Hennequin Romain
Hennequin Romain
Lead research scientist, Deezer Research
Adresse e-mail validée de deezer.com
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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
1122011
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
812015
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
762010
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
462010
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
402019
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
372018
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
282020
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
232017
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
202019
Keep it simple: Graph autoencoders without graph convolutional networks
G Salha, R Hennequin, M Vazirgiannis
arXiv preprint arXiv:1910.00942, 2019
172019
A degeneracy framework for scalable graph autoencoders
G Salha, R Hennequin, VA Tran, M Vazirgiannis
arXiv preprint arXiv:1902.08813, 2019
162019
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
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
142019
Codec independent lossy audio compression detection
R Hennequin, J Royo-Letelier, M Moussallam
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
122017
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
Scale-invariant probabilistic latent component analysis
R Hennequin, R Badeau, B David
2011 IEEE Workshop on Applications of Signal Processing to Audio and …, 2011
102011
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