title: Convolutive Transfer Function Invariant SDR training criteria for\n Multi-Channel Reverberant Speech Separation
abstract: Time-domain training criteria have proven to be very effective for the\nseparation of single-channel non-reverberant speech mixtures. Likewise,\nmask-based beamforming has shown impressive performance in multi-channel\nreverberant speech enhancement and source separation. Here, we propose to\ncombine neural network supported multi-channel source separation with a\ntime-domain training objective function. For the objective we propose to use a\nconvolutive transfer function invariant Signal-to-Dis
journal: arXiv (Cornell University)