16 citations · 50 across the 9 of their papers we have counts for
4 papers · 1 filter
The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems
Philippe Gonzalez, Zheng-Hua Tan, Jan Østergaard +3
The performance of deep neural network-based speech enhancement systems typically increases with the training dataset size. However, studies that investigated the effect of trainin…
Diffusion-Based Speech Enhancement in Matched and Mismatched Conditions Using a Heun-Based Sampler
Philippe Gonzalez, Zheng-Hua Tan, Jan Østergaard +3
Diffusion models are a new class of generative models that have recently been applied to speech enhancement successfully. Previous works have demonstrated their superior performanc…
Investigating the Design Space of Diffusion Models for Speech Enhancement
Philippe Gonzalez, Zheng-Hua Tan, Jan Østergaard +3
Diffusion models are a new class of generative models that have shown outstanding performance in image generation literature. As a consequence, studies have attempted to apply diff…
Assessing the Generalization Gap of Learning-Based Speech Enhancement Systems in Noisy and Reverberant Environments
Philippe Gonzalez, Tommy Sonne Alstrøm, Tobias May
The acoustic variability of noisy and reverberant speech mixtures is influenced by multiple factors, such as the spectro-temporal characteristics of the target speaker and the inte…