About
Mathieu Fontaine is an Associate Professor in Machine Listening at Télécom Paris, affiliated with the LTCI Lab within the IDS Department (Information, Data, Signal). His research focuses on machine listening for speech and audio signal processing.
- PhD in Informatics (2019), Lorraine University
- Master in Applied and Fundamental Mathematics (2015), Poitiers University
- BSc in Fundamental Mathematics (2013), Rennes University
Fontaine's research spans speech enhancement, speaker separation, source localization, and music source separation using heavy-tailed probabilistic models and deep Bayesian networks, with applications in augmented reality. He has expertise in Python, signal processing, and machine learning (80% proficiency).
His recent publications (2024) include work on diffusion models for speech synthesis, room acoustics estimation from 3D meshes, robust audio scene analysis, and direction-aware speech processing. Earlier publications (2022-2023) explore flow-based NMF, alpha-stable representations, and adaptive beamforming in multiparty environments.
Fontaine collaborates with the S2A team and ADASP group at LTCI Lab. His work integrates probabilistic modeling with deep learning to address challenges in real-world audio processing, including reverberation, noise, and complex acoustic environments.
