Publication at Faculty of Mathematics and Physics |
2011
Abstract
Accuracy of dependency parsers is one of the key factors limiting the quality of dependency-based machine translation. This paper deals with the influence of various dependency parsing approaches (and also different training data size) on the overall performance of an English-to-Czech dependency-based statistical translation system implemented in the Treex framework.
We also study the relationship between parsing accuracy in terms of unlabeled attachment score and machine translation quality in terms of BLEU.