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The peaky behavior of CTC models is well known experimentally.
A continuous speech recognition system embedding MLP into HMM
Bourlard, H. and Morgan, N · 1989
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Connectionist viterbi training: a new hybrid method for continuous speech recognition
Franzini, M., Lee, K.-F., and Waibel, A · 1990
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Global optimization of a neural network-hidden markov model hybrid
Bengio, Y., De Mori, R., Flammia, G., and Kompe, R · 1991
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Connectionist speech recognition with a global MMI algorithm
Haffner, P · 1993
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Forward-backward retraining of recurrent neural networks
Senior, A. and Robinson, T · 1996
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Estimation of global posteriors and forward-backward training of hybrid HMM/ANN systems
Hennebert, J., Ris, C., Bourlard, H., Renals, S., and Morgan, N · 1997
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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Speech recognition using neural networks with forward-backward probability generated targets
Yan, Y., Fanty, M., and Cole, R · 1997
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Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998
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Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
Graves, A., Fernández, S., Gomez, F., and Schmidhuber, J · 2006
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Asynchronous, online, GMM-free training of a context dependent acoustic model for speech recognition
Bacchiani, M., Senior, A. W., and Heigold, G · 2014
Cited alongside, same era.
Labeling unsegmented sequence data with DNN-HMM and its application for speech recognition
Li, X. and Wu, X · 2014
Cited alongside, same era.
GMM-free DNN acoustic model training
Senior, A., Heigold, G., Bacchiani, M., and Liao, H · 2014
Cited alongside, same era.
Standalone training of context-dependent deep neural network acoustic models
Zhang, C. and Woodland, P. C · 2014
Cited alongside, same era.
Deep Neural Networks for Large Vocabulary Handwritten Text Recognition
Bluche, T · 2015
Cited alongside, same era.
Framewise and CTC training of neural networks for handwriting recognition
Wav2letter: an end-to-end convnet-based speech recognition system
Collobert, R., Puhrsch, C., and Synnaeve, G · 2016
Later among the works it cites.
An empirical exploration of CTC acoustic models
Miao, Y., Gowayyed, M., Na, X., Ko, T., Metze, F., and Waibel, A · 2016
Later among the works it cites.
Maximum a posteriori based decoding for CTC acoustic models
Naoyuki Kanda, Xugang Lu, H. K · 2016
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Purely sequence-trained neural networks for ASR based on lattice-free MMI
Povey, D., Peddinti, V., Galvez, D., Ghahremani, P., Manohar, V., Na, X., Wang, Y., and Khudanpur, S · 2016
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SymPy: symbolic computing in Python
Meurer, A., Smith, C. P., Paprocki, M., Čertík, O., Kirpichev, S. B., Rocklin, M., Kumar, A., Ivanov, S., Moore, J. K., Singh, S., Rathnayake, T., Vig, S., Granger, B. E., Muller, R. P., Bonazzi, F., Gupta, H., Vats, S., Johansson, F., Pedregosa, F., Curry, M. J., Terrel, A. R., Roučka, v., Saboo, A., Fernando, I., Kulal, S., Cimrman, R., and Scopatz, A · 2017
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Bluche, T., Ney, H., Louradour, J., and Kermorvant, C · 2015
Cited alongside, same era.
Semi-supervised maximum mutual information training of deep neural network acoustic models
Manohar, V., Povey, D., and Khudanpur, S · 2015
Cited alongside, same era.
EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding
Miao, Y., Gowayyed, M., and Metze, F · 2015
Cited alongside, same era.
Fast and accurate recurrent neural network acoustic models for speech recognition
Sak, H., Senior, A., Rao, K., and Beaufays, F · 2015
Cited alongside, same era.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
TensorFlow Development Team · 2015
Cited alongside, same era.
Sequence transduction with recurrent neural networks
Graves, A
Cited in the paper.
Supervised Sequence Labelling with Recurrent Neural Networks , volume 385 of Studies in Computational Intelligence
Graves, A
Cited in the paper.
Recurrent neural aligner: An encoder-decoder neural network model for sequence to sequence mapping
Sak, H., Shannon, M., Rao, K., and Beaufays, F · 2017
Later among the works it cites.
CTC in the context of generalized full-sum HMM training
Zeyer, A., Beck, E., Schlüter, R., and Ney, H · 2017
Later among the works it cites.
The intriguing blank label in CTC
Bluche, T., Kermorvant, C., Ney, H., and Louradour, J · 2018
Later among the works it cites.
RETURNN as a generic flexible neural toolkit with application to translation and speech recognition
Zeyer, A., Alkhouli, T., and Ney, H · 2018
Later among the works it cites.