4 papers
Label-free Knowledge Distillation with Contrastive Loss for Light-weight Speaker Recognition
Zhiyuan Peng, Xuanji He, Ke Ding +2
Very deep models for speaker recognition (SR) have demonstrated remarkable performance improvement in recent research. However, it is impractical to deploy these models for on-devi…
Covariance Regularization for Probabilistic Linear Discriminant Analysis
Zhiyuan Peng, Mingjie Shao, Xuanji He +4
Probabilistic linear discriminant analysis (PLDA) is commonly used in speaker verification systems to score the similarity of speaker embeddings. Recent studies improved the perfor…
Unifying Cosine and PLDA Back-ends for Speaker Verification
Zhiyuan Peng, Xuanji He, Ke Ding +2
State-of-art speaker verification (SV) systems use a back-end model to score the similarity of speaker embeddings extracted from a neural network model. The commonly used back-end…
Learning Speaker Embedding with Momentum Contrast
Ke Ding, Xuanji He, Guanglu Wan
Speaker verification can be formulated as a representation learning task, where speaker-discriminative embeddings are extracted from utterances of variable lengths. Momentum Contra…