Guiding Neural Machine Translation Decoding with External Knowledge
Rajen Chatterjee,Matteo Negri,Marco Turchi,Marcello Federico,Lucia Specia,Frédéric Blain +5 more
- pp 157-168
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TLDR
This work proposes a “guide” mechanism that enhances an existing NMT decoder with the ability to prioritize and adequately handle translation options presented in the form of XML annotations of source words.Abstract:
© 2017 The Authors. Published by Association for Computational Linguistics. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: http://dx.doi.org/10.18653/v1/W17-4716read more
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References
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Proceedings ArticleDOI
Bleu: a Method for Automatic Evaluation of Machine Translation
TL;DR: This paper proposed a method of automatic machine translation evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run.
Proceedings Article
Neural Machine Translation by Jointly Learning to Align and Translate
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Neural Machine Translation by Jointly Learning to Align and Translate
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Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
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