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The authors of (Cho et al., 2014a) have shown that the recently introducedneural network translation systems suffer from a significant drop intranslation quality when translating long sentences, unlike existingphrase-based translation systems. In this paper, we propose a way to addressthis issue by automatically segmenting an input sentence into phrases that canbe easily translated by the neural network translation model. Once each segmenthas been independently translated by the neural machine translation model, thetranslated clauses are concatenated to form a final translation. Empiricalresults show a significant improvement in translation quality for longsentences.

Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation