31 citations · 39 across the 11 of their papers we have counts for
25 papers
Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module
Adam Gabryś, Goeric Huybrechts, Manuel Sam Ribeiro +6
State-of-the-art text-to-speech (TTS) systems require several hours of recorded speech data to generate high-quality synthetic speech. When using reduced amounts of training data,…
Cross-speaker style transfer for text-to-speech using data augmentation
Manuel Sam Ribeiro, Julian Roth, Giulia Comini +3
We address the problem of cross-speaker style transfer for text-to-speech (TTS) using data augmentation via voice conversion. We assume to have a corpus of neutral non-expressive d…
Enhancing audio quality for expressive Neural Text-to-Speech
Abdelhamid Ezzerg, Adam Gabrys, Bartosz Putrycz +7
Artificial speech synthesis has made a great leap in terms of naturalness as recent Text-to-Speech (TTS) systems are capable of producing speech with similar quality to human recor…
Voicy: Zero-Shot Non-Parallel Voice Conversion in Noisy Reverberant Environments
Alejandro Mottini, Jaime Lorenzo-Trueba, Sri Vishnu Kumar Karlapati +1
Voice Conversion (VC) is a technique that aims to transform the non-linguistic information of a source utterance to change the perceived identity of the speaker. While there is a r…
A learned conditional prior for the VAE acoustic space of a TTS system
Penny Karanasou, Sri Karlapati, Alexis Moinet +5
Many factors influence speech yielding different renditions of a given sentence. Generative models, such as variational autoencoders (VAEs), capture this variability and allow mult…
Weakly-supervised word-level pronunciation error detection in non-native English speech
Daniel Korzekwa, Jaime Lorenzo-Trueba, Thomas Drugman +2
We propose a weakly-supervised model for word-level mispronunciation detection in non-native (L2) English speech. To train this model, phonetically transcribed L2 speech is not req…