| 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 | 14125 | 2012 |
| Speech recognition with deep recurrent neural networks A Graves, A Mohamed, G Hinton 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 12142 | 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 | 12085 | 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 | 6391 | 2020 |
| 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 | 3208 | 2021 |
| 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 | 3007 | 2014 |
| 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 | 2358 | 2013 |
| Acoustic modeling using deep belief networks A Mohamed, G Dahl, G Hinton Audio, Speech, and Language Processing, IEEE Transactions on, 1-1, 2010 | 2290 | 2010 |
| 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 | 2052 | 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 | 1266 | 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 | 969 | 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 | 895 | 2020 |
| 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 | 730 | 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 | 684 | 2009 |
| 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 | 506 | 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 | 470 | 2017 |
| 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 | 449 | 2010 |
| Neuro-Symbolic Program Synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016 | 411 | 2016 |
| 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 | 411 | 2011 |
| Self-Supervised Speech Representation Learning: A Review A Mohamed, H Lee, L Borgholt, JD Havtorn, J Edin, C Igel, K Kirchhoff, ... arXiv preprint arXiv:2205.10643, 2022 | 407 | 2022 |
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoVerified email at cs.toronto.edu
