Mutual Information based Channel Selection for Speaker Diarization of Meetings Data

In the meeting case scenario, audio is often recorded using Multiple Distance Microphones (MDM) in a non-intrusive manner. Typically a beamforming is performed in order to obtain a single enhanced signal out of the multiple channels. This paper investigates the use of mutual information for selecting the channel subset that produces the lowest error in a diarization system. Conventional systems perform channel selection on the basis of signal properties such as SNR, cross correlation. In this paper, we propose the use of a mutual information measure that is directly related to the objective function of the diarization system. The proposed algorithms are evaluated on the NIST RT 06 eval dataset. Channel selection improves the speaker error by 1.1% absolute (6.5% relative) w.r.t. the use of all channels.