| 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 | 13746 | 2012 |
| 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 | 2024 | 2015 |
| New types of deep neural network learning for speech recognition and related applications: An overview L Deng, G Hinton, B Kingsbury 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 1619 | 2013 |
| Low-rank matrix factorization for deep neural network training with high-dimensional output targets TN Sainath, B Kingsbury, V Sindhwani, E Arisoy, B Ramabhadran 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 791 | 2013 |
| Data augmentation for deep neural network acoustic modeling X Cui, V Goel, B Kingsbury IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (9), 1469 …, 2015 | 540 | 2015 |
| Boosted MMI for model and feature-space discriminative training D Povey, D Kanevsky, B Kingsbury, B Ramabhadran, G Saon, ... 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 499 | 2008 |
| fMPE: Discriminatively trained features for speech recognition D Povey, B Kingsbury, L Mangu, G Saon, H Soltau, G Zweig Proceedings.(ICASSP'05). IEEE International Conference on Acoustics, Speech …, 2005 | 371 | 2005 |
| Robust speech recognition using the modulation spectrogram BED Kingsbury, N Morgan, S Greenberg Speech communication 25 (1-3), 117-132, 1998 | 363 | 1998 |
| Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling B Kingsbury 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009 | 352 | 2009 |
| Improvements to deep convolutional neural networks for LVCSR TN Sainath, B Kingsbury, A Mohamed, GE Dahl, G Saon, H Soltau, ... 2013 IEEE workshop on automatic speech recognition and understanding, 315-320, 2013 | 311 | 2013 |
| Deep neural network language models E Arisoy, TN Sainath, B Kingsbury, B Ramabhadran Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the …, 2012 | 310 | 2012 |
| The modulation spectrogram: In pursuit of an invariant representation of speech S Greenberg, BED Kingsbury 1997 IEEE international conference on acoustics, speech, and signal …, 1997 | 299 | 1997 |
| Scalable Minimum Bayes Risk Training of Deep Neural Network Acoustic Models Using Distributed Hessian-free Optimization. B Kingsbury, TN Sainath, H Soltau Interspeech, 10-13, 2012 | 282 | 2012 |
| Very deep multilingual convolutional neural networks for LVCSR T Sercu, C Puhrsch, B Kingsbury, Y LeCun 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 277 | 2016 |
| Making deep belief networks effective for large vocabulary continuous speech recognition TN Sainath, B Kingsbury, B Ramabhadran, P Fousek, P Novak, ... 2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 30-35, 2011 | 246 | 2011 |
| Auto-encoder bottleneck features using deep belief networks TN Sainath, B Kingsbury, B Ramabhadran 2012 IEEE international conference on acoustics, speech and signal …, 2012 | 245 | 2012 |
| Audio-visual deep learning for noise robust speech recognition J Huang, B Kingsbury 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 228 | 2013 |
| Method and system for efficient spoken term detection using confusion networks BED Kingsbury, HK Kuo, L Mangu, H Soltau US Patent 9,196,243, 2015 | 224 | 2015 |
| Classifier-based system combination for spoken term detection BED Kingsbury, HKJ Kuo, LL Mangu, H Soltau US Patent 9,477,753, 2016 | 216 | 2016 |
| Learning filter banks within a deep neural network framework TN Sainath, B Kingsbury, A Mohamed, B Ramabhadran 2013 IEEE workshop on automatic speech recognition and understanding, 297-302, 2013 | 207 | 2013 |
George SaonDistinguished Research Staff Member, IBM Research AIVerified email at us.ibm.com
