  Microphone array post-filters have demonstrated their ability to greatly
reduce noise at the output of a beamformer. However, current techniques only
consider a single source of interest, most of the time assuming stationary
background noise. We propose a microphone array post-filter that enhances the
signals produced by the separation of simultaneous sources using common source
separation algorithms. Our method is based on a loudness-domain optimal
spectral estimator and on the assumption that the noise can be described as the
sum of a stationary component and of a transient component that is due to
leakage between the channels of the initial source separation algorithm. The
system is evaluated in the context of mobile robotics and is shown to produce
better results than current post-filtering techniques, greatly reducing
interference while causing little distortion to the signal of interest, even at
very low SNR.
