| An empirical study on evaluation metrics of generative adversarial networks Q Xu, G Huang, Y Yuan, C Guo, Y Sun, F Wu, K Weinberger arXiv preprint arXiv:1806.07755, 2018 | 163* | 2018 |
| 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 | 125 | 2019 |
| End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures G Synnaeve*, Q Xu*, J Kahn*, E Grave*, T Likhomanenko, V Pratap, ... arXiv preprint arXiv:1911.08460, 2019 | 105 | 2019 |
| Libri-Light: A Benchmark for ASR with Limited or No Supervision J Kahn*, M Rivière*, W Zheng*, E Kharitonov*, Q Xu*, PE Mazaré*, ... arXiv preprint arXiv:1912.07875, 2019 | 96 | 2019 |
| Fully convolutional speech recognition N Zeghidour*, Q Xu*, V Liptchinsky, N Usunier, G Synnaeve, R Collobert arXiv preprint arXiv:1812.06864, 2018 | 70 | 2018 |
| Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions A Hannun, A Lee, Q Xu, R Collobert arXiv preprint arXiv:1904.02619, 2019 | 69* | 2019 |
| Mls: A large-scale multilingual dataset for speech research V Pratap, Q Xu, A Sriram, G Synnaeve, R Collobert arXiv preprint arXiv:2012.03411, 2020 | 34 | 2020 |
| Iterative pseudo-labeling for speech recognition Q Xu, T Likhomanenko, J Kahn, A Hannun, G Synnaeve, R Collobert arXiv preprint arXiv:2005.09267, 2020 | 33 | 2020 |
| Self-training and Pre-training are Complementary for Speech Recognition Q Xu*, A Baevski*, T Likhomanenko, P Tomasello, A Conneau, ... arXiv preprint arXiv:2010.11430, 2020 | 24 | 2020 |
| Self-training for end-to-end speech translation J Pino, Q Xu, X Ma, MJ Dousti, Y Tang arXiv preprint arXiv:2006.02490, 2020 | 21 | 2020 |
| Scaling Up Online Speech Recognition Using ConvNets V Pratap, Q Xu, J Kahn, G Avidov, T Likhomanenko, A Hannun, ... arXiv preprint arXiv:2001.09727, 2020 | 21 | 2020 |
| slimipl: Language-model-free iterative pseudo-labeling T Likhomanenko, Q Xu, J Kahn, G Synnaeve, R Collobert arXiv preprint arXiv:2010.11524, 2020 | 15 | 2020 |
| Rethinking Evaluation in ASR: Are Our Models Robust Enough? T Likhomanenko*, Q Xu*, V Pratap, P Tomasello, J Kahn, G Avidov, ... arXiv preprint arXiv:2010.11745, 2020 | 10 | 2020 |
| Learning a repression network for precise vehicle search Q Xu, K Yan, Y Tian arXiv preprint arXiv:1708.02386, 2017 | 9 | 2017 |
| 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, ... arXiv preprint arXiv:2104.01027, 2021 | 8 | 2021 |
| Spectral Frank-Wolfe algorithm: Strict complementarity and linear convergence L Ding, Y Fei, Q Xu, C Yang International Conference on Machine Learning, 2535-2544, 2020 | 8 | 2020 |
| Effects of meteorological factors on finger vein recognition H Zheng*, Q Xu*, Y Ye, W Li 2017 IEEE International Conference on Identity, Security and Behavior …, 2017 | 8 | 2017 |
| CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings T Likhomanenko, Q Xu, R Collobert, G Synnaeve, A Rogozhnikov arXiv preprint arXiv:2106.03143, 2021 | 2 | 2021 |
| Simple and Effective Zero-shot Cross-lingual Phoneme Recognition Q Xu, A Baevski, M Auli arXiv preprint arXiv:2109.11680, 2021 | 1 | 2021 |
| Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition V Manohar, T Likhomanenko, Q Xu, WN Hsu, R Collobert, Y Saraf, ... arXiv preprint arXiv:2106.07759, 2021 | 1 | 2021 |
Ronan CollobertFacebook AI ResearchVerified email at collobert.com
