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Félix de Chaumont Quitry
Félix de Chaumont Quitry
Google DeepMind
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Title
Cited by
Cited by
Year
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
1952024
Acoustic modelling with cd-ctc-smbr lstm rnns
A Senior, H Sak, F de Chaumont Quitry, T Sainath, K Rao
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015
1562015
Towards learning a universal non-semantic representation of speech
J Shor, A Jansen, R Maor, O Lang, O Tuval, FC Quitry, M Tagliasacchi, ...
arXiv preprint arXiv:2002.12764, 2020
1552020
LEAF: A learnable frontend for audio classification
N Zeghidour, O Teboul, FDC Quitry, M Tagliasacchi
arXiv preprint arXiv:2101.08596, 2021
1542021
Audiopalm: A large language model that can speak and listen
PK Rubenstein, C Asawaroengchai, DD Nguyen, A Bapna, Z Borsos, ...
arXiv preprint arXiv:2306.12925, 2023
1012023
Pre-training audio representations with self-supervision
M Tagliasacchi, B Gfeller, F de Chaumont Quitry, D Roblek
IEEE Signal Processing Letters 27, 600-604, 2020
572020
Self-supervised audio representation learning for mobile devices
M Tagliasacchi, B Gfeller, FC Quitry, D Roblek
arXiv preprint arXiv:1905.11796, 2019
492019
Disentangling speech from surroundings in a neural audio codec
A Omran, N Zeghidour, Z Borsos, F de Chaumont Quitry, M Slaney, ...
arXiv preprint ArXiv:2203.15578, 2022
10*2022
Learning audio representations via phase prediction
FC Quitry, M Tagliasacchi, D Roblek
arXiv preprint arXiv:1910.11910, 2019
92019
High quality agreement-based semi-supervised training data for acoustic modeling
F de Chaumont Quitry, A Oines, P Moreno, E Weinstein
2016 IEEE Spoken Language Technology Workshop (SLT), 592-596, 2016
82016
Learning audio representations via phase prediction
F de Chaumont Quitry, M Tagliasacchi, D Roblek
arXiv e-prints, arXiv: 1910.11910, 2019
52019
Generating audio waveforms using encoder and decoder neural networks
Y Li, M Tagliasacchi, D Roblek, F de Chaumont Quitry, B Gfeller, ...
US Patent App. 17/856,292, 2023
32023
Multi-task adapter neural networks
M Tagliasacchi, F de Chaumont Quitry, D Roblek
US Patent App. 17/764,005, 2022
22022
Self-supervised audio representation learning for mobile devices
B Gfeller, D Roblek, F de Chaumont Quitry, M Tagliasacchi
US Patent 11,501,787, 2022
12022
CycleGAN-Based Unpaired Speech Dereverberation
H Muckenhirn, A Safin, H Erdogan, FC Quitry, M Tagliasacchi, S Wisdom, ...
arXiv preprint arXiv:2203.15652, 2022
12022
Methods and systems for implementing on-device non-semantic representation fine-tuning for speech classification
J Shor, R Maor, O Lang, O Tuval, M Tagliasacchi, I Shavitt, ...
US Patent 11,996,116, 2024
2024
Learned audio frontend machine learning model for audio understanding
N Zeghidour, O Teboul, F de Chaumont Quitry, M Tagliasacchi
US Patent App. 18/029,843, 2023
2023
Self-Supervised Audio Representation Learning for Mobile Devices
B Gfeller, D Roblek, F de Chaumont Quitry, M Tagliasacchi
US Patent App. 17/986,477, 2023
2023
Multi-Task Adapters for On-Device Audio Inference
M Tagliasacchi, F de Chaumont Quitry, D Roblek
IEEE Signal Processing Letters 27, 630-634, 2020
2020
Learning audio representations with self-supervision
M Tagliasacchi, B Gfeller, F de Chaumont Quitry, D Roblek
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