10 citations · 31 across the 20 of their papers we have counts for
3 papers · 1 filter
Improving the expressiveness of neural vocoding with non-affine Normalizing Flows
Adam Gabryś, Yunlong Jiao, Viacheslav Klimkov +2
This paper proposes a general enhancement to the Normalizing Flows (NF) used in neural vocoding. As a case study, we improve expressive speech vocoding with a revamped Parallel Wav…
SynthASR: Unlocking Synthetic Data for Speech Recognition
Amin Fazel, Wei Yang, Yulan Liu +4
End-to-end (E2E) automatic speech recognition (ASR) models have recently demonstrated superior performance over the traditional hybrid ASR models. Training an E2E ASR model require…
Improving multi-speaker TTS prosody variance with a residual encoder and normalizing flows
Iván Vallés-Pérez, Julian Roth, Grzegorz Beringer +2
Text-to-speech systems recently achieved almost indistinguishable quality from human speech. However, the prosody of those systems is generally flatter than natural speech, produci…