Normalized, HOS-based, blind speech separation algorithms

Techniques for blind separation of mixed speech signals (co-channel speech) have been reported in the literature. One computationally simple method for linear mixtures (suitable for real-time separation), employs a gradient search algorithm to maximize the kurtosis of the outputs (hopefully separated speech signals). We report the results of an enhancement to the algorithm which involves a normalization to the correction matrix used in the update of the separation matrix. Simulation results (using the TIMIT speech corpus) generally indicate improved (sometimes significantly) separation quality, a higher probability in producing distinct source outputs, and robustness in noisy cases.