Robust and Fast Localization of Single Speech Source Using a Planar Array

Abstract

Heavy computational load and acoustic interferences are two major problems to speech source localization in real applications. Conventional methods can mitigate one problem, but deteriorate the other. This letter proposes an algorithm of direction-of-arrival (DOA) estimation, which is both computationally efficient and robust in the presence of acoustic interferences. The robustness is considered in two aspects. One is the eigenanalysis-based enhancement to reduce acoustic interferences such as noise and reverberation. The other is the coefficients that weight the pairwise time delays to mitigate the effect of delay outliers on DOA. The high computational efficiency is achieved by making use of a concave cost function, from which, the optimal estimate of DOA is given by a closed-form solution. The grid-search method often adopted in conventional algorithms is no longer used in this algorithm. We conduct some experiments in both simulated and real environments with a 9-element circular array. The proposed algorithm runs about ten times faster than Steered Response Power PHAse Transform (SRP-PHAT), and outperforms SRP-PHAT in terms of robustness.