@inproceedings{ea2fdf69c36d49b28c5381fb8796db60,
title = "DOA estimation in noisy environment with unknown noise power using the em algorithm",
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.",
keywords = "DOA estimation, Expectation-maximization (EM), Maximum-likelihood",
author = "Ofer Schwartz and Yuval Dorfan and Maja Taseska and Habets, {Emanuel A.P.} and Sharon Gannot",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 ; Conference date: 01-03-2017 Through 03-03-2017",
year = "2017",
month = apr,
day = "10",
doi = "10.1109/hscma.2017.7895567",
language = "الإنجليزيّة",
series = "2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "86--90",
booktitle = "2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings",
address = "الولايات المتّحدة",
}