Numerical methods for retrieval and adaptation in Nagao’s EBMT model

Kun He, Tianjing Zhao, Yves Lepage

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

Abstract

We build an example-based machine translation system. It is an instance of case-based reasoning for machine translation. We introduce numerical methods instead of symbolic methods in two steps: retrieval and adaptation. For retrieval, we test three different approaches to define similarity between sentences. For adaptation, we use neural networks to solve analogies between sentences across languages. Oracle experiments allow to identify the best retrieval technique and to estimate the possibilities of such an approach. The system could place itself between a statistical and a neural machine translation systems on a task with not so large data.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages195-200
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 2019 Jan 17
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 2018 Oct 272018 Oct 28

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
CountryIndonesia
CityYogyakarta
Period18/10/2718/10/28

Keywords

  • Example-based machine translation
  • Numerical methods

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Library and Information Sciences
  • Artificial Intelligence
  • Information Systems

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