Modeling Word Formation in English-German Neural Machine Translation

Marion Weller-Di Marco, Alexander Fraser

ACL 2020

https://www.aclweb.org/anthology/2020.acl-main.389/

This paper studies strategies to model word formation in NMT using
rich linguistic information, namely a word segmentation approach that
goes beyond splitting into substrings by considering fusional
morphology. Our linguistically sound segmentation is combined with a
method for target-side inflection to accommodate modeling word
formation. The best system variants employ source-side morphological
analysis and model complex target-side words, improving over a
standard system.