@article {13768,
	title = {Evaluation Techniques Applied to Domain Tuning of MT Lexicons},
	journal = {Proceedings of the Workshop {\textquotedblleft}Towards Systematizing MT Evaluation},
	volume = {27},
	year = {2003},
	month = {2003///},
	pages = {3 - 11},
	abstract = {We describe a set of evaluation techniques applied to domain tuning of bilingual lexicons for machine translation.Our overall objective is to translate a domain-specific document in a foreign language (in this case, Chinese) to En-
glish. First, we perform an intrinsic evaluation of the effectiveness of our domain-tuning techniques by comparing
our domain-tuned lexicon to a manually constructed domain-specific bilingual termlist. Our results indicate that we
achieve 66\% recall and 95\% precision with respect to a human-derived gold standard. Next, an extrinsic evaluation
demonstrates that our domain-tuned lexicon improves the Bleu scores 50\% over a statistical system{\textemdash}with a smaller
improvement when the system is trained on a uniformly-weighted dictionary.
},
	author = {Ayan,N.F. and Dorr, Bonnie J and Kolak,O.}
}
