1 citations · 2 across the 3 of their papers we have counts for
3 papers
Regularizing Contrastive Predictive Coding for Speech Applications
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Self-supervised methods such as Contrastive predictive Coding (CPC) have greatly improved the quality of the unsupervised representations. These representations significantly reduc…
Time-domain speech super-resolution with GAN based modeling for telephony speaker verification
Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2
Automatic Speaker Verification (ASV) technology has become commonplace in virtual assistants. However, its performance suffers when there is a mismatch between the train and test d…
Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representations
Jaejin Cho, Raghavendra Pappagari, Piotr Żelasko +3
Considering the abundance of unlabeled speech data and the high labeling costs, unsupervised learning methods can be essential for better system development. One of the most succes…