collaborators

8 papers

cs.LG2026

Multiple Choice Learning of Low-Rank Adapters for Language Modeling

Victor Letzelter, Hugo Malard, Mathieu Fontaine +4

We propose LoRA-MCL, a training scheme that extends next-token prediction in language models with a method designed to decode diverse, plausible sentence continuations at inference…

physics.class-ph2026

Taylor-SWFT: fast discrete Statistical Wave Field Theory using Taylor expansion for late reverberation Work under review

Marius Rodrigues, Louis Lalay, Roland Badeau +2

Dynamic room acoustic simulation aims to render the acoustic effects of an environment in real time while accounting for potentially moving sources and receivers. In this context,…

cs.SD2026

U-DREAM: Unsupervised Dereverberation guided by a Reverberation Model

Louis Bahrman, Marius Rodrigues, Mathieu Fontaine +1

This paper explores the outcome of training state-of-the-art dereverberation models with supervision settings ranging from weakly-supervised to virtually unsupervised, relying sole…

cs.SD2026

The silence of the weights: a structural pruning strategy for attention-based audio signal architectures with second order metrics

Andrea Diecidue, Carlo Alberto Barbano, Piero Fraternali +2

Transformer-based models have become the state of the art across multiple domains, from natural language processing to machine listening, thanks to the attention mechanisms. Howeve…

cs.SD2026

Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement

Thomas Serre, Mathieu Fontaine, Éric Benhaim +1

Personalized speech enhancement (PSE) has shown convincing results when it comes to extracting a known target voice among interfering ones. The corresponding systems usually incorp…

cs.LG2025

O-EENC-SD: Efficient Online End-to-End Neural Clustering for Speaker Diarization

Elio Gruttadauria, Mathieu Fontaine, Jonathan Le Roux +1

We introduce O-EENC-SD: an end-to-end online speaker diarization system based on EEND-EDA, featuring a novel RNN-based stitching mechanism for online prediction. In particular, we…