Simon Leglaive
Simon Leglaive
Assistant Professor at CentraleSupélec
Verified email at centralesupelec.fr - Homepage
Title
Cited by
Cited by
Year
Singing voice detection with deep recurrent neural networks
S Leglaive, R Hennequin, R Badeau
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
852015
A variance modeling framework based on variational autoencoders for speech enhancement
S Leglaive, L Girin, R Horaud
2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018
472018
Semi-supervised multichannel speech enhancement with variational autoencoders and non-negative matrix factorization
S Leglaive, L Girin, R Horaud
2019 IEEE International Conference on Acoustics, Speech and Signal …, 2019
452019
Alpha-stable multichannel audio source separation
S Leglaive, U Şimşekli, A Liutkus, R Badeau, G Richard
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
292017
Speech enhancement with variational autoencoders and alpha-stable distributions
S Leglaive, U Simsekli, A Liutkus, L Girin, R Horaud
2019 IEEE International Conference on Acoustics, Speech and Signal …, 2019
272019
Audio-visual speech enhancement using conditional variational auto-encoders
M Sadeghi, S Leglaive, X Alameda-Pineda, L Girin, R Horaud
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020
232020
Multichannel audio source separation with probabilistic reverberation priors
S Leglaive, R Badeau, G Richard
IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (12 …, 2016
192016
A Recurrent Variational Autoencoder for Speech Enhancement
S Leglaive, X Alameda-Pineda, L Girin, R Horaud
2020 IEEE International Conference on Acoustics, Speech and Signal …, 2020
172020
Dynamical Variational Autoencoders: A Comprehensive Review
L Girin, S Leglaive, X Bie, J Diard, T Hueber, X Alameda-Pineda
arXiv preprint arXiv:2008.12595, 2020
152020
Multichannel audio source separation with probabilistic reverberation modeling
S Leglaive, R Badeau, G Richard
2015 IEEE Workshop on Applications of Signal Processing to Audio and …, 2015
142015
Separating time-frequency sources from time-domain convolutive mixtures using non-negative matrix factorization
S Leglaive, R Badeau, G Richard
2017 IEEE Workshop on Applications of Signal Processing to Audio and …, 2017
132017
Multichannel audio source separation: variational inference of time-frequency sources from time-domain observations
S Leglaive, R Badeau, G Richard
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
122017
Student's t Source and Mixing Models for Multichannel Audio Source Separation
S Leglaive, R Badeau, G Richard
IEEE/ACM Transactions on Audio, Speech and Language Processing 26 (5), 1-15, 2018
92018
Notes on the use of variational autoencoders for speech and audio spectrogram modeling
L Girin, T Hueber, F Roche, S Leglaive
International Conference on Digital Audio Effects (DAFx), 2019
82019
Alpha-stable low-rank plus residual decomposition for speech enhancement
U Şimşekli, H Erdoğan, S Leglaive, A Liutkus, R Badeau, G Richard
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
82018
Audio-noise Power Spectral Density Estimation Using Long Short-term Memory
X Li, S Leglaive, L Girin, R Horaud
IEEE Signal Processing Letters 26 (6), 918-922, 2019
62019
Semi-Blind Student’s t Source Separation for Multichannel Audio Convolutive Mixtures
S Leglaive, R Badeau, G Richard
25th European Signal Processing Conference (EUSIPCO), 2323-2327, 2017
62017
Autoregressive moving average modeling of late reverberation in the frequency domain
S Leglaive, R Badeau, G Richard
2016 24th European Signal Processing Conference (EUSIPCO), 1478-1482, 2016
42016
A priori probabiliste anéchoïque pour la séparation sous-déterminée de sources sonores en milieu réverbérant
S Leglaive, R Badeau, G Richard
Colloque GRETSI, 2015
32015
On Speech Sparsity for Computational Efficiency and Noise Reduction in Hearing Aids
A Llave, S Leglaive
13th Asia Pacific Signal and Information Processing Association Annual …, 2021
2021
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