Two Efficient Lattice Rescoring Methods Using Recurrent Neural Network Language Models
暂无分享,去创建一个
Yongqiang Wang | Mark J. F. Gales | Xunying Liu | Philip C. Woodland | Xie Chen | Xie Chen | P. Woodland | M. Gales | Yongqiang Wang | Xunying Liu
[1] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[2] Steve J. Young,et al. A One Pass Decoder Design For Large Vocabulary Recognition , 1994, HLT.
[3] Philip C. Woodland,et al. Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models , 1995, Comput. Speech Lang..
[4] Steve Young,et al. The development of the 1996 HTK broadcast news transcription system , 1996 .
[5] Thomas Niesler,et al. A variable-length category-based n-gram language model , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.
[6] Andreas G. Andreou,et al. Investigation of silicon auditory models and generalization of linear discriminant analysis for improved speech recognition , 1997 .
[7] Mehryar Mohri,et al. Finite-State Transducers in Language and Speech Processing , 1997, CL.
[8] Mark J. F. Gales,et al. Maximum likelihood linear transformations for HMM-based speech recognition , 1998, Comput. Speech Lang..
[9] Hermann Ney,et al. Dynamic programming search for continuous speech recognition , 1999, IEEE Signal Process. Mag..
[10] Daniel P. W. Ellis,et al. Tandem connectionist feature extraction for conventional HMM systems , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[11] Yoshua Bengio,et al. A Neural Probabilistic Language Model , 2003, J. Mach. Learn. Res..
[12] Gunnar Evermann,et al. Posterior probability decoding, confidence estimation and system combination , 2000 .
[13] Lidia Mangu,et al. Finding consensus in speech recognition , 2000 .
[14] Andreas Stolcke,et al. Finding consensus in speech recognition: word error minimization and other applications of confusion networks , 2000, Comput. Speech Lang..
[15] Mikael Bodén,et al. A guide to recurrent neural networks and backpropagation , 2001 .
[16] Daniel Povey,et al. Minimum Phone Error and I-smoothing for improved discriminative training , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[17] Andreas Stolcke,et al. Getting More Mileage from Web Text Sources for Conversational Speech Language Modeling using Class-Dependent Mixtures , 2003, NAACL.
[18] Mark J. F. Gales,et al. Automatic complexity control for HLDA systems , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[19] Mark J. F. Gales,et al. Training LVCSR systems on thousands of hours of data , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[20] Yoshua Bengio,et al. Hierarchical Probabilistic Neural Network Language Model , 2005, AISTATS.
[21] Holger Schwenk,et al. Continuous space language models , 2007, Comput. Speech Lang..
[22] Ahmad Emami,et al. Empirical study of neural network language models for Arabic speech recognition , 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).
[23] Mark J. F. Gales,et al. Use of contexts in language model interpolation and adaptation , 2009, Comput. Speech Lang..
[24] Mark J. F. Gales,et al. Language model combination and adaptation usingweighted finite state transducers , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.
[25] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[26] Mark J. F. Gales,et al. Improved neural network based language modelling and adaptation , 2010, INTERSPEECH.
[27] Dong Yu,et al. Improved Bottleneck Features Using Pretrained Deep Neural Networks , 2011, INTERSPEECH.
[28] Kenneth Ward Church,et al. A Fast Re-scoring Strategy to Capture Long-Distance Dependencies , 2011, EMNLP.
[29] Lukás Burget,et al. Extensions of recurrent neural network language model , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[30] Tomas Mikolov,et al. RNNLM - Recurrent Neural Network Language Modeling Toolkit , 2011 .
[31] Sanjeev Khudanpur,et al. Variational approximation of long-span language models for lvcsr , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[32] Dong Yu,et al. Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[33] Petr Motlícek,et al. Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition , 2012, INTERSPEECH.
[34] Hermann Ney,et al. LSTM Neural Networks for Language Modeling , 2012, INTERSPEECH.
[35] Geoffrey Zweig,et al. Accelerating recurrent neural network training via two stage classes and parallelization , 2013, 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.
[36] Geoffrey Zweig,et al. Joint Language and Translation Modeling with Recurrent Neural Networks , 2013, EMNLP.
[37] Geoffrey Zweig,et al. Recurrent neural networks for language understanding , 2013, INTERSPEECH.
[38] Yonghong Yan,et al. Prefix tree based n-best list re-scoring for recurrent neural network language model used in speech recognition system , 2013, INTERSPEECH.
[39] Yangyang Shi,et al. Speed up of recurrent neural network language models with sentence independent subsampling stochastic gradient descent , 2013, INTERSPEECH.
[40] Phil Blunsom,et al. Recurrent Continuous Translation Models , 2013, EMNLP.
[41] Kenneth Ward Church,et al. Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model , 2012, Speech Commun..
[42] Alexandre Allauzen,et al. Structured Output Layer Neural Network Language Models for Speech Recognition , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[43] Hermann Ney,et al. Comparison of feedforward and recurrent neural network language models , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[44] Richard M. Schwartz,et al. Fast and Robust Neural Network Joint Models for Statistical Machine Translation , 2014, ACL.
[45] Yongqiang Wang,et al. Efficient GPU-based training of recurrent neural network language models using spliced sentence bunch , 2014, INTERSPEECH.
[46] Daniele Falavigna,et al. Direct word graph rescoring using a* search and RNNLM , 2014, INTERSPEECH.
[47] Atsushi Nakamura,et al. Real-time one-pass decoding with recurrent neural network language model for speech recognition , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[48] Mark J. F. Gales,et al. Paraphrastic language models , 2014, Comput. Speech Lang..
[49] Hermann Ney,et al. Lattice decoding and rescoring with long-Span neural network language models , 2014, INTERSPEECH.
[50] Yu Wang,et al. Large scale recurrent neural network on GPU , 2014, 2014 International Joint Conference on Neural Networks (IJCNN).
[51] Geoffrey Zweig,et al. Cache based recurrent neural network language model inference for first pass speech recognition , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[52] Yongqiang Wang,et al. Efficient lattice rescoring using recurrent neural network language models , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[53] Mark J. F. Gales,et al. Paraphrastic recurrent neural network language models , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[54] Mark J. F. Gales,et al. Improving the training and evaluation efficiency of recurrent neural network language models , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[55] Hermann Ney,et al. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling , 2015, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[56] Mark J. F. Gales,et al. The Cambridge University 2014 BOLT conversational telephone Mandarin Chinese LVCSR system for speech translation , 2015, INTERSPEECH.