Paper: Grammatical Machine Translation

ACL ID N06-1032
Title Grammatical Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2006
Authors

We present an approach to statistical machine translation that combines ideas from phrase-based SMT and traditional grammar-based MT. Our system incor- porates the concept of multi-word trans- lation units into transfer of dependency structure snippets, and models and trains statistical components according to state- of-the-art SMT systems. Compliant with classical transfer-based MT, target depen- dency structure snippets are input to a grammar-based generator. An experimen- tal evaluation shows that the incorpora- tion of a grammar-based generator into an SMT framework provides improved gram- maticality while achieving state-of-the-art quality on in-coverage examples, suggest- ing a possible hybrid framework.