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
68532012
Deep convolutional neural networks for LVCSR
TN Sainath, A Mohamed, B Kingsbury, B Ramabhadran
2013 IEEE international conference on acoustics, speech and signal …, 2013
7652013
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
6512013
Boosted MMI for model and feature-space discriminative training.
D Povey, D Kanevsky, B Kingsbury, B Ramabhadran, G Saon, ...
ICASSP 2008, 4057-4060, 2008
4272008
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
3552013
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
3522005
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
3042015
Robust speech recognition using the modulation spectrogram
BED Kingsbury, N Morgan, S Greenberg
Speech communication 25 (1-3), 117-132, 1998
2961998
Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling
B Kingsbury
2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009
2842009
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
2392012
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
2371997
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
2022011
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
1932015
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
1932012
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
1742013
Auto-encoder bottleneck features using deep belief networks
TN Sainath, B Kingsbury, B Ramabhadran
2012 IEEE international conference on acoustics, speech and signal …, 2012
1722012
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
1641998
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
1632016
IEEE Signal Process
G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ...
Mag 29 (6), 82-97, 2012
1612012
The IBM Attila speech recognition toolkit
H Soltau, G Saon, B Kingsbury
2010 IEEE Spoken Language Technology Workshop, 97-102, 2010
1552010
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Artiklar 1–20