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…