45 citations · 211 across the 23 of their papers we have counts for
5 papers · 1 filter
SepRQ : Self-Supervised Speech Mixture Representation Learning via Mask-Free, Multi-Scale Source Separation
Séverin Baroudi, Hervé Bredin, Ricard Marxer
Self-supervised learning (SSL) is standard for speech representation learning, but mainstream models are designed around single-speaker audio, limiting their usefulness in multi-sp…
Steering Speech-Language Models: Training-Free Task Specialization via Contrastive Activation Addition
Séverin Baroudi, Yanis Labrak, Pierfrancesco Melucci +5
Activation steering has proven effective for controlling the behavior of Large Language Models (LLMs) at inference time, but its application to SpeechLLMs remains new, and training…
GLaS-JEPA: Gaussian-Regularized Speech SSL without Engineered Prediction Targets
Gaspard Botté, Séverin Baroudi, Samir Sadok +5
Speech self-supervised learning aims to learn general-purpose representations for downstream speech tasks. However, current approaches rely on complex, carefully designed predictio…
Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization
Yanis Labrak, David Grünert, Séverin Baroudi +11
Long-context audio reasoning is underserved in both training data and evaluation. Existing benchmarks target short-context tasks, and the open-ended generation tasks most relevant…
DASHA: Diarization-Aware Speech-LLM ASR for Healthcare in Code-Switched Indic Doctor-Patient Conversations
Séverin Baroudi, Yanis Labrak, Shashi Kumar +7
Extracting patients' medical conditions from recorded primary-care conversations requires knowing who said what, which is difficult when speech is far-field, spontaneous, overlappi…