Source localization for multiple speech sources using low complexity non-parametric source separation and clustering

Authors:
M. Swartling;B. Sällberg;N. Grbić
Affiliations:
Department of Electrical Engineering, Blekinge Institute of Technology, SE-371 79 Karlskrona, Sweden;Department of Electrical Engineering, Blekinge Institute of Technology, SE-371 79 Karlskrona, Sweden;Department of Electrical Engineering, Blekinge Institute of Technology, SE-371 79 Karlskrona, Sweden
Venue:
Signal Processing
Year:
2011

Citing 3
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Abstract

This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application.