Auditory scene analysis by time-delay analysis with three microphones

We propose two methods for the disambiguation of results in time-delay based detection and localization of sound sources, when a triangle of microphones is applied for signal acquisition. A standard approach is to create histograms of time differences of arrival (TDOA) for each microphone pair in a triangular array and to create an averaged histogram. But each individual histogram is designed to detect unique orientation of source only within the local range of [-π/2, π/2]. Hence, taking the average for different pairs is not appropriate and such method suffers from ambiguity of results in the full range of orientations: [0, 2π]. Our first proposition is a delay vector transformation method, that combines corresponding delay measurements into vectors and transforms them into a 2-D space in which a full-range orientation histogram can finally be established and analyzed. In our second method, individual orientation histograms obtained for pairs of microphones are analyzed first and for each detected source two competitive hypotheses are created. Due to a final clustering of the hypothesis set a unique orientation of each source can be estimated.