TY - GEN
T1 - Multiple acoustic sources localization using distributed expectation-maximization algorithm
AU - Dorfan, Yuval
AU - Hazan, Gershon
AU - Gannot, Sharon
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84904458583&partnerID=8YFLogxK
U2 - 10.1109/hscma.2014.6843254
DO - 10.1109/hscma.2014.6843254
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AN - SCOPUS:84904458583
SN - 9781479931095
T3 - 2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014
SP - 72
EP - 76
BT - 2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014
PB - IEEE Computer Society
T2 - 2014 4th Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, HSCMA 2014
Y2 - 12 May 2014 through 14 May 2014
ER -