A robust method to count and locate audio sources in a multichannel underdetermined mixture

We propose a method to count and estimate the mixing directions in an underdetermined multichannel mixture. The approach is based on the hypothesis that in the neighbourhood of some time-frequency points, only one source essentially contributes to the mixture: such time-frequency points can provide robust local estimates of the corresponding source direction. At the core of our contribution is a statistical model to exploit a local confidence measure which detects the timefrequency regions where such robust information is available. A clustering algorithm called DEMIX is proposed to merge the information from all time-frequency regions according to their confidence level. So as to estimate the delays of anechoic mixtures and overcome the intrinsic ambiguities of phase unwrapping as met with DUET, we propose a technique similar to GCC-PHAT which is able to estimate delays that can largely exceed one sample. We propose an extensive experimental study which shows that the resulting method...

• Type: Journal
• Year: 2010
• Where: TSP
• Authors: Simon Arberet, Rémi Gribonval, Frédéric Bimbot
• Keywords: Artificial Intelligence, Robust, Source Directions, Time-frequency Points, TSP 2010