2 papers
cs.SD2025
Keep what you need : extracting efficient subnetworks from large audio representation models
David Genova, Philippe Esling, Tom Hurlin
Recently, research on audio foundation models has witnessed notable advances, as illustrated by the ever improving results on complex downstream tasks. Subsequently, those pretrain…
cs.SD2024
Combining audio control and style transfer using latent diffusion
Nils Demerlé, Philippe Esling, Guillaume Doras +1
Deep generative models are now able to synthesize high-quality audio signals, shifting the critical aspect in their development from audio quality to control capabilities. Although…