activity
20182022
most citedLearning robust speech representation with an articulatory-regularized variational autoencoder

4 citations · 4 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2022

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…

cs.SD2022

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…

cs.SD2021

A Benchmark of Dynamical Variational Autoencoders applied to Speech Spectrogram Modeling

Xiaoyu Bie, Laurent Girin, Simon Leglaive +2

The Variational Autoencoder (VAE) is a powerful deep generative model that is now extensively used to represent high-dimensional complex data via a low-dimensional latent space lea…

cs.SD20214 cited

Learning robust speech representation with an articulatory-regularized variational autoencoder

Marc-Antoine Georges, Laurent Girin, Jean-Luc Schwartz +1

It is increasingly considered that human speech perception and production both rely on articulatory representations. In this paper, we investigate whether this type of representati…

cs.CL2021

Alternate Endings: Improving Prosody for Incremental Neural TTS with Predicted Future Text Input

Brooke Stephenson, Thomas Hueber, Laurent Girin +1

The prosody of a spoken word is determined by its surrounding context. In incremental text-to-speech synthesis, where the synthesizer produces an output before it has access to the…

eess.AS2020

What the Future Brings: Investigating the Impact of Lookahead for Incremental Neural TTS

Brooke Stephenson, Laurent Besacier, Laurent Girin +1

In incremental text to speech synthesis (iTTS), the synthesizer produces an audio output before it has access to the entire input sentence. In this paper, we study the behavior of…