An Online Multiple-speaker DOA Tracking Using the CappÉ-Moulines Recursive Expectation-maximization Algorithm

Koby Weisberg, Sharon Gannot, Ofer Schwartz

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

17 Scopus citations

Abstract

In this paper, we present a multiple-speaker direction of arrival (DOA) tracking algorithm with a microphone array that utilizes the recursive EM (REM) algorithm proposed by Cappé and Moulines. In our model, all sources can be located in one of a predefined set of candidate DOAs. Accordingly, the received signals from all microphones are modeled as Mixture of Gaussians (MoG) vectors in which each speaker is associated with a corresponding Gaussian. The localization task is then formulated as a maximum likelihood (ML) problem, where the MoG weights and the power spectral density (PSD) of the speakers are the unknown parameters. The REM algorithm is then utilized to estimate the ML parameters in an online manner, facilitating multiple source tracking. By using Fisher-Neyman factorization, the outputs of the minimum variance distortionless response (MVDR)-beamformer (BF) are shown to be sufficient statistics for estimating the parameters of the problem at hand. With that, the terms for the E-step are significantly simplified to a scalar form. An experimental study demonstrates the benefits of the using proposed algorithm in both a simulated data-set and real recordings from the acoustic source localization and tracking (LOCATA) data-set.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages656-660
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 12 May 201917 May 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period12/05/1917/05/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • LOCATA challenge
  • Recursive expectation-maximization
  • Speaker tracking

Fingerprint

Dive into the research topics of 'An Online Multiple-speaker DOA Tracking Using the CappÉ-Moulines Recursive Expectation-maximization Algorithm'. Together they form a unique fingerprint.

Cite this