Word Sense Disambiguation Improves Statistical Machine Translation 论文
2007引用 278
Natural Language Processing TechniquesTopic ModelingSpeech and dialogue systems
摘要
Recent research presents conflicting evi-dence on whether word sense disambigua-tion (WSD) systems can help to improve the performance of statistical machine transla-tion (MT) systems. In this paper, we suc-cessfully 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 sys-tem improves the performance of a state-of-the-art statistical MT system on an actual translation task. Furthermore, the improve-ment is statistically significant. 1