Title

Augmenting Manual Dictionaries for Statistical Machine Translation Systems

Author(s)

Stephan Vogel, Christian Monson

Language Technologies Institute, Carnegie Mellon University

Session

O36-SW

Abstract

We show that the usefulness of manually created dictionaries can be enhanced for a statistical machine translation system when new translations are automatically added which are simple morphological transformations (plural forms, different verb inflections) of the original. Further improvement is possible when assigning probabilities to the lexicon entries. We describe a method to do this on the basis of an automatically trained statistical lexicon. Experimental results are given for Chinese to English translation tasks and show a significant improvement in translation quality.

Keyword(s)

Dictionary, statistical machine translation

Language(s) Chinese, English
Full Paper

543.pdf