From binaural to multimicrophone blind source separation using fixed beamforming with HRTFs

In this article, we are interested in the problem of blind source separation (BSS) for the robot audition, we study the performance of blind source separation with a varying number of sensors in a microphone array placed in the head of an infant size dummy. We propose a two stage blind source separation algorithm based on a fixed beamforming preprocessing using the head related transfer functions (HRTF) of the dummy and a separation algorithm using a sparsity criterion. We show that in the case of robot audition, the use of a multisensor array improves significantly the performance of the source separation algorithm, as compared to the binaural case, up to a limit number of microphones studied in this paper.