Skip to main content
SpringerLink
Log in
Book cover

International Conference on Applications of Natural Language to Information Systems

NLDB 2018: Natural Language Processing and Information Systems pp 494–497Cite as

Integration of Neural Machine Translation Systems for Formatting-Rich Document Translation

  • Conference paper
  • First Online:

  • 2488 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10859))

Abstract

In this paper, we present our work on integrating neural machine translation systems in the document translation workflow of the cloud-based machine translation platform Tilde MT. We describe the functionality of the translation workflow and provide examples for formatting-rich document translation.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    https://www.sdltrados.com.

  2. 2.

    https://memsource.com.

  3. 3.

    https://www.memoq.com.

  4. 4.

    http://docs.oasis-open.org/xliff.

References

  1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: Proceedings of ICLR 2015 (2015)

    Google Scholar 

  2. Escartın, C.P., Arcedillo, M.: Machine translation evaluation made fuzzier: a study on post-editing productivity and evaluation metrics in commercial settings. In: Proceedings of MT Summit XV, p. 131 (2015)

    Google Scholar 

  3. Federico, M., Bertoldi, N., Cettolo, M., Negri, M., Turchi, M., Trombetti, M., Cattelan, A., Farina, A., Lupinetti, D., Martines, A., et al.: The MateCat tool. In: Proceedings of COLING 2014: System Demonstrations, pp. 129–132 (2014)

    Google Scholar 

  4. Koehn, P., Och, F.J., Marcu, D.: Statistical phrase-based translation. In: Proceedings of NAACL-HLT 2003, vol. 1, pp. 48–54 (2003)

    Google Scholar 

  5. Lommel, A.R., DePalma, D.A.: Europe’s leading role in machine translation. Technical report, Common Sense Advisory (2016)

    Google Scholar 

  6. Pinnis, M., Krišlauks, R., Deksne, D., Miks, T.: Neural machine translation for morphologically rich languages with improved sub-word units and synthetic data. In: Ekštein, K., Matoušek, V. (eds.) TSD 2017. LNCS (LNAI), vol. 10415, pp. 237–245. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-64206-2_27

    Chapter  Google Scholar 

  7. Sanchez-Torron, M., Koehn, P.: Machine translation quality and post-editor productivity. AMTA 2016, 16 (2016)

    Google Scholar 

  8. Sennrich, R., Haddow, B., Birch, A.: Neural machine translation of rare words with subword units. In: Proceedings of ACL 2015. Association for Computational Linguistics, Berlin (2015)

    Google Scholar 

  9. Skadina, I., Pinnis, M.: NMT or SMT: case study of a narrow-domain English-Latvian post-editing project. In: Proceedings of IJCNLP 2017 (Volume 1: Long Papers), pp. 373–383 (2017)

    Google Scholar 

  10. Vasiljevs, A., Skadinš, R., Tiedemann, J.: LetsMT!: a cloud-based platform for do-it-yourself machine translation. In: Proceedings of the ACL 2012 System Demonstrations, pp. 43–48, July 2012

    Google Scholar 

Download references

Acknowledgments

The research has been supported by the “Forest Sector Competence Centre” within the project “Forestry industry communication technologies” of EU Structural funds, ID n\(^{\circ }\) 1.2.1.1/16/A/009.

Author information

Authors and Affiliations

  1. Tilde, Vienības gatve 75A, Riga, 1004, Latvia

    Mārcis Pinnis, Raivis Skadiņš, Valters Šics & Toms Miks

Authors
  1. Mārcis Pinnis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raivis Skadiņš
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Valters Šics
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Toms Miks
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mārcis Pinnis .

Editor information

Editors and Affiliations

  1. Université de Franche-Comté, Besançon, France

    Max Silberztein

  2. Conservatoire National des Arts et Métiers, Paris, France

    Faten Atigui

  3. Conservatoire National des Arts et Métiers, Paris, France

    Elena Kornyshova

  4. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

  5. University of Salford, Manchester, United Kingdom

    Farid Meziane

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pinnis, M., Skadiņš, R., Šics, V., Miks, T. (2018). Integration of Neural Machine Translation Systems for Formatting-Rich Document Translation. In: Silberztein, M., Atigui, F., Kornyshova, E., Métais, E., Meziane, F. (eds) Natural Language Processing and Information Systems. NLDB 2018. Lecture Notes in Computer Science(), vol 10859. Springer, Cham. https://doi.org/10.1007/978-3-319-91947-8_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-91947-8_51

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91946-1

  • Online ISBN: 978-3-319-91947-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation