| End-to-end lyrics alignment for polyphonic music using an audio-to-character recognition model D Stoller, S Durand, S Ewert ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 117 | 2019 |
| OpenMIC-2018: An Open Data-set for Multiple Instrument Recognition. E Humphrey, S Durand, B McFee ISMIR, 438-444, 2018 | 113 | 2018 |
| Downbeat tracking with multiple features and deep neural networks S Durand, JP Bello, B David, G Richard 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 59 | 2015 |
| Robust downbeat tracking using an ensemble of convolutional networks S Durand, JP Bello, B David, G Richard IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (1), 76-89, 2016 | 57 | 2016 |
| Feature adapted convolutional neural networks for downbeat tracking S Durand, JP Bello, B David, G Richard 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 41 | 2016 |
| Deblocking DCT-based compressed images with weighted total variation F Alter, SY Durand, J Froment 2004 IEEE International Conference on Acoustics, Speech, and Signal …, 2004 | 41 | 2004 |
| Llark: A multimodal foundation model for music J Gardner, S Durand, D Stoller, RM Bittner arXiv preprint arXiv:2310.07160, 2023 | 27 | 2023 |
| Downbeat Detection with Conditional Random Fields and Deep Learned Features. S Durand, S Essid ISMIR, 386-392, 2016 | 20 | 2016 |
| Enhancing downbeat detection when facing different music styles S Durand, B David, G Richard 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 20 | 2014 |
| Contrastive learning-based audio to lyrics alignment for multiple languages S Durand, D Stoller, S Ewert ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 14 | 2023 |
| A conditional random field system for beat tracking T Fillon, C Joder, S Durand, S Essid 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 14 | 2015 |
| LLark: A Multimodal Instruction-Following Language Model for Music JP Gardner, S Durand, D Stoller, RM Bittner Forty-first International Conference on Machine Learning, 2023 | 13 | 2023 |
| Data cleansing with contrastive learning for vocal note event annotations G Meseguer-Brocal, R Bittner, S Durand, B Brost arXiv preprint arXiv:2008.02069, 2020 | 7 | 2020 |
| Dereverberation using joint estimation of dry speech signal and acoustic system S Wager, K Choi, S Durand arXiv preprint arXiv:2007.12581, 2020 | 4 | 2020 |
| Automatic Identification of Samples in Hip-Hop Music via Multi-Loss Training and an Artificial Dataset H Cheston, J Van Balen, S Durand arXiv preprint arXiv:2502.06364, 2025 | | 2025 |
| Doctorat ParisTech THÈSE S Durand telecom-paristech, 2017 | | 2017 |
| Estimation automatique des premiers temps dans un signal audio musical S Durand Télécom ParisTech, 2017 | | 2017 |
| Rapport de stage de Master II S Durand | | 2013 |
| Bounded Representations of Amenable Groupoids and Transference S Durand, R Feres | | |
| 3.3 What is the Best Task to Learn a Generic Music Audio Representation? S Durand, D Stoller Deep Learning and Knowledge Integration for Music Audio Analysis, 112, 0 | | |
Gaël RichardProfessor, Télécom Paris, Institut polytechnique de ParisDirección de correo verificada de telecom-paris.fr