Analogy-based machine translation using secability

Tatsuya Kimura, Jin Matsuoka, Yusuke Nishikawa, Yves Lepage

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of reordering remains the main problem in machine translation. Computing structures of sentences and the alignment of substructures is a way that has been proposed to solve this problem. We use secability to compute structures and show its effectiveness in an example-based machine translation.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
PublisherIEEE Computer Society
Pages297-298
Number of pages2
Volume2
ISBN (Print)9781479930098
DOIs
Publication statusPublished - 2014
Event2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 - Las Vegas, NV
Duration: 2014 Mar 102014 Mar 13

Other

Other2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
CityLas Vegas, NV
Period14/3/1014/3/13

Keywords

  • Alignment
  • Example-based machine translation
  • Proportional analogy
  • Secability
  • Translation table

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

Cite this

Kimura, T., Matsuoka, J., Nishikawa, Y., & Lepage, Y. (2014). Analogy-based machine translation using secability. In Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 (Vol. 2, pp. 297-298). [6822353] IEEE Computer Society. https://doi.org/10.1109/CSCI.2014.142

Analogy-based machine translation using secability. / Kimura, Tatsuya; Matsuoka, Jin; Nishikawa, Yusuke; Lepage, Yves.

Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. Vol. 2 IEEE Computer Society, 2014. p. 297-298 6822353.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kimura, T, Matsuoka, J, Nishikawa, Y & Lepage, Y 2014, Analogy-based machine translation using secability. in Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. vol. 2, 6822353, IEEE Computer Society, pp. 297-298, 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014, Las Vegas, NV, 14/3/10. https://doi.org/10.1109/CSCI.2014.142
Kimura T, Matsuoka J, Nishikawa Y, Lepage Y. Analogy-based machine translation using secability. In Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. Vol. 2. IEEE Computer Society. 2014. p. 297-298. 6822353 https://doi.org/10.1109/CSCI.2014.142
Kimura, Tatsuya ; Matsuoka, Jin ; Nishikawa, Yusuke ; Lepage, Yves. / Analogy-based machine translation using secability. Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. Vol. 2 IEEE Computer Society, 2014. pp. 297-298
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