Abdelrahman Mohamed
Abdelrahman Mohamed
Research scientist, Facebook AI Research
Verified email at - Homepage
Cited by
Cited by
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
Speech recognition with deep recurrent neural networks
A Graves, A Mohamed, G Hinton
2013 IEEE international conference on acoustics, speech and signal …, 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
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
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
Acoustic modeling using deep belief networks
A Mohamed, G Dahl, G Hinton
Audio, Speech, and Language Processing, IEEE Transactions on, 1-1, 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
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
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
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
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
Unsupervised Cross-lingual Representation Learning for Speech Recognition
A Conneau, A Baevski, R Collobert, A Mohamed, M Auli
arXiv preprint arXiv:2006.13979, 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
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
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
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
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
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
Neuro-Symbolic Program Synthesis
E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli
arXiv preprint arXiv:1611.01855, 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
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