Paper: Using a Dependency Parser to Improve SMT for Subject-Object-Verb Languages

ACL ID N09-1028
Title Using a Dependency Parser to Improve SMT for Subject-Object-Verb Languages
Venue Human Language Technologies
Session Main Conference
Year 2009
Authors

We introduce a novel precedence reordering approach based on a dependency parser to sta- tistical machine translation systems. Similar to other preprocessing reordering approaches, our method can efficiently incorporate linguis- tic knowledge into SMT systems without in- creasing the complexity of decoding. For a set of five subject-object-verb (SOV) order lan- guages, we show significant improvements in BLEU scores when translating from English, compared to other reordering approaches, in state-of-the-art phrase-based SMT systems.