Multiple acoustic sources localization using distributed expectation-maximization algorithm

Yuval Dorfan, Gershon Hazan, Sharon Gannot

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

Abstract

The challenge of localizing number of concurrent acoustic sources in reverberant enclosures is addressed in this paper. We formulate the localization task as a maximum likelihood (ML) parameter estimation problem, and develop a distributed expectation-maximization (DEM) procedure, based on the Incremental EM (IEM) framework. The algorithm enables localization of the speakers without a center point. Unlike direction search, localization is a distributed task in nature, since the sensors must be spatially deployed. Taking advantage of the distributed constellation of the sensors we propose a distributed algorithm that enables multiple processing nodes and considers communication constraints between them. The proposed DEM has surprising advantages over conventional expectation-maximization (EM) schemes. Firstly, it is less sensitive to initial conditions. Secondly, it converges much faster than the conventional EM. The proposed algorithm is tested by an extensive simulation study.

Original languageEnglish
Title of host publication2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014
PublisherIEEE Computer Society
Pages72-76
Number of pages5
ISBN (Print)9781479931095
DOIs
StatePublished - 2014
Event2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014 - Villers-les-Nancy, France
Duration: 12 May 201414 May 2014

Publication series

Name2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014

Conference

Conference2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014
Country/TerritoryFrance
CityVillers-les-Nancy
Period12/05/1414/05/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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