| 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 | 541 | 2021 |
| 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 | 291 | 2017 |
| 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 | 202 | 2018 |
| 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 | 148 | 2019 |
| 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 | 132 | 2021 |
| 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 | 111 | 2022 |
| Audio tagging with noisy labels and minimal supervision E Fonseca, M Plakal, F Font, DPW Ellis, X Serra arXiv preprint arXiv:1906.02975, 2019 | 109 | 2019 |
| 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 | 104 | 2021 |
| 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 | 84 | 2021 |
| 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 | 70 | 2020 |
| 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 | 56 | 2023 |
| 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 | 40 | 2021 |
| 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 | 31 | 2017 |
| 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 | 30 | 2020 |
| 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 | 15 | 2021 |
| 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 | 15 | 2017 |
| 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 | 14 | 2022 |
| Improving sound event classification by increasing shift invariance in convolutional neural networks E Fonseca, A Ferraro, X Serra arXiv preprint arXiv:2107.00623, 2021 | 14 | 2021 |
| A simple fusion of deep and shallow learning for acoustic scene classification E Fonseca, R Gong, X Serra arXiv preprint arXiv:1806.07506, 2018 | 12 | 2018 |
| Model-agnostic approaches to handling noisy labels when training sound event classifiers E Fonseca, F Font, X Serra arXiv preprint arXiv:1910.12004, 2019 | 11 | 2019 |
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), BarcelonaVerifierad e-postadress på upf.edu
Frederic FontMusic Technology Group, PhonosVerifierad e-postadress på upf.edu
Daniel P W EllisResearch Scientist, GoogleVerifierad e-postadress på google.com
Xavier FavoryAstraZeneca - Center for AIVerifierad e-postadress på astrazeneca.com
Manoj PlakalVerifierad e-postadress på cs.wisc.eduJustin SalamonSenior Research Scientist, Adobe ResearchVerifierad e-postadress på adobe.com
John HersheyGoogle (formerly MERL, IBM, MSR, UCSD)Verifierad e-postadress på google.com
Scott WisdomGoogle DeepMindVerifierad e-postadress på google.com
romain serizelAssociate professor, Université de Lorraine, LORIAVerifierad e-postadress på serizel.net
Nicolas TurpaultSonaideVerifierad e-postadress på sonaide.fr
Dmitry BogdanovMusic Technology Group, Universitat Pompeu FabraVerifierad e-postadress på upf.edu
Aren JansenGoogle DeepMindVerifierad e-postadress på google.com
Hakan ErdoganGoogleVerifierad e-postadress på google.com
Prem SeetharamanSr. Research Scientist, Adobe ResearchVerifierad e-postadress på adobe.com
Andres FerraroPandora SiriusXMVerifierad e-postadress på acm.org
Diego Ortego HernándezSenior Research Scientist, NielsenIQ (Spain)Verifierad e-postadress på nielseniq.com
Marco TagliasacchiResearch Scientist, Google