Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Radical Enhanced Chinese Word Embedding Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Research on Chinese-Tibetan Neural Machine Translation

Authors : Wen Lai, Xiaobing Zhao, Xiaqing Li

Published in: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

At present, the research on Tibetan machine translation is mainly focused on Tibetan-Chinese machine translation and the research on Chinese-Tibetan machine translation is almost blank. In this paper, the neural machine translation model is applied to the Chinese-Tibetan machine translation task for the first time, the syntax tree is also introduced into the Chinese-Tibetan neural machine translation model for the first time, and a good translation effect is achieved. Besides, the preprocessing methods we use are syllable segmentation on Tibetan corpus and character segmentation on Chinese Corpus, which has a better performance than the word segmentation on both Chinese and Tibetan corpus. The experimental results show that performance of the neural network translation model based on the completely self-attention mechanism is the best in the Chinese-Tibetan machine translation task and the BLEU score is increased by one percentage point.

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

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!

inform now
previous chapter Term Translation Extraction from Historical Classics Using Modern Chinese Explanation
next chapter Metadata Extraction for Scientific Papers
Literature
Liu, Y.: Recent advances in neural machine translation. J. Comput. Res. Dev. 54(6), 1144–1149 (2017). (in Chinese)
Zhao, T.: Machine Translation Theory. Harbin Institute of Technology Press (1900). (in Chinese)
Hinton, G.E., Osindero, S., Teh, Y.-W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527–1554 (2006)MathSciNetCrossRef
Wei, S.: Research on Tibetan - Chinese online translation system based on phrases. Dissertation, Northwest University for Nationalities (2015). (in Chinese)
Cai, Z., Cai, R.: Research on the distribution of tibetan character forms. J. Chin. Inf. Process. 30(4), 98–105 (2016). (in Chinese)MathSciNet
Dong, X., Cao, H., Jiang, T.: Phrase based Tibetan - Chinese statistical machine translation system. Technol. Wind 17, 60–61 (2012). (in Chinese)
Luo, X.: Research on syntax-based Chinese-Tibetan statistical machine translation system. Dissertation, Xiamen University (2010). (in Chinese)
Hua, Q.: Research on some key technologies of machine translation based on tree-to-string in tibetan language. Dissertation, Shanxi Normal University (2014a). (in Chinese)
Cai, R.: Research on large-scale Sino-Tibetan bilingual corpus construction for natural language processing. J. Chin. Inf. Process. 25(6), 157–162 (2011)
Pang, W.: Research on the construction technology of Tibetan-Chinese bilingual corpus of corpus based on web. Dissertation, Minzu University of China (2015). (in Chinese)
Xiang, B., Zhang, G.: Research on the translation of han names in Chinese-Tibetan machine translation. J. Qinghai Normal Univ. (Nat. Sci.) 27(4), 88–90 (2011)
Hua, G.: Tibetan verb researching in Chinese Tibetan machine translation. Dissertation, Qinghai Normal University (2014b). (in Chinese)
Nuo, M., Wu, J., Liu, H., Ding, Z.: Research on phrase translation extraction for Chinese-Tibetan machine translation. J. Chin. Inf. Process. 25(3), 112–118 (2011)
Li, Y., Xiong, D., Zhang, M., Jiang, J., Ma, N., Yin, J.: Research on Tibetan-Chinese neural machine translation. J. Chin. Inf. Process. 31(6), 103–109 (2017a)
Guan, Q.: Research on Tibetan segmentation for machine translation. Electron. Test 11x, 46–48 (2015)
Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: Advances in Neural Information Processing Systems (2014)
Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. Comput. Sci. (2014)
D’Informatique, D.E., Ese, N., Esent, P., et al.: Long short-term memory in recurrent neural networks. EPFL 9(8), 1735–1780 (2001)
Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. Comput. Sci. (2014)
Gehring, J., Auli, M., Grangier, D., et al.: Convolutional Sequence to Sequence Learning (2017)
Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems (2017)
Xue, Y., Li, S., Zhao, T., Yang, M.: Syntax-based reordering model for phrasal statistical machine translation. J. Commun. Test 29(1), 7–14 (2008)
Xiong, D., Liu, Q., Lin, S.: A survey of syntax-based statistic machine translation. J. Chin. Inf. Process. 22(2), 28–39 (2008)
Chen, H., et al.: Improved neural machine translation with a syntax-aware encoder and decoder, pp. 1936–1945 (2017)
Eriguchi, A., Tsuruoka, Y., Cho, K.: Learning to Parse and Translate Improves Neural Machine Translation (2017)
Li, J., et al.: Modeling Source Syntax for Neural Machine Translation, pp. 688–697 (2017b)
Aharoni, R., Goldberg, Y.: Towards String-to-Tree Neural Machine Translation (2017)
Xiao, T., et al.: NiuTrans: an open source toolkit for phrase-based and syntax-based machine translation. In: Proceedings of the ACL 2012 System Demonstrations. Association for Computational Linguistics (2012)
Sennrich, R., Haddow, B., Birch, A.: Neural machine translation of rare words with subword units. arXiv preprint arXiv:​1508.​07909 (2015)
Papineni, K., et al.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Association for Computational Linguistics (2002)
Li, Y., et al.: TIP-LAS: an open source toolkit for Tibetan word segmentation and POS tagging. J. Chin. Inf. Process. 29(6), 203–207 (2015)CrossRef
Li, Z., Sun, M.: Punctuation as implicit annotations for chinese word segmentation. Comput. Linguist. 35(4), 505–512 (2009)CrossRef
Petrov, S., et al.: Learning accurate, compact, and interpretable tree annotation. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics (2006)
Metadata
Title
Research on Chinese-Tibetan Neural Machine Translation
Authors
Wen Lai
Xiaobing Zhao
Xiaqing Li
Copyright Year
2018
Book
Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

Print ISBN: 978-3-030-01715-6

Electronic ISBN: 978-3-030-01716-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-01716-3_9

Premium Partner

    Image Credits