover, we propose to first filter the measurements in order to reduce the effect of the multipath conditions. The proposed method is evaluated using both simulated data and real-life recordings.

Original languageEnglish
Article number8241767
Pages (from-to)682-695
Number of pages14
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume26
Issue number3
DOIs
StatePublished - Mar 2018

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Precedence effect
  • auditory scene analysis
  • distributed expectation-maximization
  • incremental expectation-maximization
  • multi-path
  • onset dominance
  • sound source localization
  • spectral masking
  • time difference of arrival
  • truncated Gaussian

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