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DOA estimation in noisy environment with unknown noise power using the EM algorithm

 
: Schwartz, Ofer; Dorfan, Yuval; Taseska, Maja; Habets, Emanuël A.P.; Gannot, Sharon

:

Bellegarda, J. ; IEEE Signal Processing Society:
Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017. Proceedings : March 1-3, 2017, San Francisco, California, U.S.A.
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-5925-6
ISBN: 978-1-5090-5924-9
ISBN: 978-1-5090-5926-3
S.86-90
Workshop on Hands-Free Speech Communication and Microphone Arrays (HSCMA) <5, 2017, San Francisco/Calif.>
Englisch
Konferenzbeitrag
Fraunhofer IIS ()
audio

Abstract
A direction of arrival (DOA) estimator for concurrent speakers in a noisy environment with unknown noise power is presented. Spatially colored noise, if not properly addressed, is known to degrade the performance of DOA estimators. In our contribution, the DOA estimation task is formulated as a maximum likelihood (ML) problem, which is solved using the expectation-maximization (EM) procedure. The received microphone signals are modelled as a sum of the speech and noise components. The noise power spectral density (PSD) matrix is modelled by a time-invariant full-rank coherence matrix multiplied by the noise power. The PSDs of the speech and noise components are estimated as part of the EM procedure. The benefit of the presented algorithm in a simulated noisy environment using measured room impulse responses is demonstrated.

: http://publica.fraunhofer.de/dokumente/N-484096.html