Hennequin Romain
Hennequin Romain
Lead research scientist, Deezer Research
Verified email at deezer.com
Title
Cited by
Cited by
Year
Score informed audio source separation using a parametric model of non-negative spectrogram
R Hennequin, B David, R Badeau
2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011
1132011
Identification of cascade of Hammerstein models for the description of nonlinearities in vibrating devices
M Rébillat, R Hennequin, E Corteel, BFG Katz
Journal of sound and vibration 330 (5), 1018-1038, 2011
852011
Singing voice detection with deep recurrent neural networks
S Leglaive, R Hennequin, R Badeau
2015 IEEE International conference on acoustics, speech and signal …, 2015
842015
NMF with time–frequency activations to model nonstationary audio events
R Hennequin, R Badeau, B David
IEEE Transactions on Audio, Speech, and Language Processing 19 (4), 744-753, 2010
782010
Spleeter: A fast and state-of-the art music source separation tool with pre-trained models
R Hennequin, A Khlif, F Voituret, M Moussallam
Late-Breaking/Demo ISMIR 2019, 2019
472019
Time-dependent parametric and harmonic templates in non-negative matrix factorization
R Hennequin, R Badeau, B David
Proc. of the 13th International Conference on Digital Audio Effects (DAFx), 2010
472010
Spleeter: a fast and efficient music source separation tool with pre-trained models
R Hennequin, A Khlif, F Voituret, M Moussallam
Journal of Open Source Software 5 (50), 2154, 2020
422020
Beta-divergence as a subclass of Bregman divergence
R Hennequin, B David, R Badeau
IEEE Signal Processing Letters 18 (2), 83-86, 2010
402010
Music mood detection based on audio and lyrics with deep neural net
R Delbouys, R Hennequin, F Piccoli, J Royo-Letelier, M Moussallam
ISMIR 2018, 2018
392018
Gravity-inspired graph autoencoders for directed link prediction
G Salha, S Limnios, R Hennequin, VA Tran, M Vazirgiannis
Proceedings of the 28th ACM International Conference on Information and …, 2019
252019
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
242017
A degeneracy framework for scalable graph autoencoders
G Salha, R Hennequin, VA Tran, M Vazirgiannis
arXiv preprint arXiv:1902.08813, 2019
202019
Keep it simple: Graph autoencoders without graph convolutional networks
G Salha, R Hennequin, M Vazirgiannis
arXiv preprint arXiv:1910.00942, 2019
182019
Singing voice separation: A study on training data
L Prétet, R Hennequin, J Royo-Letelier, A Vaglio
ICASSP 2019-2019 ieee international conference on acoustics, speech and …, 2019
172019
Speech-guided source separation using a pitch-adaptive guide signal model
R Hennequin, JJ Burred, S Maller, P Leveau
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
152014
Prediction of harmonic distortion generated by electro-dynamic loudspeakers using cascade of Hammerstein models
M Rébillat, R Hennequin, E Corteel, B Katz
128th Convention of the audio engineering society, 7993, 2010
152010
Codec independent lossy audio compression detection
R Hennequin, J Royo-Letelier, M Moussallam
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
132017
Simple and effective graph autoencoders with one-hop linear models
G Salha, R Hennequin, M Vazirgiannis
arXiv preprint arXiv:2001.07614, 2020
122020
Décomposition de spectrogrammes musicaux informée par des modeles de synthese spectrale. Modélisation des variations temporelles dans les éléments sonores.
R Hennequin
Télécom ParisTech, 2011
122011
Audio based disambiguation of music genre tags
R Hennequin, J Royo-Letelier, M Moussallam
ISMIR 2018, 2018
102018
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