59 citations · 147 across the 14 of their papers we have counts for
25 papers
Unsupervised speech enhancement with deep dynamical generative speech and noise models
Xiaoyu Lin, Simon Leglaive, Laurent Girin +1
This work builds on a previous work on unsupervised speech enhancement using a dynamical variational autoencoder (DVAE) as the clean speech model and non-negative matrix factorizat…
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…
HiT-DVAE: Human Motion Generation via Hierarchical Transformer Dynamical VAE
Xiaoyu Bie, Wen Guo, Simon Leglaive +3
Studies on the automatic processing of 3D human pose data have flourished in the recent past. In this paper, we are interested in the generation of plausible and diverse future hum…
Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder
Xiaoyu Lin, Laurent Girin, Xavier Alameda-Pineda
In this paper, we present an unsupervised probabilistic model and associated estimation algorithm for multi-object tracking (MOT) based on a dynamical variational autoencoder (DVAE…
SALADnet: Self-Attentive multisource Localization in the Ambisonics Domain
Pierre-Amaury Grumiaux, Srdan Kitic, Prerak Srivastava +2
In this work, we propose a novel self-attention based neural network for robust multi-speaker localization from Ambisonics recordings. Starting from a state-of-the-art convolutiona…
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…