@article {13714,
	title = {A study of translation edit rate with targeted human annotation},
	journal = {Proceedings of Association for Machine Translation in the Americas},
	year = {2006},
	month = {2006///},
	pages = {223 - 231},
	abstract = {We examine a new, intuitive measurefor evaluating machine-translation output
that avoids the knowledge intensiveness
of more meaning-based approaches, and
the labor-intensiveness of human judg-
ments. Translation Edit Rate (TER) mea-
sures the amount of editing that a hu-
man would have to perform to change
a system output so it exactly matches a
reference translation. We show that the
single-reference variant of TER correlates
as well with human judgments of MT
quality as the four-reference variant of
BLEU. We also define a human-targeted
TER (or HTER) and show that it yields
higher correlations with human judgments
than BLEU{\textemdash}even when BLEU is given
human-targeted references. Our results in-
dicate that HTER correlates with human
judgments better than HMETEOR and
that the four-reference variants of TER
and HTER correlate with human judg-
ments as well as{\textemdash}or better than{\textemdash}a sec-
ond human judgment does.
},
	author = {Snover,M. and Dorr, Bonnie J and Schwartz,R. and Micciulla,L. and Makhoul,J.}
}
