@inproceedings{7888a949f05746e79c0e281f3bd7d079,
title = "Multiple acoustic sources localization using distributed expectation-maximization algorithm",
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.",
author = "Yuval Dorfan and Gershon Hazan and Sharon Gannot",
year = "2014",
doi = "https://doi.org/10.1109/HSCMA.2014.6843254",
language = "الإنجليزيّة",
isbn = "9781479931095",
series = "2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014",
publisher = "IEEE Computer Society",
pages = "72--76",
booktitle = "2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014",
address = "الولايات المتّحدة",
note = "2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014 ; Conference date: 12-05-2014 Through 14-05-2014",
}