59 citations · 103 across the 3 of their papers we have counts for
3 papers
A Recurrent Variational Autoencoder for Speech Enhancement
Simon Leglaive, Xavier Alameda-Pineda, Laurent Girin +1
This paper presents a generative approach to speech enhancement based on a recurrent variational autoencoder (RVAE). The deep generative speech model is trained using clean speech…
Speech enhancement with variational autoencoders and alpha-stable distributions
Simon Leglaive, Umut Simsekli, Antoine Liutkus +2
This paper focuses on single-channel semi-supervised speech enhancement. We learn a speaker-independent deep generative speech model using the framework of variational autoencoders…
A variance modeling framework based on variational autoencoders for speech enhancement
Simon Leglaive, Laurent Girin, Radu Horaud
In this paper we address the problem of enhancing speech signals in noisy mixtures using a source separation approach. We explore the use of neural networks as an alternative to a…