Mixtures of Gamma Priors for Non-Negative Matrix Factorization Based Speech Separation

These audio examples demonstrate the performance of the algorithm to be presented at the ICA 2009 conference. Here, a model for male speakers and a model for female speakers was trained without using the test speakers. The mixtures were separated using the proposed method with 30 spectrum vectors, with and without adaptation of the vectors. The signals were generated by mixing random sentences from the GRID corpus.

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