Rule-based Morphological Inflection Improves Neural Terminology Translation

Weijia Xu, Marine Carpuat


Abstract
Current approaches to incorporating terminology constraints in machine translation (MT) typically assume that the constraint terms are provided in their correct morphological forms. This limits their application to real-world scenarios where constraint terms are provided as lemmas. In this paper, we introduce a modular framework for incorporating lemma constraints in neural MT (NMT) in which linguistic knowledge and diverse types of NMT models can be flexibly applied. It is based on a novel cross-lingual inflection module that inflects the target lemma constraints based on the source context. We explore linguistically motivated rule-based and data-driven neural-based inflection modules and design English-German health and English-Lithuanian news test suites to evaluate them in domain adaptation and low-resource MT settings. Results show that our rule-based inflection module helps NMT models incorporate lemma constraints more accurately than a neural module and outperforms the existing end-to-end approach with lower training costs.
Anthology ID:
2021.emnlp-main.477
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5902–5914
Language:
URL:
https://aclanthology.org/2021.emnlp-main.477
DOI:
10.18653/v1/2021.emnlp-main.477
Bibkey:
Cite (ACL):
Weijia Xu and Marine Carpuat. 2021. Rule-based Morphological Inflection Improves Neural Terminology Translation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 5902–5914, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Rule-based Morphological Inflection Improves Neural Terminology Translation (Xu & Carpuat, EMNLP 2021)
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PDF:
https://aclanthology.org/2021.emnlp-main.477.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.477.mp4
Code
 izecson/terminology-translation