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

By Jan-Thorsten Peter, Farzad Toutounchi, Joern Wuebker, Hermann Ney. 2015

4 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Machine Translation

Citations in the corpus

• Findings of the 2015 Workshop on Statistical Machine Translation (2015, neutral): “RWTH RWTH Aachen (Peter et al., 2015)”