SYSTRAN Purely Neural MT Engines for WMT2017

September 12, 2017 ยท Declared Dead ยท ๐Ÿ› Conference on Machine Translation

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Authors Yongchao Deng, Jungi Kim, Guillaume Klein, Catherine Kobus, Natalia Segal, Christophe Servan, Bo Wang, Dakun Zhang, Josep Crego, Jean Senellart arXiv ID 1709.03814 Category cs.CL: Computation & Language Citations 5 Venue Conference on Machine Translation Last Checked 4 months ago
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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