Paper: A New String-to-Dependency Machine Translation Algorithm with a Target Dependency Language Model

ACL ID P08-1066
Title A New String-to-Dependency Machine Translation Algorithm with a Target Dependency Language Model
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

In this paper, we propose a novel string-to- dependency algorithm for statistical machine translation. With this new framework, we em- ploy a target dependency language model dur- ing decoding to exploit long distance word relations, which are unavailable with a tra- ditional n-gram language model. Our ex- periments show that the string-to-dependency decoder achieves 1.48 point improvement in BLEU and 2.53 point improvement in TER compared to a standard hierarchical string-to- string system on the NIST 04 Chinese-English evaluation set.