| MLS: A large-scale multilingual dataset for speech research V Pratap, Q Xu, A Sriram, G Synnaeve, R Collobert INTERSPEECH 2020, 21st Annual Conference of the International Speech …, 2020 | 493 | 2020 |
| End-to-end asr: from supervised to semi-supervised learning with modern architectures G Synnaeve, Q Xu, J Kahn, T Likhomanenko, E Grave, V Pratap, A Sriram, ... International Conference on Machine Learning - Workshop on Self-supervised …, 2019 | 276 | 2019 |
| Robust wav2vec 2.0: Analyzing domain shift in self-supervised pre-training WN Hsu, A Sriram, A Baevski, T Likhomanenko, Q Xu, V Pratap, J Kahn, ... INTERSPEECH 2021, 22nd Annual Conference of the International Speech …, 2021 | 251 | 2021 |
| Scaling speech technology to 1,000+ languages V Pratap, A Tjandra, B Shi, P Tomasello, A Babu, S Kundu, A Elkahky, ... Journal of Machine Learning Research 25 (97), 1-52, 2024 | 246 | 2024 |
| Wav2letter++: A fast open-source speech recognition system V Pratap, A Hannun, Q Xu, J Cai, J Kahn, G Synnaeve, V Liptchinsky, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 239 | 2019 |
| Massively Multilingual ASR: 50 languages, 1 model, 1 billion parameters V Pratap, A Sriram, P Tomasello, A Hannun, V Liptchinsky, G Synnaeve, ... INTERSPEECH 2020, 21st Annual Conference of the International Speech …, 2020 | 152 | 2020 |
| Rethinking evaluation in ASR: Are our models robust enough? T Likhomanenko, Q Xu, V Pratap, P Tomasello, J Kahn, G Avidov, ... INTERSPEECH 2021, 22nd Annual Conference of the International Speech …, 2020 | 105 | 2020 |
| Scaling up online speech recognition using convnets V Pratap, Q Xu, J Kahn, G Avidov, T Likhomanenko, A Hannun, ... INTERSPEECH 2020, 21st Annual Conference of the International Speech …, 2020 | 49 | 2020 |
| Differentiable weighted finite-state transducers A Hannun, V Pratap, J Kahn, WN Hsu arXiv preprint arXiv:2010.01003, 2020 | 34 | 2020 |
| Flashlight: Enabling innovation in tools for machine learning JD Kahn, V Pratap, T Likhomanenko, Q Xu, A Hannun, J Cai, P Tomasello, ... International Conference on Machine Learning, 10557-10574, 2022 | 25 | 2022 |
| Performance evaluation of offline speech recognition on edge devices S Gondi, V Pratap Electronics 10 (21), 2697, 2021 | 17 | 2021 |
| Performance and efficiency evaluation of ASR inference on the edge S Gondi, V Pratap Sustainability 13 (22), 12392, 2021 | 13 | 2021 |
| TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch J Hwang, M Hira, C Chen, X Zhang, Z Ni, G Sun, P Ma, R Huang, V Pratap, ... 2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 1-9, 2023 | 12 | 2023 |
| Star temporal classification: Sequence classification with partially labeled data V Pratap, A Hannun, G Synnaeve, R Collobert arXiv preprint arXiv:2201.12208, 2022 | 12* | 2022 |
| Customized keyword query suggestions on online social networks KS Hazra, VP Konduru US Patent 10,534,815, 2020 | 9 | 2020 |
| Word order does not matter for speech recognition V Pratap, Q Xu, T Likhomanenko, G Synnaeve, R Collobert ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 5 | 2022 |
| Scaling a simple approach to zero-shot speech recognition J Zhao, V Pratap, M Auli arXiv preprint arXiv:2407.17852, 2024 | 2 | 2024 |
| Less Peaky and More Accurate CTC Forced Alignment by Label Priors R Huang, X Zhang, Z Ni, L Sun, M Hira, J Hwang, V Manohar, V Pratap, ... ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 2 | 2024 |
| Parallel composition of weighted finite-state transducers S Sengupta, V Pratap, A Hannun ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 1 | 2022 |
| Improving Multilingual ASR in the Wild Using Simple N-best Re-ranking B Yan, V Pratap, S Watanabe, M Auli arXiv preprint arXiv:2409.18428, 2024 | | 2024 |
Gabriel SynnaeveResearch scientist at Facebook AI ResearchE-mail confirmado em fb.com