Paper: A Dependency Edge-based Transfer Model for Statistical Machine Translation

ACL ID C14-1104
Title A Dependency Edge-based Transfer Model for Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

Previous models in syntax-based statistical machine translation usually resort to some kinds of synchronous procedures, few of these works are based on the analysis-transfer-generation methodology. In this paper, we present a statistical implementation of the analysis-transfer- generation methodology in rule-based translation. The procedures of syntax analysis, syntax transfer and language generation are modeled independently in order to break the synchronous constraint, resorting to dependency structures with dependency edges as atomic manipulating units. Large-scale experiments on Chinese to English translation show that our model exhibits state-of-the-art performance by significantly outperforming the phrase-based model. The statis- tical transfer-generation method results in significan...