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Volumn 30, Issue 1, 2015, Pages 61-98

A survey on the application of recurrent neural networks to statistical language modeling

Author keywords

Language modeling; Machine translation; Natural language processing; Recurrent neural networks; Speech recognition

Indexed keywords

COMPUTATIONAL LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; SPEECH RECOGNITION; SPEECH TRANSMISSION; SURVEYS;

EID: 84913601027     PISSN: 08852308     EISSN: 10958363     Source Type: Journal    
DOI: 10.1016/j.csl.2014.09.005     Document Type: Review
Times cited : (227)

References (138)
  • 2
    • 84870486362 scopus 로고    scopus 로고
    • Revised N-gram based automatic spelling correction tool to improve retrieval effectiveness
    • F. Ahmed, E.W. De Luca, and A. Nürnberger Revised N-gram based automatic spelling correction tool to improve retrieval effectiveness Polibits 40 2009 39 48
    • (2009) Polibits , vol.40 , pp. 39-48
    • Ahmed, F.1    De Luca, E.W.2    Nürnberger, A.3
  • 4
    • 84897930752 scopus 로고    scopus 로고
    • Converting neural network language models into back-off language models for efficient decoding in automatic speech recognition
    • E. Arisoy, S.F. Chen, B. Ramabhadran, and A. Sethy Converting neural network language models into back-off language models for efficient decoding in automatic speech recognition IEEE/ACM Trans. Audio Speech Lang. Process. 22 1 2014 184 192
    • (2014) IEEE/ACM Trans. Audio Speech Lang. Process. , vol.22 , Issue.1 , pp. 184-192
    • Arisoy, E.1    Chen, S.F.2    Ramabhadran, B.3    Sethy, A.4
  • 8
    • 0033943206 scopus 로고    scopus 로고
    • A genetic algorithm to obtain the optimal recurrent neural network
    • A. Blanco, M. Delgado, and M.C. Pegalajar A genetic algorithm to obtain the optimal recurrent neural network Int. J. Approx. Reason. 23 1 2000 67 83
    • (2000) Int. J. Approx. Reason. , vol.23 , Issue.1 , pp. 67-83
    • Blanco, A.1    Delgado, M.2    Pegalajar, M.C.3
  • 9
    • 0030196364 scopus 로고    scopus 로고
    • Stacked regressions
    • L. Breiman Stacked regressions Mach. Learn. 24 1 1996 49 64
    • (1996) Mach. Learn. , vol.24 , Issue.1 , pp. 49-64
    • Breiman, L.1
  • 12
    • 84980642840 scopus 로고    scopus 로고
    • Boosted hybrid recurrent neural classifier for text document classification on the Reuters news text corpus
    • E. Buabin Boosted hybrid recurrent neural classifier for text document classification on the Reuters news text corpus Int. J. Mach. Learn. Comput. 2 5 2012 588 592
    • (2012) Int. J. Mach. Learn. Comput. , vol.2 , Issue.5 , pp. 588-592
    • Buabin, E.1
  • 13
    • 79951778871 scopus 로고    scopus 로고
    • Study on interaction between entropy pruning and Kneser-Ney smoothing
    • C. Chelba, T. Brants, W. Neveitt, and P. Xu Study on interaction between entropy pruning and Kneser-Ney smoothing Proceedings of Interspeech 2010 2242 2245
    • (2010) Proceedings of Interspeech , pp. 2242-2245
    • Chelba, C.1    Brants, T.2    Neveitt, W.3    Xu, P.4
  • 19
    • 0035058193 scopus 로고    scopus 로고
    • Improved language modelling through better language model evaluation measures
    • P. Clarkson, and T. Robinson Improved language modelling through better language model evaluation measures Comput. Speech Lang. 15 1 2001 39 53
    • (2001) Comput. Speech Lang. , vol.15 , Issue.1 , pp. 39-53
    • Clarkson, P.1    Robinson, T.2
  • 28
    • 84870293590 scopus 로고    scopus 로고
    • Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model
    • A. Deoras, T. Mikolov, S. Kombrink, and K. Church Approximate inference: a sampling based modeling technique to capture complex dependencies in a language model Speech Commun. 55 1 2013 162 177
    • (2013) Speech Commun. , vol.55 , Issue.1 , pp. 162-177
    • Deoras, A.1    Mikolov, T.2    Kombrink, S.3    Church, K.4
  • 31
    • 84891723531 scopus 로고    scopus 로고
    • Reservoir computing as an alternative to traditional artificial neural networks in rainfall-runoff modelling
    • Discussion 9
