Recent research presents conflicting evidence on whether word sense disambiguation (WSD) systems can help to improve the performance of statistical machine translation (MT) systems. In this paper, we successfully integrate a state-of-the-art WSD system into a state-of-the-art hierarchical phrase-based MT system, Hiero. We show for the first time that integrating a WSD system improves the performance of a state-ofthe-art statistical MT system on an actual translation task. Furthermore, the improvement is statistically significant.
REF have made an effort to integrate a state-of-the-art WSD system into a state-of-the-art hierarchical phrase-based MT system, Hiero.
Word Sense Disambiguation Improves Statistical Machine Translation
45th Annual Meeting of the Association of Computational Linguistics
Computer Science