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This paper presents a novel algorithm for learning a hierarchical dictionary in the short-time Fourier (STFT) domain, which can improve the performance of dictionary learning (DL) based single-channel speech separation (SCSS). The goal of SCSS is to separate the underlying clean speeches from a signal mixture, which was often achieved by learning a pair of discriminative sub-dictionaries and sparsely...
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