Academic team

Slim Essid is Full Professor at Télécom Paris and the coordinator of the Audio Data Analysis and Signal Processing theme (ADASP). His research is on machine learning and artificial intelligence for temporal data analysis, especially multiview learning, structured prediction, representation learning and data decomposition methods. The target applications include machine listening and music content analysis (MIR); multimodal perception: human behavior analysis, affective computing, and EEG data analysis; multimedia content analysis, especially joint audiovisual data analysis.

Keywords : Multiview learning, structured prediction, representation learning, audio and multimodal data

Visit his website

Mathieu Fontaine is Associate Professor in the LTCI S2A team at Télécom Paris. After a PhD in Inria Nancy Grand-Est entitled “alpha-stable process for signal processing”, he was a Postdoc from October 2019 to August 2021 at RIKEN Center Artificial Intelligence Project (AIP) and became a guest at Kyoto University. His interests is mainly on machine listening including - but not limited to - speech enhancement, speaker separation, source localization and music source separation using heavy-tailed probabilistic models and/or deep bayesian networks with also applications in augmented reality.

Keywords : Machine listening, Machine Learning, Probability, Augmented Reality

Visit his website

Geoffroy Peeters is full professor in the LTCI S2A team at Télécom Paris. He received his PHDs degree in 2001 and Habilitation in 2013 from University Paris-VI on audio signal processing, data analysis and machine learning. Before joining Télécom Paris, he led researches related to Music Information Retrieval at IRCAM. His current research work is on signal processing, machine learning and deep learning applied to audio and music data analysis.

Keywords : Audio signal processing, machine learning and deep learning.

Visit his website

Gaël Richard is Professor at Télécom Paris, Institut Mines-Télécom and head of the Image, Data, Signal (IDS) department. His research work lies at the core of digitization and is dedicated to the analysis, transformation, understanding and automatic indexing of acoustic signals (including speech, music, surrounding sounds) and to a lesser extent of heterogeneous and multimodal signals. In particular, he developed several source separation methods for audio and musical signals based on machine learning approaches.

Keywords : Machine listening, Matrix Factorization, Representation and subspace learning, Music Information Retrieval (MIR), Sound recognition, Audio source separation.

Visit his website

Roland Badeau is Full Professor in the Signal, Statistics and Machine learning (S2A) team of the Image, Data, Signal (IDS) Department at Télécom Paris. His research interests focus on statistical modeling of non-stationary signals (including adaptive high-resolution spectral analysis and Bayesian extensions to NMF), with applications to audio and music (source separation, denoising, dereverberation, multipitch estimation, automatic music transcription, audio coding, audio inpainting). He is a co-author of 30 journal papers, over 100 international conference papers, and 4 patents. He is also an Associate Editor of the EURASIP Journal on Audio, Speech, and Music Processing and the IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Keywords : machine learning, data decomposition, machine listening, MIR

Visit his website

Yves Grenier was Associate professor at the Ecole Nationale Supérieure des Télécommunications (now Télécom Paris) from 1977, and was appointed Professor there in 1984. For ten years, he directed the Signal and Image Processing Department, then renamed IDS (Image, Data, Signal) at LTCI, and is since April 2018 Professor Emeritus at Télécom Paris. Part of his research focused on multi-sensor signal processing: antenna filtering, localization of sources received on a sensor network. He has focused in particular on the applications of these techniques to aerial acoustics and to sound recording by microphone arrays: acoustic echo cancellation, dereverberation, noise reduction, source separation, spatialization by loudspeaker array. His interests have also led him to musical information extraction, multi-pitch detection, chord recognition. He has participated in many national and European projects (K-Space, 3D-Life, Quaero, Romeo ). He is a member of theIEEE and was technical co-chair of the "2010 IEEE International Workshop on Multimedia Signal Processing" MMSP 2010.

Keywords : Audio signal processing.

Visit his website