A context-sensitive-chunk BPTT approach to training deep LSTM/BLSTM recurrent neural networks for offline handwriting recognition
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Zhi-Jie Yan | Qiang Huo | Kai Chen | Qiang Huo | Kai Chen | Zhijie Yan
[1] Jing Peng,et al. An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories , 1990, Neural Computation.
[2] Hervé Bourlard,et al. Connectionist Speech Recognition: A Hybrid Approach , 1993 .
[3] Ronald J. Williams,et al. Gradient-based learning algorithms for recurrent networks and their computational complexity , 1995 .
[4] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[5] Kuldip K. Paliwal,et al. Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..
[6] Jürgen Schmidhuber,et al. Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.
[7] Jürgen Schmidhuber,et al. Learning Precise Timing with LSTM Recurrent Networks , 2003, J. Mach. Learn. Res..
[8] Horst Bunke,et al. The IAM-database: an English sentence database for offline handwriting recognition , 2002, International Journal on Document Analysis and Recognition.
[9] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[10] Jürgen Schmidhuber,et al. Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition , 2005, ICANN.
[11] J. Schmidhuber,et al. A Novel Connectionist System for Unconstrained Handwriting Recognition , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Daniel Povey,et al. The Kaldi Speech Recognition Toolkit , 2011 .
[13] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[14] Navdeep Jaitly,et al. Hybrid speech recognition with Deep Bidirectional LSTM , 2013, 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.
[15] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[16] Thomas M. Breuel,et al. High-Performance OCR for Printed English and Fraktur Using LSTM Networks , 2013, 2013 12th International Conference on Document Analysis and Recognition.
[17] Andrew W. Senior,et al. Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.
[18] Navdeep Jaitly,et al. Towards End-To-End Speech Recognition with Recurrent Neural Networks , 2014, ICML.
[19] Hermann Ney,et al. Fast and Robust Training of Recurrent Neural Networks for Offline Handwriting Recognition , 2014, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[20] Christopher Kermorvant,et al. The A2iA Multi-lingual Text Recognition System at the Second Maurdor Evaluation , 2014, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[21] Georg Heigold,et al. Sequence discriminative distributed training of long short-term memory recurrent neural networks , 2014, INTERSPEECH.
[22] Hermann Ney,et al. A Comparison of Sequence-Trained Deep Neural Networks and Recurrent Neural Networks Optical Modeling for Handwriting Recognition , 2014, SLSP.
[23] Dong Yu,et al. Deep Learning: Methods and Applications , 2014, Found. Trends Signal Process..
[24] Hermann Ney,et al. Sequence-discriminative training of recurrent neural networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[25] Min Wang,et al. Building Handwriting Recognizers by Leveraging Skeletons of Both Offline and Online Samples , 2015, 2015 13th International Conference on Document Analysis and Recognition (ICDAR).