62 citations · 117 across the 10 of their papers we have counts for
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eess.AS2022
Speaker Representation Learning via Contrastive Loss with Maximal Speaker Separability
Zhe Li, Man-Wai Mak
A great challenge in speaker representation learning using deep models is to design learning objectives that can enhance the discrimination of unseen speakers under unseen domains.…
eess.AS2022
Discriminative Speaker Representation via Contrastive Learning with Class-Aware Attention in Angular Space
Zhe Li, Man-Wai Mak, Helen Mei-Ling Meng
The challenges in applying contrastive learning to speaker verification (SV) are that the softmax-based contrastive loss lacks discriminative power and that the hard negative pairs…
cs.CV2022★ 5 cited
Masked Generative Distillation
Zhendong Yang, Zhe Li, Mingqi Shao +3
Knowledge distillation has been applied to various tasks successfully. The current distillation algorithm usually improves students' performance by imitating the output of the teac…