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Part of
Recent Advances in Multiword Units in Machine Translation and Translation Technology
Edited by Johanna Monti, Gloria Corpas Pastor, Ruslan Mitkov and Carlos Manuel Hidalgo-Ternero
[Current Issues in Linguistic Theory 366] 2024
► pp. 18–39

Chapter 2
ReGap

A text-preprocessing algorithm to enhance MWE-aware neural machine translation systems

| Universidad de Málaga |
| Universidad de Málaga
This research presents ReGap, a text-preprocessing algorithm for the automatic token-based identification and conversion of discontinuous multiword expressions (MWEs) into their canonical state, i.e., their continuous form, as a means to optimise neural machine translation (NMT) systems. To this end, an experiment with flexible verb-noun idiomatic constructions (VNICs) is conducted in order to assess to what extent ReGap can enhance the performance of the most robust NMT system to date, DeepL, under the challenge of MWE discontinuity in the Spanish-into-English and the Spanish-into-German directionalities. In this regard, the promising results yielded for VNICs will shed some light on new avenues for enhancing MWE-aware NMT systems.
Keywords: Text-preprocessing algorithm, Neural Machine Translation (NMT), DeepL, Token-based MWE identification, Verb-noun idiomatic constructions (VNICs), discontinuity
Article outline
  • 1.Introduction
  • 2.The MWEs under study
  • 3.Related work
  • 4.Methodology
  • 5.Results
  • 6.Discussion
  • 7.Conclusion
  • Notes
  • References
This content is being prepared for publication; it may be subject to changes.
References (50)
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