SYSTRAN Purely Neural MT Engines for WMT2017
Yongchao Deng
Jungi Kim
Guillaume Klein
Catherine Kobus
N. Segal
Christophe Servan
Bo Wang
Dakun Zhang
Josep Crego
Jean Senellart

Abstract
This paper describes SYSTRAN's systems submitted to the WMT 2017 shared news translation task for English-German, in both translation directions. Our systems are built using OpenNMT, an open-source neural machine translation system, implementing sequence-to-sequence models with LSTM encoder/decoders and attention. We experimented using monolingual data automatically back-translated. Our resulting models are further hyper-specialised with an adaptation technique that finely tunes models according to the evaluation test sentences.
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