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Roger Cheng

1 accepted papers

2022

Contrastive-mixup Learning for Improved Speaker Verification

ICASSP 2022accepted

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 weighted combination of random data point and label pairs for deep neural network training. Mixup has attracted increasing a…

Cited by 0SourceScholar