| Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ... IEEE Signal processing magazine 29 (6), 82-97, 2012 | 13397 | 2012 |
| Speech recognition with deep recurrent neural networks A Graves, A Mohamed, G Hinton 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 11385 | 2013 |
| Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension M Lewis, Y Liu, N Goyal, M Ghazvininejad, A Mohamed, O Levy, ... arXiv preprint arXiv:1910.13461, 2019 | 9723 | 2019 |
| wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations A Baevski, H Zhou, A Mohamed, M Auli arXiv preprint arXiv:2006.11477, 2020 | 4669 | 2020 |
| Convolutional neural networks for speech recognition O Abdel-Hamid, A Mohamed, H Jiang, L Deng, G Penn, D Yu IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 22 …, 2014 | 2786 | 2014 |
| Acoustic modeling using deep belief networks A Mohamed, G Dahl, G Hinton Audio, Speech, and Language Processing, IEEE Transactions on, 1-1, 2010 | 2231 | 2010 |
| Hybrid speech recognition with deep bidirectional LSTM A Graves, N Jaitly, A Mohamed 2013 IEEE workshop on automatic speech recognition and understanding, 273-278, 2013 | 2199 | 2013 |
| HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units WN Hsu, B Bolte, YHH Tsai, K Lakhotia, R Salakhutdinov, A Mohamed arXiv preprint arXiv:2106.07447, 2021 | 2137 | 2021 |
| Deep convolutional neural networks for large-scale speech tasks TN Sainath, B Kingsbury, G Saon, H Soltau, A Mohamed, G Dahl, ... Neural Networks 64, 39-48, 2015 | 1997 | 2015 |
| Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition O Abdel-Hamid, A Mohamed, H Jiang, G Penn 2012 IEEE international conference on Acoustics, speech and signal …, 2012 | 1220 | 2012 |
| SUPERB: Speech processing Universal PERformance Benchmark S Yang, PH Chi, YS Chuang, CIJ Lai, K Lakhotia, YY Lin, AT Liu, J Shi, ... arXiv preprint arXiv:2105.01051, 2021 | 731 | 2021 |
| Unsupervised Cross-lingual Representation Learning for Speech Recognition A Conneau, A Baevski, R Collobert, A Mohamed, M Auli arXiv preprint arXiv:2006.13979, 2020 | 691 | 2020 |
| Deep belief networks for phone recognition A Mohamed, G Dahl, G Hinton NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 2009 | 656 | 2009 |
| Libri-light: A benchmark for asr with limited or no supervision J Kahn, M Rivière, W Zheng, E Kharitonov, Q Xu, PE Mazaré, J Karadayi, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 559 | 2020 |
| Binary coding of speech spectrograms using a deep auto-encoder L Deng, ML Seltzer, D Yu, A Acero, A Mohamed, G Hinton Eleventh Annual Conference of the International Speech Communication Association, 2010 | 488 | 2010 |
| Phone recognition with the mean-covariance restricted Boltzmann machine GE Dahl, M Ranzato, A Mohamed, GE Hinton Advances in Neural Information Processing Systems 23, 469-477, 2010 | 445 | 2010 |
| Robustfill: Neural program learning under noisy I/O J Devlin, J Uesato, S Bhupatiraju, R Singh, A Mohamed, P Kohli Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 436 | 2017 |
| Deep belief networks using discriminative features for phone recognition A Mohamed, TN Sainath, G Dahl, B Ramabhadran, GE Hinton, ... 2011 IEEE international conference on acoustics, speech and signal …, 2011 | 404 | 2011 |
| Neuro-Symbolic Program Synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016 | 384 | 2016 |
| Understanding how deep belief networks perform acoustic modelling A Mohamed, G Hinton, G Penn 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 375 | 2012 |
Geoffrey HintonEmeritus Prof. Computer Science, University of Toronto在 cs.toronto.edu 的电子邮件经过验证
