Rule-based Morphological Inflection Improves Neural Terminology Translation (2021.emnlp-main)
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| Challenge: | Current approaches to incorporating terminology constraints in machine translation (MT) typically assume that the constraint terms are provided in their correct morphological forms. |
| Approach: | They propose a framework for incorporating lemma constraints in machine translation . they use a cross-lingual inflection module that inflects the target lemmo constraints based on the source context. |
| Outcome: | The proposed framework outperforms existing methods with lower training costs and linguistic knowledge in domain adaptation and low-resource MT settings. |
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