93 citations · 122 across the 6 of their papers we have counts for
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eess.AS2022★ 5 cited
Adversarial Reweighting for Speaker Verification Fairness
Minho Jin, Chelsea J. -T. Ju, Zeya Chen +3
We address performance fairness for speaker verification using the adversarial reweighting (ARW) method. ARW is reformulated for speaker verification with metric learning, and show…
eess.AS2022★ 11 cited
openFEAT: Improving Speaker Identification by Open-set Few-shot Embedding Adaptation with Transformer
Kishan K C, Zhenning Tan, Long Chen +4
Household speaker identification with few enrollment utterances is an important yet challenging problem, especially when household members share similar voice characteristics and r…
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…