An approach to prevent adaptive beamformers from cancelling the desired signal
Tofigh Naghibi, Beat Pfister · 2012
Under real conditions, severe signal cancellation often occurs in adaptive beamformers because of reverberation, microphone transfer function mismatch or steering vector error. Therefore, usually voice activity information is necessary to pause the beamformer update during the speech activity. However, this information is not available or not sufficiently accurate in most applications. Here we propose a new algorithm in order to mitigate the signal cancellation effect. The algorithm extracts the desired source-to-microphones transfer functions from the data covariance matrix by using rough estimates of some source locations. We show that it is robust against reverberation, microphone mismatch and imprecisely estimated target direction.