Improving statistical machine translation in the medical domain using the unified medical language system

Authors:
Matthias Eck;Stephan Vogel;Alex Waibel
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA
Venue:
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Year:
2004

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Abstract

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.