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Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech
Guangyan Zhang, Thomas Merritt, Manuel Sam Ribeiro +10
Neural text-to-speech systems are often optimized on L1/L2 losses, which make strong assumptions about the distributions of the target data space. Aiming to improve those assumptio…
Improving grapheme-to-phoneme conversion by learning pronunciations from speech recordings
Manuel Sam Ribeiro, Giulia Comini, Jaime Lorenzo-Trueba
The Grapheme-to-Phoneme (G2P) task aims to convert orthographic input into a discrete phonetic representation. G2P conversion is beneficial to various speech processing application…
Low-data? No problem: low-resource, language-agnostic conversational text-to-speech via F0-conditioned data augmentation
Giulia Comini, Goeric Huybrechts, Manuel Sam Ribeiro +2
The availability of data in expressive styles across languages is limited, and recording sessions are costly and time consuming. To overcome these issues, we demonstrate how to bui…