8 citations · 11 across the 8 of their papers we have counts for
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Contrastive Speaker Embedding With Sequential Disentanglement
Youzhi Tu, Man-Wai Mak, Jen-Tzung Chien
Contrastive speaker embedding assumes that the contrast between the positive and negative pairs of speech segments is attributed to speaker identity only. However, this assumption…
Asymmetric Clean Segments-Guided Self-Supervised Learning for Robust Speaker Verification
Chong-Xin Gan, Man-Wai Mak, Weiwei Lin +1
Contrastive self-supervised learning (CSL) for speaker verification (SV) has drawn increasing interest recently due to its ability to exploit unlabeled data. Performing data augmen…
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.…
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…