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Self-Supervised Neural Machine Translation

2019-07-01ACL 2019Code Available0· sign in to hype

Dana Ruiter, Cristina Espa{\~n}a-Bonet, Josef van Genabith

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Abstract

We present a simple new method where an emergent NMT system is used for simultaneously selecting training data and learning internal NMT representations. This is done in a self-supervised way without parallel data, in such a way that both tasks enhance each other during training. The method is language independent, introduces no additional hyper-parameters, and achieves BLEU scores of 29.21 (en2fr) and 27.36 (fr2en) on newstest2014 using English and French Wikipedia data for training.

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