Speech enhancement with a low-complexity online source number estimator using distributed arrays
Maja Taseska, Affan Hasan Khan and Emanuel A. P. Habets
Published in the Proc. of the European Signal Processing Conference (EUSIPCO), 2014.
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.
Description
Room size: 6 m x 5 m x 3 m. Three uniform circular arrays were used with diameter 2.5 cm and with three microphones each. Further details about the setup and implementation can be found in the paper.
Audio Examples
SNR 25 dB, Reverberation time 200 ms, During an onset of a new interferer:
SNR 25 dB, Reverberation time 200 ms, During triple-talk (after convergence):
SNR 15 dB, Reverberation time 350 ms, During an onset of a new interferer:
SNR 15 dB, Reverberation time 350 ms, During triple-talk (after convergence):