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A new approach to the separation of speech from speech-in-noise mixtures is the use of time-frequency (T-F) masking. Originated in the field of computational auditory scene analysis, T-F masking performs separation in the time-frequency domain. This article introduces the T-F masking concept and reviews T-F masking algorithms that separate target speech from either monaural or binaural mixtures, as well as microphone-array recordings. The review emphasizes techniques that are promising for hearing aid design. This article also surveys recent studies that evaluate the perceptual effects of T-F masking techniques, particularly their effectiveness in improving human speech recognition in noise. An assessment is made of the potential benefits of T-F masking methods for the hearing impaired in light of the processing constraints of hearing aids. Finally, several issues pertinent to T-F masking are discussed.
DeLiang Wang (Thu,) studied this question.