169 citations · 196 across the 13 of their papers we have counts for
4 papers · 1 filter
BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language model
Brooke Stephenson, Laurent Besacier, Laurent Girin +1
Several recent studies have tested the use of transformer language model representations to infer prosodic features for text-to-speech synthesis (TTS). While these studies have exp…
Self-supervised speech unit discovery from articulatory and acoustic features using VQ-VAE
Marc-Antoine Georges, Jean-Luc Schwartz, Thomas Hueber
The human perception system is often assumed to recruit motor knowledge when processing auditory speech inputs. Using articulatory modeling and deep learning, this study examines h…
Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
Sanjana Sankar, Denis Beautemps, Thomas Hueber
This paper proposes a simple and effective approach for automatic recognition of Cued Speech (CS), a visual communication tool that helps people with hearing impairment to understa…
Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation
Marc-Antoine Georges, Julien Diard, Laurent Girin +2
We propose a computational model of speech production combining a pre-trained neural articulatory synthesizer able to reproduce complex speech stimuli from a limited set of interpr…