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cs.CL2022
Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models
Sung-Lin Yeh, Hao Tang
While discrete latent variable models have had great success in self-supervised learning, most models assume that frames are independent. Due to the segmental nature of phonemes in…
eess.AS2022★ 20 cited
Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution
Chin-Yun Yu, Sung-Lin Yeh, György Fazekas +1
Recently, diffusion models (DMs) have been increasingly used in audio processing tasks, including speech super-resolution (SR), which aims to restore high-frequency content given l…
cs.CL2022
Autoregressive Co-Training for Learning Discrete Speech Representations
Sung-Lin Yeh, Hao Tang
While several self-supervised approaches for learning discrete speech representation have been proposed, it is unclear how these seemingly similar approaches relate to each other.…