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We propose an unsupervised speech separation framework for mixtures of two unseen speakers in a single-channel setting based on deep neural networks (DNNs). We rely on a key assumption that two speakers could be well segregated if they are not too similar to each other. A dissimilarity measure between two speakers is first proposed to characterize the separation ability between competing speakers...
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