SYSTRAN Purely Neural MT Engines for WMT2017
September 12, 2017 ยท Declared Dead ยท ๐ Conference on Machine Translation
"No code URL or promise found in abstract"
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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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