Publication at Faculty of Mathematics and Physics |
2013
Abstract
One of the key obstacles in automatic evaluation of machine translation systems is the reliance on a few (typically just one) human-made reference translations to which the system output is compared. We propose a method of capturing millions of possible translations and implement a tool for translators to specify them using a compact representation.
We evaluate this new type of reference set by edit distance and correlation to human judgements of translation quality.