Learning Speaker Embedding with Momentum Contrast

7 Jan 2020Ke DingXuanji HeGuanglu Wan

Speaker verification can be formulated as a representation learning task, where speaker-discriminative embeddings are extracted from utterances of variable lengths. Momentum Contrast (MoCo) is a recently proposed unsupervised representation learning framework, and has shown its effectiveness for learning good feature representation for downstream vision tasks... (read more)

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