Brian Kingsbury
Brian Kingsbury
Distinguished Research Staff Member, IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
Verifierad e-postadress på us.ibm.com - Startsida
TitelCiteras avÅr
Deep neural networks for acoustic modeling in speech recognition
G Hinton, L Deng, D Yu, G Dahl, A Mohamed, N Jaitly, A Senior, ...
IEEE Signal processing magazine 29, 2012
63072012
Deep convolutional neural networks for LVCSR
TN Sainath, A Mohamed, B Kingsbury, B Ramabhadran
2013 IEEE international conference on acoustics, speech and signal …, 2013
7062013
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
5972013
Boosted MMI for model and feature-space discriminative training.
D Povey, D Kanevsky, B Kingsbury, B Ramabhadran, G Saon, ...
ICASSP 2008, 4057-4060, 2008
4122008
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
3492005
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
3282013
Robust speech recognition using the modulation spectrogram
BED Kingsbury, N Morgan, S Greenberg
Speech communication 25 (1-3), 117-132, 1998
2871998
Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling
B Kingsbury
2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009
2772009
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
2752015
Scalable minimum Bayes risk training of deep neural network acoustic models using distributed Hessian-free optimization
B Kingsbury, TN Sainath, H Soltau
Thirteenth Annual Conference of the International Speech Communication …, 2012
2332012
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
2331997
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
1992011
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
1772012
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
1692013
Auto-encoder bottleneck features using deep belief networks
TN Sainath, B Kingsbury, B Ramabhadran
2012 IEEE international conference on acoustics, speech and signal …, 2012
1692012
Data augmentation for deep neural network acoustic modeling
X Cui, V Goel, B Kingsbury
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 23 (9 …, 2015
1672015
Incorporating information from syllable-length time scales into automatic speech recognition
SL Wu, ED Kingsbury, N Morgan, S Greenberg
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech …, 1998
1621998
The IBM Attila speech recognition toolkit
H Soltau, G Saon, B Kingsbury
2010 IEEE Spoken Language Technology Workshop, 97-102, 2010
1512010
IEEE Signal Process
G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ...
Mag 29 (6), 82-97, 2012
1502012
Advances in speech transcription at IBM under the DARPA EARS program
SF Chen, B Kingsbury, L Mangu, D Povey, G Saon, H Soltau, G Zweig
IEEE Transactions on Audio, Speech, and Language Processing 14 (5), 1596-1608, 2006
1502006
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Artiklar 1–20