    • N.J. de Vos Reservoir computing as an alternative to traditional artificial neural networks in rainfall-runoff modelling Hydrol. Earth Syst. Sci. 2012 Discussion 9
    • (2012) Hydrol. Earth Syst. Sci.
    • De Vos, N.J.1
  • 33
    • 26444565569 scopus 로고
    • Finding structure in time
    • J.L. Elman Finding structure in time Cogn. Sci. 14 2 1990 179 211
    • (1990) Cogn. Sci. , vol.14 , Issue.2 , pp. 179-211
    • Elman, J.L.1
  • 40
    • 84874589571 scopus 로고    scopus 로고
    • Integrating models derived from non-parametric Bayesian co-segmentation into a statistical machine transliteration system
    • A. Finch, P. Dixon, and E. Sumita Integrating models derived from non-parametric Bayesian co-segmentation into a statistical machine transliteration system Proceedings of the Named Entities Workshop 2011 23 27
    • (2011) Proceedings of the Named Entities Workshop , pp. 23-27
    • Finch, A.1    Dixon, P.2    Sumita, E.3
  • 41
    • 85048273951 scopus 로고    scopus 로고
    • Rescoring a phrase-based machine transliteration system with recurrent neural network language models
    • A. Finch, P. Dixon, and E. Sumita Rescoring a phrase-based machine transliteration system with recurrent neural network language models NEWS'12 Proceedings of the 4th Named Entity Workshop 2012 47 51
    • (2012) NEWS'12 Proceedings of the 4th Named Entity Workshop , pp. 47-51
    • Finch, A.1    Dixon, P.2    Sumita, E.3
  • 43
    • 0033116017 scopus 로고    scopus 로고
    • Phoneme boundary estimation using bidirectional recurrent neural networks and its applications
    • T. Fukada, M. Schuster, and Y. Sagisaka Phoneme boundary estimation using bidirectional recurrent neural networks and its applications Syst. Comput. Jpn. 30 4 1999 20 30
    • (1999) Syst. Comput. Jpn. , vol.30 , Issue.4 , pp. 20-30
    • Fukada, T.1    Schuster, M.2    Sagisaka, Y.3
  • 44
    • 0035505385 scopus 로고    scopus 로고
    • LSTM recurrent networks learn simple context free and context sensitive languages
    • F.A. Gers, and J. Schmidhuber LSTM recurrent networks learn simple context free and context sensitive languages IEEE Trans. Neural Netw. 12 6 2001 1333 1340
    • (2001) IEEE Trans. Neural Netw. , vol.12 , Issue.6 , pp. 1333-1340
    • Gers, F.A.1    Schmidhuber, J.2
  • 47
    • 27744588611 scopus 로고    scopus 로고
    • Framewise phoneme classification with bidirectional LSTM and other neural network architectures
    • A. Graves, and J. Schmidhuber Framewise phoneme classification with bidirectional LSTM and other neural network architectures Neural Netw. 18 5-6 2005 602 610
    • (2005) Neural Netw. , vol.18 , Issue.56 , pp. 602-610
    • Graves, A.1    Schmidhuber, J.2
  • 50
    • 71249112130 scopus 로고    scopus 로고
    • Offline handwriting recognition with multidimensional recurrent neural networks
    • D. Koller, D. Schuurmans, Y. Bengio, L. Bottou, MIT Press
    • A. Graves, and J. Schmidhuber Offline handwriting recognition with multidimensional recurrent neural networks D. Koller, D. Schuurmans, Y. Bengio, L. Bottou, Advances in Neural Information Processing Systems 2009 MIT Press
    • (2009) Advances in Neural Information Processing Systems
    • Graves, A.1    Schmidhuber, J.2
  • 56
    • 85123792805 scopus 로고    scopus 로고
    • Named entity recognition with long short-term memory
    • J. Hammerton Named entity recognition with long short-term memory Proceedings of CoNLL-2003 2003 172 175
    • (2003) Proceedings of CoNLL-2003 , pp. 172-175
    • Hammerton, J.1
  • 58
    • 0031171679 scopus 로고    scopus 로고
    • Optimal linear combinations of neural networks
    • S. Hashem Optimal linear combinations of neural networks Neural Netw. 10 4 1997 599 614
    • (1997) Neural Netw. , vol.10 , Issue.4 , pp. 599-614
    • Hashem, S.1
  • 62
    • 84897743792 scopus 로고    scopus 로고
    • Learning representations for weakly supervised natural language processing tasks
    • F. Huang, A. Ahuja, D. Downey, Y. Yang, Y. Guo, and A. Yates Learning representations for weakly supervised natural language processing tasks Comput. Linguist. 40 1 2014 85 120
