The RWTH Aachen German-English Machine Translation System for WMT 2015 | Zendy

Jan-Thorsten Peter | Zendy; Farzad Toutounchi | Zendy; Joern Wuebker | Zendy; Hermann Ney | Zendy

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The RWTH Aachen German-English Machine Translation System for WMT 2015

Author(s) -

Jan-Thorsten Peter,

Farzad Toutounchi,

Joern Wuebker,

Hermann Ney

Publication year - 2015

Language(s) - English

Resource type - Conference proceedings

DOI - 10.18653/v1/w15-3018

Subject(s) - machine translation , computer science , phrase , artificial intelligence , discriminative model , natural language processing , example based machine translation , machine translation software usability , language model , word (group theory) , german , translation (biology) , artificial neural network , evaluation of machine translation , speech recognition , linguistics , philosophy , biochemistry , chemistry , messenger rna , gene

This paper describes the statistical machine translation system developed at RWTH Aachen University for the German!English translation task of the EMNLP 2015 Tenth Workshop on Statistical Machine Translation (WMT 2015). A phrase-based machine translation system was applied and augmented with hierarchical phrase reordering and word class language models. Further, we ran discriminative maximum expected BLEU training for our system. In addition, we utilized multiple feed-forward neural network language and translation models and a recurrent neural network language model for reranking.

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