Acoustic modelling with CD-CTC-SMBR LSTM RNNS
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Tara N. Sainath | Andrew W. Senior | Hasim Sak | Kanishka Rao | Felix de Chaumont Quitry | A. Senior | T. Sainath | Kanishka Rao | H. Sak | F. D. C. Quitry
[1] Frank Fallside,et al. A recurrent error propagation network speech recognition system , 1991 .
[2] Jonathan G. Fiscus,et al. A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER) , 1997, 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings.
[3] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[4] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[5] Jürgen Schmidhuber,et al. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks , 2006, ICML.
[6] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[7] Izhak Shafran,et al. Context dependent phone models for LSTM RNN acoustic modelling , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[8] Andrew W. Senior,et al. Fast and accurate recurrent neural network acoustic models for speech recognition , 2015, INTERSPEECH.
[9] Tara N. Sainath,et al. Large vocabulary automatic speech recognition for children , 2015, INTERSPEECH.
[10] Tara N. Sainath,et al. Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[11] George Saon,et al. The IBM 2015 English conversational telephone speech recognition system , 2015, INTERSPEECH.
[12] Johan Schalkwyk,et al. Learning acoustic frame labeling for speech recognition with recurrent neural networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).