Authors
Minh-Thang Luong, Ilya Sutskever, Quoc V Le, Oriol Vinyals, Wojciech Zaremba
Publication date
2014/10/30
Journal
arXiv preprint arXiv:1410.8206
Description
Abstract: Neural Machine Translation (NMT) is a new approach to machine translation that
has shown promising results that are comparable to traditional approaches. A significant
weakness in conventional NMT systems is their inability to correctly translate very rare
words: end-to-end NMTs tend to have relatively small vocabularies with a single unk symbol
that represents every possible out-of-vocabulary (OOV) word. In this paper, we propose and
implement an effective technique to address this problem. We train an NMT system on ...
Total citations
20142015201613552
Scholar articles
MT Luong, I Sutskever, QV Le, O Vinyals, W Zaremba - arXiv preprint arXiv:1410.8206, 2014