17 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
Diffusion-based speech enhancement with a weighted generative-supervised learning loss
Jean-Eudes Ayilo, Mostafa Sadeghi, Romain Serizel
Diffusion-based generative models have recently gained attention in speech enhancement (SE), providing an alternative to conventional supervised methods. These models transform cle…
Unsupervised speech enhancement with diffusion-based generative models
Berné Nortier, Mostafa Sadeghi, Romain Serizel
Recently, conditional score-based diffusion models have gained significant attention in the field of supervised speech enhancement, yielding state-of-the-art performance. However,…
Posterior sampling algorithms for unsupervised speech enhancement with recurrent variational autoencoder
Mostafa Sadeghi, Romain Serizel
In this paper, we address the unsupervised speech enhancement problem based on recurrent variational autoencoder (RVAE). This approach offers promising generalization performance o…
Unsupervised Performance Analysis of 3D Face Alignment with a Statistically Robust Confidence Test
Mostafa Sadeghi, Xavier Alameda-Pineda, Radu Horaud
This paper addresses the problem of analysing the performance of 3D face alignment (3DFA), or facial landmark localization. This task is usually supervised, based on annotated data…