    • (2014) Comput. Linguist. , vol.40 , Issue.1 , pp. 85-120
    • Huang, F.1    Ahuja, A.2    Downey, D.3    Yang, Y.4    Guo, Y.5    Yates, A.6
  • 74
    • 84906217753 scopus 로고    scopus 로고
    • Measuring the influence of long range dependencies with neural network language models
    • H.-S. Le, A. Allauzen, and F. Yvon Measuring the influence of long range dependencies with neural network language models Proceedings of the NAACL-HLT 2012 Workshop 2012 1 10
    • (2012) Proceedings of the NAACL-HLT 2012 Workshop , pp. 1-10
    • Le, H.-S.1    Allauzen, A.2    Yvon, F.3
  • 76
    • 84878381641 scopus 로고    scopus 로고
    • Conversion of recurrent neural network language models to weighted finite state transducers for automatic speech recognition
    • G. Lecorvé, and P. Motlicek Conversion of recurrent neural network language models to weighted finite state transducers for automatic speech recognition Proceedings of Interspeech 2012 1666 1669
    • (2012) Proceedings of Interspeech , pp. 1666-1669
    • Lecorvé, G.1    Motlicek, P.2
  • 79
    • 68649088777 scopus 로고    scopus 로고
    • Reservoir computing approaches to recurrent neural network training
    • M. LukǒsevѤcius, and H. Jaeger Reservoir computing approaches to recurrent neural network training Comput. Sci. Rev. 3 3 2009 127 149
    • (2009) Comput. Sci. Rev. , vol.3 , Issue.3 , pp. 127-149
    • LukǒsevѤcius, M.1    Jaeger, H.2
  • 80
    • 0036834701 scopus 로고    scopus 로고
    • Real-time computing without stable states: A new framework for neural computation based on perturbations
    • W. Maass, T. Natschläger, and H. Markram Real-time computing without stable states: a new framework for neural computation based on perturbations Neural Comput. 14 11 2002 2531 2560
    • (2002) Neural Comput. , vol.14 , Issue.11 , pp. 2531-2560
    • Maass, W.1    Natschläger, T.2    Markram, H.3
  • 85
    • 84893412627 scopus 로고    scopus 로고
    • The IAM-database: An English sentence database for offline handwriting recognition
    • U.-V. Marti, and H. Bunke The IAM-database: an English sentence database for offline handwriting recognition Int. J. Doc. Anal. Recognit. 5 1 2002 39 46
    • (2002) Int. J. Doc. Anal. Recognit. , vol.5 , Issue.1 , pp. 39-46
    • Marti, U.-V.1    Bunke, H.2
  • 86
    • 0002235611 scopus 로고    scopus 로고
    • Adaptive topic-dependent language modelling using word-based varigrams
    • S.C. Martin, J. Liermann, and H. Ney Adaptive topic-dependent language modelling using word-based varigrams Proceedings of Eurospeech 1997 1447 1450
    • (1997) Proceedings of Eurospeech , pp. 1447-1450
    • Martin, S.C.1    Liermann, J.2    Ney, H.3
  • 95
    • 84898987069 scopus 로고    scopus 로고
    • Learning word embeddings efficiently with noise-contrastive estimation
    • A. Mnih, and K. Kavukcuoglu Learning word embeddings efficiently with noise-contrastive estimation Adv. Neural Inf. Process. Syst. 26 2013 2265 2273
    • (2013) Adv. Neural Inf. Process. Syst. , vol.26 , pp. 2265-2273
    • Mnih, A.1    Kavukcuoglu, K.2
  • 99
    • 34547997987 scopus 로고    scopus 로고
    • Hierarchical probabilistic neural network language model
    • F. Morin, and Y. Bengio Hierarchical probabilistic neural network language model Proceedings eAISTATS'05 2005 246 252
    • (2005) Proceedings eAISTATS'05 , pp. 246-252
    • Morin, F.1    Bengio, Y.2
  • 102
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods: An empirical study
    • D. Opitz, and R. Macline Popular ensemble methods: an empirical study J. Artif. Intell. Res. 11 1999 169 198
    • (1999) J. Artif. Intell. Res. , vol.11 , pp. 169-198
    • Opitz, D.1    Macline, R.2
  • 103
    • 84858769800 scopus 로고    scopus 로고
    • Behaviour analysis of multilayer perceptrons with multiple hidden neurons and hidden layers
    • G. Panchal, A. Ganatra, Y.P. Kosta, and D. Panchal Behaviour analysis of multilayer perceptrons with multiple hidden neurons and hidden layers Int. J. Comput. Theory Eng. 3 2011 332 337
    • (2011) Int. J. Comput. Theory Eng. , vol.3 , pp. 332-337
