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arXiv · 1709.03814

SYSTRAN Purely Neural MT Engines for WMT2017

Yongchao Deng·Jungi Kim·Guillaume Klein·Catherine Kobus·Natalia Segal·Christophe Servan·Bo Wang·Dakun Zhang·Josep Crego·Jean Senellart
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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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Yongchao Deng, Jungi Kim, Guillaume Klein, Catherine Kobus, Natalia Segal, Christophe Servan, Bo Wang, Dakun Zhang, Josep Crego, Jean Senellart. 2017-09-12. SYSTRAN Purely Neural MT Engines for WMT2017. https://arxiv.org/abs/1709.03814

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