Modeling Word Formation in English–German Neural Machine Translation
Marion Weller-Di Marco, Alexander Fraser
Machine Translation Short Paper
Session 7B: Jul 7
(09:00-10:00 GMT)
Session 8A: Jul 7
(12:00-13:00 GMT)
Abstract:
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.
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