Compact microphone array processing for in-vehicle voice detection applications.
Elizabeth A. Hoppe, Michael J. Roan · The Journal of the Acoustical Society of America · 2009
The main goal of voice activity detection algorithms is to determine the presence of human voice signals in a given environment. Voice activity detection is very challenging in vehicle interiors. The main challenge in detecting the presence of voice signals in vehicles is the presence of a large number of interferers and a high background noise level. Further, many types of interferers such as tire or engine noise have signals that are highly nonstationary. In this work, compact microphone arrays mounted in various locations within a vehicle are used to extract signals from locations of interest. Experimental comparisons of the performance of several voice activity detection algorithms are made for various array configurations (including single microphone) and source extraction processing algorithms. Processing algorithms considered include blind source separation algorithms such as fastICA, transfer function based inversion methods, and both fixed and adaptive beamforming techniques. The performance of compact arrays is also compared to the performance of larger distributed microphone arrays. It is shown that the use of compact microphone arrays can significantly improve voice activity detection algorithms. The gain is quantified using receiver operating characteristic type curves plotting probability of detection vs probability of false alarm.