Facilitating Terminology Translation with Target Lemma Annotations

Toms Bergmanis, Mārcis Pinnis


Abstract
Most of the recent work on terminology integration in machine translation has assumed that terminology translations are given already inflected in forms that are suitable for the target language sentence. In day-to-day work of professional translators, however, it is seldom the case as translators work with bilingual glossaries where terms are given in their dictionary forms; finding the right target language form is part of the translation process. We argue that the requirement for apriori specified target language forms is unrealistic and impedes the practical applicability of previous work. In this work, we propose to train machine translation systems using a source-side data augmentation method that annotates randomly selected source language words with their target language lemmas. We show that systems trained on such augmented data are readily usable for terminology integration in real-life translation scenarios. Our experiments on terminology translation into the morphologically complex Baltic and Uralic languages show an improvement of up to 7 BLEU points over baseline systems with no means for terminology integration and an average improvement of 4 BLEU points over the previous work. Results of the human evaluation indicate a 47.7% absolute improvement over the previous work in term translation accuracy when translating into Latvian.
Anthology ID:
2021.eacl-main.271
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3105–3111
Language:
URL:
https://aclanthology.org/2021.eacl-main.271
DOI:
10.18653/v1/2021.eacl-main.271
Bibkey:
Cite (ACL):
Toms Bergmanis and Mārcis Pinnis. 2021. Facilitating Terminology Translation with Target Lemma Annotations. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 3105–3111, Online. Association for Computational Linguistics.
Cite (Informal):
Facilitating Terminology Translation with Target Lemma Annotations (Bergmanis & Pinnis, EACL 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/update-css-js/2021.eacl-main.271.pdf
Code
 tilde-nlp/terminology_translation