Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancement

19 May 2021

Papers citing "Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancement"

8 / 8 papers shown

Title
Diffusion-based Unsupervised Audio-visual Speech Enhancement Jean-Eudes Ayilo Mostafa Sadeghi Romain Serizel Xavier Alameda-Pineda DiffM 32 0 0 04 Oct 2024
Integrating Uncertainty into Neural Network-based Speech Enhancement Hu Fang Dennis Becker S. Wermter Timo Gerkmann UQCV 37 2 0 15 May 2023
VarietySound: Timbre-Controllable Video to Sound Generation via Unsupervised Information Disentanglement Chenye Cui Yi Ren Jinglin Liu Rongjie Huang Zhou Zhao VGen 40 14 0 19 Nov 2022
A Two-Stage Deep Representation Learning-Based Speech Enhancement Method Using Variational Autoencoder and Adversarial Training Yang Xiang Jesper Lisby Højvang M. Rasmussen M. G. Christensen DRL 25 5 0 16 Nov 2022
Speech Enhancement and Dereverberation with Diffusion-based Generative Models Julius Richter Simon Welker Jean-Marie Lemercier Bunlong Lay Timo Gerkmann DiffM 24 185 0 11 Aug 2022
A deep representation learning speech enhancement method using $β$ -VAE Yang Xiang Jesper Lisby Højvang M. Rasmussen M. G. Christensen DRL 27 2 0 11 May 2022
Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain Simon Welker Julius Richter Timo Gerkmann DiffM 33 110 0 31 Mar 2022
Variational Autoencoder for Speech Enhancement with a Noise-Aware Encoder Hu Fang Guillaume Carbajal S. Wermter Timo Gerkmann 41 59 0 17 Feb 2021