835496
doi
10.1109/TASLP.2017.2718733
oai:zenodo.org:835496
Pavlidi Despoina
FORTH-ICS
Mouchtaris Athanasios
FORTH-ICS
Perpendicular Cross-Spectra Fusion for Sound Source Localization with a Planar Microphone Array
Stefanakis Nikolaos
FORTH-ICS
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Direction of arrival estimation, multiple source localization, source counting, information fusion
<p>Multiple sound source localization in reverberant environments stands as one of the most difficult challenges for many applications related to microphone array signal processing. In this paper, we describe Perpendicular Cross-Spectra Fusion (PCSF), a new Direction of Arrival (DOA) estimation algorithm which utilizes an analytic formula for direction estimation in the time-frequency (TF) domain. Inherent to this technique is the presence of multiple direction estimation subsystems which operate in parallel, producing a multiplicity of candidate DOAs at each TF point. We define a metric of coherence based on the property of divergence of the different DOA estimators, for assessing the reliability of different signal portions, so that only TF bins with a high quality of directional information are exploited for local DOA estimation. The resulting collection of local DOAs is provided as input to a recently proposed histogram processing approach which is based on matching pursuit. Results based on simulation and real recordings illustrate the advantages of PCSF compared to other DOA estimation techniques subjected to the same histogram based processing, in the context of real-time multiple source localization and counting; improved performance in reverberant conditions and high tolerance to diffuse and common mode noise.</p>
Zenodo
2017-07-27
info:eu-repo/semantics/article
835495
award_title=Hands-free Voice-enabled Interface to Web Applications for Smart Home Environments; award_number=644283; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/644283; funder_id=00k4n6c32; funder_name=European Commission;
1579542177.929134
1224134
md5:e62fcf4c733a01cef4d64e3ecd76af12
https://zenodo.org/records/835496/files/IEEE2016_final.pdf
public
IEEE/ACM Transactions on Audio, Speech, and Language Processing
22
9
1517 - 1531
2017-07-27