Volume 135, Issue 2, February 2014
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
Sound reproduction in personal audio systems using the least-squares approach with acoustic contrast control constraint135(2014); http://dx.doi.org/10.1121/1.4861341View Description Hide Description
This paper describes a method for focusing the reproduced sound in the bright zone without disturbing other people in the dark zone in personal audio systems. The proposed method combines the least-squares and acoustic contrast criteria. A constrained parameter is introduced to tune the balance between two performance indices, namely, the acoustic contrast and the spatial average error. An efficient implementation of this method using convex optimization is presented. Offline simulations and real-time experiments using a linear loudspeaker array are conducted to evaluate the performance of the presented method. Results show that compared with the traditional acoustic contrast control method, the proposed method can improve the flatness of response in the bright zone by sacrificing the level of acoustic contrast.
A Bayesian direction-of-arrival model for an undetermined number of sources using a two-microphone array135(2014); http://dx.doi.org/10.1121/1.4861356View Description Hide Description
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.