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Speech enhancement with a low-complexity online source number estimator using distributed arrays

 
: Taseska, Maja; Khan, Affan-Hassan; Habets, Emanuël A.P.

Institute of Electrical and Electronics Engineers -IEEE-; European Association for Speech, Signal and Image Processing -EURASIP-:
22nd European Signal Processing Conference, EUSIPCO 2014. Proceedings. Vol.2 : Lisbon, Portugal, 1-5 September 2014
Piscataway, NJ: IEEE, 2014
ISBN: 978-0-9928626-1-9
ISBN: 978-1-4799-4603-7
pp.929-933
European Signal Processing Conference (EUSIPCO) <22, 2014, Lisbon, Portugal>
English
Conference Paper
Fraunhofer IIS ()

Abstract
Enhancement of a desired speech signal in the presence of background noise and interferers is required in various modern communication systems. Existing multichannel techniques often require that the number of sources and their locations are known in advance, which makes them inapplicable in many practical situations. We propose a framework which uses the microphones of distributed arrays to enhance a desired speech signal by reducing background noise and an initially unknown number of interferers. The desired signal is extracted by a minimum variance distortionless response filter in dynamic scenarios where the number of active interferers is time-varying. An efficient, geometry-based approach that estimates the number of active interferers and their locations online is proposed. The overall performance is compared to the one of a geometry-based probabilistic framework for source extraction, recently proposed by the authors.

: http://publica.fraunhofer.de/documents/N-330241.html