1 citations · 1 across the 3 of their papers we have counts for
5 papers
Sparse Autoencoders Make Audio Foundation Models more Explainable
Théo Mariotte, Martin Lebourdais, Antonio Almudévar +3
Audio pretrained models are widely employed to solve various tasks in speech processing, sound event detection, or music information retrieval. However, the representations learned…
TalTech-IRIT-LIS Speaker and Language Diarization Systems for DISPLACE 2024
Joonas Kalda, Tanel Alumäe, Martin Lebourdais +3
This paper describes the submissions of team TalTech-IRIT-LIS to the DISPLACE 2024 challenge. Our team participated in the speaker diarization and language diarization tracks of th…
Explainable by-design Audio Segmentation through Non-Negative Matrix Factorization and Probing
Martin Lebourdais, Théo Mariotte, Antonio Almudévar +2
Audio segmentation is a key task for many speech technologies, most of which are based on neural networks, usually considered as black boxes, with high-level performances. However,…
Joint speech and overlap detection: a benchmark over multiple audio setup and speech domains
Martin Lebourdais, Théo Mariotte, Marie Tahon +5
Voice activity and overlapped speech detection (respectively VAD and OSD) are key pre-processing tasks for speaker diarization. The final segmentation performance highly relies on…
Overlapped speech and gender detection with WavLM pre-trained features
Martin Lebourdais, Marie Tahon, Antoine Laurent +1
This article focuses on overlapped speech and gender detection in order to study interactions between women and men in French audiovisual media (Gender Equality Monitoring project)…