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Sparse deep neural networks (SDNNs) for speaker segmentation are proposed. First, the SDNNs are trained using the side information that is the class label of the input. Then, speaker-specific features are extracted from the super-vector feature of the speech signal by the SDNNs. Lastly, the label of each speech frame is obtained by K-means clustering, which is used to segment different speakers of...
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