Deep clustering: Discriminative embeddings for segmentation and separation

Short summary

A deep learning framework called deep clustering uses contrastive embeddings to segment and separate audio sources, achieving 6dB improvement in signal quality for two-speaker mixtures and performing surprisingly well on three-speaker mixtures.

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