Finding structural correspondences from bilingual parsed corpus for corpus-based translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Evaluation of machine translation
HLT '93 Proceedings of the workshop on Human Language Technology
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Towards a simple and accurate statistical approach to learning translation relationships among words
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Overcoming the customization bottleneck using example-based MT
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Towards a simple and accurate statistical approach to learning translation relationships among words
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
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In the development of a machine translation system, one important issue is being able to adapt to a specific domain without requiring time-consuming lexical work. We have experimented with using a statistical word-alignment algorithm to derive word association pairs (French-English) that complement an existing multi-purpose bilingual dictionary. This word association information is added to the system at the time of the automatic creation of our translation pattern database, thereby making this database more domain specific. This technique significantly improves the overall quality of translation, as measured in an independent blind evaluation.