Chang Han

Curricular Contrastive Regularization for Speech Enhancement with Self-Supervised Representations

Existing deep learning-based speech enhancement methods only adopt clean speech as positive samples to guide the training of speech enhancement networks while negative samples, i.e., noisy speech, are unexploited. In this paper, we adopt contrastive regularization (CR) built upon contrastive learnin…