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Convolutional neural networks (CNNs) are a standard component of many current state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) systems.
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“Speaker-independent isolated digit recognition: multilayer perceptrons vs. dynamic time warping,”
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S. Scanzio, P. Laface, L. Fissore, R. Gemello, and F. Mana, · 2008
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“Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling,”
Brian Kingsbury, · 2009
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“Investigation into bottle-neck features for meeting speech recognition.,”
F. Grezl, M. Karafiát, and L. Burget, · 2009
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“Understanding the difficulty of training deep feedforward neural networks,”
X. Glorot and Y. Bengio, · 2010
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“Conversational speech transcription using context-dependent deep neural networks.,”
F. Seide, G. Li, and D. Yu, · 2011
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“Deep belief networks using discriminative features for phone recognition,”
A.-r. Mohamed, T. N Sainath, G. Dahl, B. Ramabhadran, G. E Hinton, and Michael A P., · 2011
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“Traffic sign recognition with multi-scale convolutional networks,”
P. Sermanet and Y. LeCun, · 2011
Cited alongside, same era.
“Imagenet classification with deep convolutional neural networks,”
A. Krizhevsky, I. Sutskever, and G. E. Hinton, · 2012
Cited alongside, same era.
“Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition,”
O. Abdel-Hamid, A.-r. Mohamed, H. Jiang, and G. Penn, · 2012
Cited alongside, same era.
“Multilingual MLP features for low-resource LVCSR systems,”
S. Thomas, S. Ganapathy, and H. Hermansky, · 2012
Cited alongside, same era.
“ADADELTA: An adaptive learning rate method,”
M. D. Zeiler, · 2012
Cited alongside, same era.
“Pedestrian detection with unsupervised multi-stage feature learning,”
“Rich feature hierarchies for accurate object detection and semantic segmentation,”
R. Girshick, J. Donahue, T. Darrell, and J. Malik, · 2014
Later among the works it cites.
“Overfeat: Integrated recognition, localization and detection using convolutional networks,”
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, · 2014
Later among the works it cites.
“Joint training of convolutional and non-convolutional neural networks,”
H. Soltau, G. Saon, and T. N. Sainath, · 2014
Later among the works it cites.
“Depth map prediction from a single image using a multi-scale deep network,”
D. Eigen, C. Puhrsch, and R. Fergus, · 2014
Later among the works it cites.
“Very deep convolutional networks for large-scale image recognition,”
K. Simonyan and A. Zisserman, · 2015
Closest in time.
“The IBM 2015 english conversational telephone speech recognition system,”
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P. Sermanet, K. Kavukcuoglu, S. Chintala, and Y. LeCun, · 2013
Cited alongside, same era.
“Learning hierarchical features for scene labeling,”
C. Farabet, C. Couprie, L. Najman, and Y. LeCun, · 2013
Cited alongside, same era.
“Deep convolutional neural networks for lvcsr,”
T. N. Sainath, A.-r. Mohamed, B. Kingsbury, and B. Ramabhadran, · 2013
Cited alongside, same era.
“Investigation on cross-and multilingual MLP features under matched and mismatched acoustical conditions,”
Z. Tüske, J. Pinto, D. Willett, and R. Schlüter, · 2013
Cited alongside, same era.
“Investigation of multilingual deep neural networks for spoken term detection,”
K. M. Knill, M. J. F. Gales, S. P. Rath, P. C. Woodland, C. Zhang, and S.-X. Zhang, · 2013
Cited alongside, same era.
G. Saon, H.-K. Kuo, S. Rennie, and M. Picheny, · 2015
Closest in time.
“Very deep convolutional neural networks for LVCSR,”
M. Bi, Y. Qian, and K. Yu, · 2015
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“Fully convolutional networks for semantic segmentation,”
J. Long, E. Shelhamer, and T. Darrell, · 2015
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“Convolutional, long short-term memory, fully connected deep neural networks,”
T. N Sainath, O. Vinyals, A. Senior, and H. Sak, · 2015
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“Adam: A method for stochastic optimization,”
D. Kingma and J. Ba, · 2015
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