10 citations · 16 across the 5 of their papers we have counts for
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eess.AS2022★ 10 cited
Contrastive-mixup learning for improved speaker verification
Xin Zhang, Minho Jin, Roger Cheng +3
This paper proposes a novel formulation of prototypical loss with mixup for speaker verification. Mixup is a simple yet efficient data augmentation technique that fabricates a weig…
cs.LG2022★ 5 cited
Self-supervised Speaker Recognition Training Using Human-Machine Dialogues
Metehan Cekic, Ruirui Li, Zeya Chen +3
Speaker recognition, recognizing speaker identities based on voice alone, enables important downstream applications, such as personalization and authentication. Learning speaker re…