    • Panchal, G.1    Ganatra, A.2    Kosta, Y.P.3    Panchal, D.4
  • 107
    • 0032089995 scopus 로고    scopus 로고
    • A study of N-gram and decision tree letter language modeling methods
    • G. Potamianosa, and F. Jelinek A study of N-gram and decision tree letter language modeling methods Speech Commun. 24 3 1998 171 192
    • (1998) Speech Commun. , vol.24 , Issue.3 , pp. 171-192
    • Potamianosa, G.1    Jelinek, F.2
  • 110
    • 0027662338 scopus 로고
    • Pruning algorithms - A survey
    • R. Reed Pruning algorithms - a survey IEEE Trans. Neural Netw. 4 5 1993 740 747
    • (1993) IEEE Trans. Neural Netw. , vol.4 , Issue.5 , pp. 740-747
    • Reed, R.1
  • 112
    • 0028392167 scopus 로고
    • An application of recurrent neural nets to phone probability estimation
    • A.J. Robinson An application of recurrent neural nets to phone probability estimation IEEE Trans. Neural Netw. 5 2 1994 298 305
    • (1994) IEEE Trans. Neural Netw. , vol.5 , Issue.2 , pp. 298-305
    • Robinson, A.J.1
  • 115
    • 33646907991 scopus 로고    scopus 로고
    • Two decades of statistical language modeling: Where do we go from here
    • R. Rosenfeld Two decades of statistical language modeling: where do we go from here Proceedings of the IEEE 2000 1270 1278
    • (2000) Proceedings of the IEEE , pp. 1270-1278
    • Rosenfeld, R.1
  • 116
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • D.E. Rumelhart, J.L. McClelland, MIT Press
    • D.E. Rumelhart, G. Hinton, and R.J. Williams Learning internal representations by error propagation D.E. Rumelhart, J.L. McClelland, Parallel Distributed Processing 1986 MIT Press 318 362
    • (1986) Parallel Distributed Processing , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.2    Williams, R.J.3
  • 117
    • 34547898032 scopus 로고    scopus 로고
    • Recurrent neural networks are universal approximators
    • A.M. Schäfer, and H.G. Zimmerman Recurrent neural networks are universal approximators Int. J. Neural Syst. 17 4 2007 253 263
    • (2007) Int. J. Neural Syst. , vol.17 , Issue.4 , pp. 253-263
    • Schäfer, A.M.1    Zimmerman, H.G.2
  • 122
    • 85044798389 scopus 로고    scopus 로고
    • Continuous space language models for statistical machine translation
    • H. Schwenk Continuous space language models for statistical machine translation Prague Bull. Math. Linguist. 93 2010 137 146
    • (2010) Prague Bull. Math. Linguist. , vol.93 , pp. 137-146
    • Schwenk, H.1
  • 125
    • 84880153709 scopus 로고    scopus 로고
    • Review on methods to fix number of hidden neurons in neural networks
    • Article ID 425740
    • K.G. Sheela, and S.N. Deepa Review on methods to fix number of hidden neurons in neural networks Math. Prob. Eng. 2013 Article ID 425740
    • (2013) Math. Prob. Eng.
    • Sheela, K.G.1    Deepa, S.N.2
  • 130
    • 80053495924 scopus 로고    scopus 로고
    • Word representations: A simple and general method for semi-supervised learning
    • J. Turian, L. Ratinov, and Y. Bengio Word representations: a simple and general method for semi-supervised learning ACL 2010
    • (2010) ACL
    • Turian, J.1    Ratinov, L.2    Bengio, Y.3
  • 133
    • 3042527199 scopus 로고    scopus 로고
    • Offline recognition of unconstrained handwritten texts using HMMs and statistical language models
    • A. Vinciarelli, S. Bengio, and H. Bunke Offline recognition of unconstrained handwritten texts using HMMs and statistical language models IEEE Trans. Pattern Anal. Mach. Intell. 26 6 2004 709 720
    • (2004) IEEE Trans. Pattern Anal. Mach. Intell. , vol.26 , Issue.6 , pp. 709-720
    • Vinciarelli, A.1    Bengio, S.2    Bunke, H.3
  • 134
    • 24044495247 scopus 로고    scopus 로고
    • Combining statistical language models via the latent maximum entropy principle
    • S. Wang, D. Schuurmans, F. Peng, and Y. Zhao Combining statistical language models via the latent maximum entropy principle Mach. Learn. 60 1-3 2005 229 250
    • (2005) Mach. Learn. , vol.60 , Issue.13 , pp. 229-250
    • Wang, S.1    Schuurmans, D.2    Peng, F.3    Zhao, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.