A small dodecahedral microphone array for blind source separation

Abstract

A sound source separation method based on frequency-domain independent component analysis (FD-ICA) is proposed. This method fully utilizes the dodecahedral microphone array (DHMA), which has several merits: 1) the size of the array is very small and thus easy to handle; 2) the amplitude difference among microphones on the different surfaces is large; and 3) it is less affected by spatial aliasing in the higher frequency region. In the proposed method, in order to solve the permutation problem in FD-ICA through clustering acoustic transfer functions, amplitude and phase differences are optimally combined as a function of frequency. A DHMA of 8 cm in diameter with 60 microphones is used for the experiment, where up to twelve sound sources (speech/musical instruments) are separated using the proposed algorithm. The separation performance of the proposed method attains 24 dB in the signal-to-interference ratio (SIR) improvement score for the case of twelve sources. Since the performance is better by up to 10 dB in comparison to the conventional method, our results confirm the effectiveness of the proposed method.