Paper: Anchor Graph: Global Reordering Contexts for Statistical Machine Translation

ACL ID D13-1048
Title Anchor Graph: Global Reordering Contexts for Statistical Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Reordering poses one of the greatest chal- lenges in Statistical Machine Translation re- search as the key contextual information may well be beyond the confine of translation units. We present the ?Anchor Graph? (AG) model where we use a graph structure to model global contextual information that is crucial for reordering. The key ingredient of our AG model is the edges that capture the relation- ship between the reordering around a set of selected translation units, which we refer to as anchors. As the edges link anchors that may span multiple translation units at decoding time, our AG model effectively encodes global contextual information that is previously ab- sent. We integrate our proposed model into a state-of-the-art translation system and demon- strate the efficacy of our proposa...