Guillaume Carbajal
Title
Cited by
Cited by
Year
Multiple-input neural network-based residual echo suppression
G Carbajal, R Serizel, E Vincent, E Humbert
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
202018
Joint DNN-Based Multichannel Reduction of Acoustic Echo, Reverberation and Noise
G Carbajal, R Serizel, E Vincent, E Humbert
arXiv preprint arXiv:1911.08934, 2019
52019
Joint NN-Supported Multichannel Reduction of Acoustic Echo, Reverberation and Noise
G Carbajal, R Serizel, E Vincent, E Humbert
IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 2158-2173, 2020
32020
Speech Enhancement with Stochastic Temporal Convolutional Networks
J Richter, G Carbajal, T Gerkmann
Proc. Interspeech 2020, 4516-4520, 2020
22020
Variational Autoencoder for Speech Enhancement with a Noise-Aware Encoder
H Fang, G Carbajal, S Wermter, T Gerkmann
arXiv preprint arXiv:2102.08706, 2021
2021
Guided Variational Autoencoder for Speech Enhancement With a Supervised Classifier
G Carbajal, J Richter, T Gerkmann
arXiv preprint arXiv:2102.06454, 2021
2021
Apprentissage profond bout-en-bout pour le rehaussement de la parole
G Carbajal
Université de Lorraine, 2020
2020
Joint NN-Supported Multichannel Reduction of Acoustic Echo, Reverberation and Noise: Supporting Document
G Carbajal, R Serizel, E Vincent, E Humbert
INRIA Nancy; Invoxia SAS, 2019
2019
Procédé de suppression d'écho résiduel dans un signal acoustique
G Carbajal, R Serizel, E Vincent, E Humbert
2017
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Articles 1–9