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Titouan Parcollet
Titouan Parcollet
Research Scientist, Samsung AI Cambridge - University of Cambridge
Verified email at samsung.com - Homepage
Title
Cited by
Cited by
Year
SpeechBrain: A general-purpose speech toolkit
M Ravanelli, T Parcollet, P Plantinga, A Rouhe, S Cornell, L Lugosch, ...
arXiv preprint arXiv:2106.04624, 2021
623*2021
Flower: A friendly federated learning research framework
DJ Beutel, T Topal, A Mathur, X Qiu, J Fernandez-Marques, Y Gao, L Sani, ...
arXiv preprint arXiv:2007.14390, 2020
5892020
The pytorch-kaldi speech recognition toolkit
M Ravanelli, T Parcollet, Y Bengio
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
2532019
Quaternion recurrent neural networks
T Parcollet, M Ravanelli, M Morchid, G Linarès, C Trabelsi, R De Mori, ...
ICLR 2019, 2018
1492018
A survey of quaternion neural networks
T Parcollet, M Morchid, G Linarès
Artificial Intelligence Review 53 (4), 2957-2982, 2020
1412020
Quaternion convolutional neural networks for end-to-end automatic speech recognition
T Parcollet, Y Zhang, M Morchid, C Trabelsi, G Linarès, R De Mori, ...
INTERSPEECH 2018, 2018
1042018
Quaternion convolutional neural networks for heterogeneous image processing
T Parcollet, M Morchid, G Linarès
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
1002019
Lebenchmark: A reproducible framework for assessing self-supervised representation learning from speech
S Evain, H Nguyen, H Le, MZ Boito, S Mdhaffar, S Alisamir, Z Tong, ...
arXiv preprint arXiv:2104.11462, 2021
682021
A first look into the carbon footprint of federated learning
X Qiu, T Parcollet, J Fernandez-Marques, PPB Gusmao, Y Gao, DJ Beutel, ...
Journal of Machine Learning Research 24 (129), 1-23, 2023
552023
Quaternion neural networks for spoken language understanding
T Parcollet, M Morchid, PM Bousquet, R Dufour, G Linarès, R De Mori
2016 IEEE Spoken Language Technology Workshop (SLT), 362-368, 2016
452016
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity
X Qiu, J Fernandez-Marques, PPB Gusmao, Y Gao, T Parcollet, ND Lane
International Conference on Learning Representations, 2022
422022
Task agnostic and task specific self-supervised learning from speech with lebenchmark
S Evain, MH Nguyen, H Le, MZ Boito, S Mdhaffar, S Alisamir, Z Tong, ...
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
372021
On-device federated learning with flower
A Mathur, DJ Beutel, PPB de Gusmao, J Fernandez-Marques, T Topal, ...
arXiv preprint arXiv:2104.03042, 2021
372021
End-to-end speech recognition from federated acoustic models
Y Gao, T Parcollet, S Zaiem, J Fernandez-Marques, PPB de Gusmao, ...
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
362022
E2E-SINCNET: Toward fully end-to-end speech recognition
T Parcollet, M Morchid, G Linares
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
342020
Cgcnn: Complex gabor convolutional neural network on raw speech
PG Noé, T Parcollet, M Morchid
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
312020
The energy and carbon footprint of training end-to-end speech recognizers
T Parcollet, M Ravanelli
302021
Flower: a friendly federated learning research framework (2020)
DJ Beutel, T Topal, A Mathur, X Qiu, T Parcollet, ND Lane
arXiv preprint arXiv:2007.14390, 2007
302007
Flower: A friendly federated learning research framework. arXiv 2020
DJ Beutel, T Topal, A Mathur, X Qiu, T Parcollet, PP de Gusmão, ND Lane
arXiv preprint arXiv:2007.14390, 2021
292021
Adversarial disentanglement of speaker representation for attribute-driven privacy preservation
PG Noé, M Mohammadamini, D Matrouf, T Parcollet, A Nautsch, ...
arXiv preprint arXiv:2012.04454, 2020
292020
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