Abstract
This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the German!English translation task of the ACL 2014 Eighth Workshop on Statistical Machine Translation (WMT 2014). Both hierarchical and phrase-based SMT systems are applied employing hierarchical phrase reordering and word class language models. For the phrase-based system, we run discriminative phrase training. In addition, we describe our preprocessing pipeline for German!English.
Cite
CITATION STYLE
Peitz, S., Wuebker, J., Freitag, M., & Ney, H. (2014). The rwth aachen german-english machine translation system for WMT 2014. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 157–162). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-3317
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