10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Efficient Combination of Confidence Measures for Machine Translation

Sylvain Raybaud, David Langlois, Kamel Smaïli

LORIA, France

We present in this paper a twofold contribution to Confidence Measures for Machine Translation. First, in order to train and test confidence measures, we present a method to automatically build corpora containing realistic errors. Errors introduced into reference translation simulate classical machine translation errors (word deletion and word substitution), and are supervised by Wordnet. Second, we use SVM to combine original and classical confidence measures both at word- and sentence-level. We show that the obtained combination outperforms by 14% (absolute) our best single word-level confidence measure, and that combination of sentence-level confidence measures produces meaningful scores.

Full Paper

Bibliographic reference.  Raybaud, Sylvain / Langlois, David / Smaïli, Kamel (2009): "Efficient combination of confidence measures for machine translation", In INTERSPEECH-2009, 424-427.