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.
|Title of host publication||2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|State||Published - 10 Apr 2017|
|Event||2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - San Francisco, United States|
Duration: 1 Mar 2017 → 3 Mar 2017
|Name||2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017 - Proceedings|
|Conference||2017 Hands-Free Speech Communications and Microphone Arrays, HSCMA 2017|
|Period||1/03/17 → 3/03/17|
Bibliographical notePublisher Copyright:
© 2017 IEEE.
- DOA estimation
- Expectation-maximization (EM)