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

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.