A bayesian direction-of-arrival model for an undetermined number of sources using a two-microphone array

Abstract

Sound source localization using a two-microphone array is an active area of research, with considerable potential for use with video conferencing, mobile devices, and robotics. Based on the observed time-differences of arrival between sound signals, a probability distribution of the location of the sources is considered to estimate the actual source positions. However, these algorithms assume a given number of sound sources. This paper describes an updated research account on the solution presented in Escolano et al. [J. Acoust. Am. Soc. 132(3), 1257-1260 (2012)], where nested sampling is used to explore a probability distribution of the source position using a Laplacian mixture model, which allows both the number and position of speech sources to be inferred. This paper presents different experimental setups and scenarios to demonstrate the viability of the proposed method, which is compared with some of the most popular sampling methods, demonstrating that nested sampling is an accurate tool for speech localization. (C) 2014 Acoustical Society of America.