257 citations · 424 across the 25 of their papers we have counts for
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StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberation
Jean-Marie Lemercier, Julius Richter, Simon Welker +1
Diffusion models have shown a great ability at bridging the performance gap between predictive and generative approaches for speech enhancement. We have shown that they may even ou…
Analysing Diffusion-based Generative Approaches versus Discriminative Approaches for Speech Restoration
Jean-Marie Lemercier, Julius Richter, Simon Welker +1
Diffusion-based generative models have had a high impact on the computer vision and speech processing communities these past years. Besides data generation tasks, they have also be…
Speech Enhancement and Dereverberation with Diffusion-based Generative Models
Julius Richter, Simon Welker, Jean-Marie Lemercier +2
In this work, we build upon our previous publication and use diffusion-based generative models for speech enhancement. We present a detailed overview of the diffusion process that…
Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain
Simon Welker, Julius Richter, Timo Gerkmann
Score-based generative models (SGMs) have recently shown impressive results for difficult generative tasks such as the unconditional and conditional generation of natural images an…