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As a means of speech separation, time-frequency masking applies a gain function to the timefrequency representation of noisy speech. On the other hand, nonnegative matrix factorization (NMF) addresses separation by linearly combining basis vectors from speech and noise models to approximate noisy speech. This paper presents an approach for improving the perceptual quality of speech separated from background noise at low signal-to-noise ratios. An ideal ratio mask is estimated, which separatesdoi:10.1121/1.4928612 pmid:26428778 pmcid:PMC5392055 fatcat:2ydwgowujfbh7a4f5jaziqtmva