activity
20182022
most citedParallel WaveNet conditioned on VAE latent vectors

4 citations · 10 across the 10 of their papers we have counts for

collaborators

16 papers

eess.AS2022

Remap, warp and attend: Non-parallel many-to-many accent conversion with Normalizing Flows

Abdelhamid Ezzerg, Thomas Merritt, Kayoko Yanagisawa +6

Regional accents of the same language affect not only how words are pronounced (i.e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intona…

cs.CL20222 cited

Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech

Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke +5

Stuttering is a speech disorder where the natural flow of speech is interrupted by blocks, repetitions or prolongations of syllables, words and phrases. The majority of existing au…

cs.CL20221 cited

Prosodic Alignment for off-screen automatic dubbing

Yogesh Virkar, Marcello Federico, Robert Enyedi +1

The goal of automatic dubbing is to perform speech-to-speech translation while achieving audiovisual coherence. This entails isochrony, i.e., translating the original speech by als…

eess.AS20222 cited

Text-free non-parallel many-to-many voice conversion using normalising flows

Thomas Merritt, Abdelhamid Ezzerg, Piotr Biliński +4

Non-parallel voice conversion (VC) is typically achieved using lossy representations of the source speech. However, ensuring only speaker identity information is dropped whilst all…

eess.AS2022

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,…

cs.LG2021

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…