| DALI: a large Dataset of synchronized Audio, LyrIcs and notes, automatically created using teacher-student machine learning paradigm G Meseguer-Brocal, A Cohen-Hadria, G Peeters | 108 | 2018 |
| Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source Separations G Meseguer-Brocal, G Peeters arXiv preprint arXiv:1907.01277, 2019 | 74 | 2019 |
| A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation RM Bittner, JJ Bosch, D Rubinstein, G Meseguer-Brocal, S Ewert ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 37 | 2022 |
| Creating DALI, a Large Dataset of Synchronized Audio, Lyrics, and Notes G Meseguer-Brocal, A Cohen-Hadria, G Peeters Transactions of the International Society for Music Information Retrieval 3 (1), 2020 | 24 | 2020 |
| WASABI: a Two Million Song Database Project with Audio and Cultural Metadata plus WebAudio enhanced Client Applications G Meseguer-Brocal, G Peeters, G Pellerin, M Buffa, E Cabrio, CF Zucker, ... Web Audio Conference 2017–Collaborative Audio# WAC2017, 2017 | 24 | 2017 |
| vocadito: A dataset of solo vocals with , note, and lyric annotations R M. Bittner, K Pasalo, JJ Bosch, G Meseguer-Brocal, D Rubinstein arXiv preprint arXiv:2110.05580, 2021 | 17 | 2021 |
| Content based singing voice source separation via strong conditioning using aligned phonemes G Meseguer-Brocal, G Peeters arXiv preprint arXiv:2008.02070, 2020 | 16 | 2020 |
| 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 |
| Movement Analysis and Decomposition with the Continuous Wavelet Transform J Françoise, G Meseguer-Brocal, F Bevilacqua Proceedings of the 8th International Conference on Movement and Computing, 1-13, 2022 | 5 | 2022 |
| Lyrics segmentation via bimodal text–audio representation M Fell, Y Nechaev, G Meseguer-Brocal, E Cabrio, F Gandon, G Peeters Natural Language Engineering 28 (3), 317-336, 2022 | 5 | 2022 |
| Detecting music deepfakes is easy but actually hard D Afchar, G Meseguer-Brocal, R Hennequin arXiv preprint arXiv:2405.04181, 2024 | 2 | 2024 |
| An Experimental Comparison of Multi-View Self-Supervised Methods for Music Tagging G Meseguer-Brocal, D Desblancs, R Hennequin ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 2 | 2024 |
| From Real to Cloned Singer Identification D Desblancs, G Meseguer-Brocal, R Hennequin, M Moussallam arXiv preprint arXiv:2407.08647, 2024 | | 2024 |
| STONE: Self-supervised Tonality Estimator Y Kong, V Lostanlen, G Meseguer-Brocal, S Wong, M Lagrange, ... arXiv preprint arXiv:2407.07408, 2024 | | 2024 |
| Detecting Synthetic Lyrics with Few-Shot Inference Y Labrak, G Meseguer-Brocal, EV Epure arXiv preprint arXiv:2406.15231, 2024 | | 2024 |
| MULTIMODAL ANALYSIS: Informed content estimation and audio source separation G Meseguer-Brocal Sorbonne Université, 2020 | | 2020 |
| Automatic content-based detection of influences in the history of Progressive Rock Music G Meseguer-Brocal https://s3.amazonaws.com/academia.edu.documents/52818101/Gabriel-Meseguer …, 2013 | | 2013 |
| Detección de armonía y estructura rítmica musical G Meseguer-Brocal, AP Ibáñez | | 2009 |
Geoffroy PeetersTélécom Paris (previously IRCAM - STMS)在 telecom-paris.fr 的电子邮件经过验证
