This work addresses the problem of audio source localization in multiple speakers indoor scenarios. Three different direction of arrival (DOA)algorithms are applied to measure the angular position of the primary audio source with respect to a reference microphone, then a fuzzy logic-based method is applied to fuse the crisp measurements. The model-free estimation capability of the fuzzy logic enables to gain a good degree of precision keeping low the computational complexity of the system. This two level audio source localization system approach is robust and reliable because each module operates independently from the other, and the fuzzy logic inferential engine has the capability to evaluate qualitatively the performance of each of the DOA measurement subsystems.

Audio data fuzzy fusion for source localization / M. Malcangi - In: Engineering applications of neural networks : 14th international conference, EANN 2013, Halkidiki, Greece, september 13-16, 2013 : proceedings, part I CCIS 383 / [a cura di] L. Iliadis, H. Papadopoulos, C. Jayne. - Heidelberg : Springer, 2013. - ISBN 9783642410123. - pp. 323-329 (( Intervento presentato al 14. convegno International Conference on Engineering Applications of Neural Networks tenutosi a Halkidiki, Greece nel 2013 [10.1007/978-3-642-41013-0_33].

Audio data fuzzy fusion for source localization

M. Malcangi
Primo
2013

Abstract

This work addresses the problem of audio source localization in multiple speakers indoor scenarios. Three different direction of arrival (DOA)algorithms are applied to measure the angular position of the primary audio source with respect to a reference microphone, then a fuzzy logic-based method is applied to fuse the crisp measurements. The model-free estimation capability of the fuzzy logic enables to gain a good degree of precision keeping low the computational complexity of the system. This two level audio source localization system approach is robust and reliable because each module operates independently from the other, and the fuzzy logic inferential engine has the capability to evaluate qualitatively the performance of each of the DOA measurement subsystems.
Fuzzy logic data fusion ; audio source localization ; direction of arrival ; audio beamforming
Settore INF/01 - Informatica
International Neural Networks Society
Aristotle University of Tessaloniki
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/225684
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