Improving Statistical Machine Translation Inflected Verb F

This paper introduces a rule-based classification of single-word and compound verbs into a statistical machine translation ap-proach. By substituting verb forms by the lemma of their head verb, the data sparseness problem caused by highly-inflected languages can be successfully addressed. On the other hand, the information of seen verb forms can be used to generate new translations for unseen verb forms. Translation results for an English to Spanish task are reported, producing a significant performance improvement. 1