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Eduardo Fonseca
Eduardo Fonseca
Research Scientist @ Google DeepMind
Verified email at google.com - Homepage
Title
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Cited by
Year
FSD50K: an open dataset of human-labeled sound events
E Fonseca, X Favory, J Pons, F Font, X Serra
IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 829-852, 2021
4572021
Freesound datasets: a platform for the creation of open audio datasets
E Fonseca, J Pons Puig, X Favory, F Font Corbera, D Bogdanov, ...
Proceedings of the 18th ISMIR Conference; 2017; Suzhou, China, 2017
2692017
General-purpose tagging of freesound audio with audioset labels: Task description, dataset, and baseline
E Fonseca, M Plakal, F Font, DPW Ellis, X Favory, J Pons, X Serra
arXiv preprint arXiv:1807.09902, 2018
1922018
Learning sound event classifiers from web audio with noisy labels
E Fonseca, M Plakal, DPW Ellis, F Font, X Favory, X Serra
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
1332019
The benefit of temporally-strong labels in audio event classification
S Hershey, DPW Ellis, E Fonseca, A Jansen, C Liu, RC Moore, M Plakal
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
1112021
Hear: Holistic evaluation of audio representations
J Turian, J Shier, HR Khan, B Raj, BW Schuller, CJ Steinmetz, C Malloy, ...
NeurIPS 2021 Competitions and Demonstrations Track, 125-145, 2022
1032022
Audio tagging with noisy labels and minimal supervision
E Fonseca, M Plakal, F Font, DPW Ellis, X Serra
arXiv preprint arXiv:1906.02975, 2019
1032019
What’s all the fuss about free universal sound separation data?
S Wisdom, H Erdogan, DPW Ellis, R Serizel, N Turpault, E Fonseca, ...
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
942021
Unsupervised contrastive learning of sound event representations
E Fonseca, D Ortego, K McGuinness, NE O’Connor, X Serra
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
752021
Improving sound event detection in domestic environments using sound separation
N Turpault, S Wisdom, H Erdogan, J Hershey, R Serizel, E Fonseca, ...
arXiv preprint arXiv:2007.03932, 2020
662020
Audiovisual masked autoencoders
MI Georgescu, E Fonseca, RT Ionescu, M Lucic, C Schmid, A Arnab
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
442023
Sound event detection and separation: a benchmark on desed synthetic soundscapes
N Turpault, R Serizel, S Wisdom, H Erdogan, JR Hershey, E Fonseca, ...
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
392021
Acoustic scene classification by ensembling gradient boosting machine and convolutional neural networks
E Fonseca, R Gong, D Bogdanov, O Slizovskaia, E Gómez Gutiérrez, ...
Virtanen T, Mesaros A, Heittola T, Diment A, Vincent E, Benetos E, Martinez …, 2017
332017
Addressing missing labels in large-scale sound event recognition using a teacher-student framework with loss masking
E Fonseca, S Hershey, M Plakal, DPW Ellis, A Jansen, RC Moore
IEEE Signal Processing Letters 27, 1235-1239, 2020
292020
Self-supervised learning from automatically separated sound scenes
E Fonseca, A Jansen, DPW Ellis, S Wisdom, M Tagliasacchi, JR Hershey, ...
2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021
152021
Acoustic scene classification by fusing LightGBM and VGG-net multichannel predictions
R Gong, E Fonseca, D Bogdanov, O Slizovskaia, E Gomez, X Serra
Proc. IEEE AASP Challenge Detection Classification Acoust. Scenes Events, 1-4, 2017
142017
Description and analysis of novelties introduced in DCASE Task 4 2022 on the baseline system
F Ronchini, S Cornell, R Serizel, N Turpault, E Fonseca, DPW Ellis
arXiv preprint arXiv:2210.07856, 2022
122022
A simple fusion of deep and shallow learning for acoustic scene classification
E Fonseca, R Gong, X Serra
arXiv preprint arXiv:1806.07506, 2018
122018
Model-agnostic approaches to handling noisy labels when training sound event classifiers
E Fonseca, F Font, X Serra
arXiv preprint arXiv:1910.12004, 2019
112019
Improving sound event classification by increasing shift invariance in convolutional neural networks
E Fonseca, A Ferraro, X Serra
arXiv preprint arXiv:2107.00623, 2021
102021
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