nach oben

Erschienen in:

2017 | OriginalPaper | Buchkapitel

Statistical Machine Translation Context Modelling with Recurrent Neural Network and LDA

verfasst von : Shrooq Alsenan, Mourad Ykhlef

Erschienen in: Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Machine Translation of text is a fundamental problem in machine learning that resists solutions that do not take into account the dependencies between words and sentences. Recurrent Neural Networks have recently delivered outstanding results in learning about sequential dependencies in many languages. Arabic language as a target language has not received enough attention in the recent language model experiments due to its, structural and semantic difficulties. In this paper, we present a Statistical Machine Translation (SMT) Context Modelling using Recurrent Neural Networks (RNNs) and Latent Dirichlet Allocation (LDA). This research is based on the state-of-the-art RNN language model by Mikolov. Our preliminary contribution is in integrating and presenting a new hybridization to utilize Recurrent Neural Network sequential word learning dependencies as well as Latent Dirichlet Allocation context and topic classification ability to produce the most accurate language scoring.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel A New Method for Interoperability Between Lexical Resources Using MDA Approach

Nächstes Kapitel Optimizing Fuzzy Inference Systems for Improving Speech Emotion Recognition

Callison-Burch, C., Talbot, D., Osborne, M.: Statistical machine translation with word-and sentence-aligned parallel corpora. In: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, p. 175 (2004)

Durrani, N., Fraser, A., Schmid, H.: Model with minimal translation units, but decode with phrases. In: Proceedings of NAACL-HLT, 9–14 June 2013, Atlanta, Georgia (2013)

Brown, P., de Souza, P., Mercer, R., Pietra, V., Lai, J.: Class-based n-gram models of natural language. Computational Linguistics. Comput. Linguist. 18(4), 467–479 (1992)

Lipton, Z., Berkowitz, J., Elkan, C.: A Critical review of recurrent neural networks for sequence learning’, arXiv preprint arXiv:1506.00019 (2015)

Farabet, C., Couprie, C., Najman, L., LeCun, Y.: Learning hierarchical features for scene labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 1915–1929 (2013)CrossRef

Zhao, B., Tam, Y.: Bilingual recurrent neural networks for improved statistical machine translation. In: Spoken Language Technology Workshop (SLT), 7–10 December 2014, South Lake Tahoe, NV. IEEE (2014)

Sundermeyer, M., Alkhouli, T., Wuebker, J., Ney, H.: Translation modeling with bidirectional recurrent neural networks. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 14–25 October 2014, Doha, Qatar (2014)

Hopfield, J.J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Nat. Acad. Sci. 79(8), 2554–2558 (1982)MathSciNetCrossRef

Jordan, M.: Serial order: a parallel distributed processing approach. Technical report 8604, Institute for Cognitive Science, University of California, San Diego (1986)

10.

Elman, J.: Finding structure in time. Cogn. Sci. 14, 179–211 (1990)CrossRef

11.

Mikolov, T., Zweig, G.: Context dependent recurrent neural network language model. In: 2012 workshop on Spoken Language Technology, pp. 234–239 (2012)

12.

Kombrink, S., Mikolov, T., Karafiat, M., Burget, L.: Recurrent neural network based language model. In: INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, Makuhari, Chiba, Japan, 26–30 September 2010, pp. 1045–1048 (2010)

13.

Kalchbrenner, N., Blunsom, P.: Recurrent continuous translation models. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, October 2013, Seattle, Washington, USA, pp. 1700–1709 (2013)

14.

Liu, S., Yang, N., Li, Zhou, M.: A recursive recurrent neural network for statistical machine translation. In: Proceedings of ACL, pp. 1491–1550 (2014)

15.

Hu, Y., Auli, M., Gao, Q., Gao, J.: Minimum translation modeling with recurrent neural networks. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, April 2014

16.

Schuster, M., Paliwal, K.: Bidirectional recurrent neural networks. IEEE Trans. Signal Process. 45(11), 2673–2681 (1997)CrossRef

17.

Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735–1780 (1997)CrossRef

18.

Schwenk, H.: Continuous space translation models for phrase-based statistical machine translation. In: 25th International Conference on Computational Linguistics (COLING), December, Mumbai, India, pp. 1071–1080 (2012)

19.

Mikolov, T.: Statistical Language Models Based on Neural Networks. Ph.D., Brno University of Technology (2012)

20.

Arabic Gigaword Corpus. https://catalog.ldc.upenn.edu/LDC2011T11

21.

Mikolov, T.: RNNLM Toolkit (2012). http://www.rnnlm.org/. Accessed: 28 Nov 2015

22.

Guessabi, F.: The cultural problems in translating a novel from arabic to english language. AWEJ Special Issue on Translation (2), 224–232 (2013)

23.

https://ar.wikipedia.org/wiki/. Accessed: 20 Dec 2015

24.

Ponweiser, M.: Latent dirichlet allocation in R. Diploma Thesis, Institute for Statistics and Mathematics 2 May 2012

25.

Zhengxian, G., Guodong, Z.: Employing topic modeling for statistical machine translation. In: 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE (2011)

Titel: Statistical Machine Translation Context Modelling with Recurrent Neural Network and LDA
verfasst von: Shrooq Alsenan
Mourad Ykhlef
Verlag: Springer International Publishing
Buch: Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016
Print ISBN: 978-3-319-48307-8

Electronic ISBN: 978-3-319-48308-5

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-48308-5_8

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"