In this section
@article{Hafezi:2021:10.1121/10.0004214,
author = {Hafezi, S and Moore, A and Naylor, P},
doi = {10.1121/10.0004214},
journal = {Journal of the Acoustical Society of America},
title = {Narrowband multi-source Direction-of-Arrival estimation in the spherical harmonic domain},
url = {http://dx.doi.org/10.1121/10.0004214},
volume = {149},
year = {2021}
}
TY - JOUR
AB - A conventional approach to wideband multi-source (MS) direction-of-arrival (DOA) estimation is to perform single source (SS) DOA estimation in time-frequency (TF) bins for which a SS assumption is valid. Such methods use the W-disjoint orthogonality (WDO) assumption due to the speech sparseness. As the number of sources increases, the chance of violating the WDO assumption increases. As shown in the challenging scenarios with multiple simultaneously active sources over a short period of time masking each other, it is possible for a strongly masked source (due to inconsistency of activity or quietness) to be rarely dominant in a TF bin. SS-based DOA estimators fail in the detection or accurate localization of masked sources in such scenarios. Two analytical approaches are proposed for narrowband DOA estimation based on the MS assumption in a bin in the spherical harmonic domain. In the first approach, eigenvalue decomposition is used to decompose a MS scenario into multiple SS scenarios, and a SS-based analytical DOA estimation is performed on each. The second approach analytically estimates two DOAs per bin assuming the presence of two active sources per bin. The evaluation validates the improvement to double accuracy and robustness to sensor noise compared to the baseline methods.
AU - Hafezi,S
AU - Moore,A
AU - Naylor,P
DO - 10.1121/10.0004214
PY - 2021///
SN - 0001-4966
TI - Narrowband multi-source Direction-of-Arrival estimation in the spherical harmonic domain
T2 - Journal of the Acoustical Society of America
UR - http://dx.doi.org/10.1121/10.0004214
UR - http://hdl.handle.net/10044/1/89097
VL - 149
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom