23 citations · 23 across the 6 of their papers we have counts for
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eess.AS2021
Switching Variational Auto-Encoders for Noise-Agnostic Audio-visual Speech Enhancement
Mostafa Sadeghi, Xavier Alameda-Pineda
Recently, audio-visual speech enhancement has been tackled in the unsupervised settings based on variational auto-encoders (VAEs), where during training only clean data is used to…
eess.AS2019
Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement
Mostafa Sadeghi, Xavier Alameda-Pineda
In this paper, we are interested in unsupervised (unknown noise) audio-visual speech enhancement based on variational autoencoders (VAEs), where the probability distribution of cle…
eess.AS2019
Robust Unsupervised Audio-visual Speech Enhancement Using a Mixture of Variational Autoencoders
Mostafa Sadeghi, Xavier Alameda-Pineda
Recently, an audio-visual speech generative model based on variational autoencoder (VAE) has been proposed, which is combined with a nonnegative matrix factorization (NMF) model fo…