Improving statistical machine translation in the medical domain using the unified medical language system
Matthias Eck, Stephan Vogel, Alex Waibel · 2004
Texts from the medical domain are an important task for natural language processing. This paper investigates the usefulness of a large medical database (the Unified Medical Language System) for the translation of dialogues between doctors and patients using a statistical machine translation system. We are able to show that the extraction of a large dictionary and the usage of semantic type information to generalize the training data significantly improves the translation performance.