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Look It Up: Bilingual Dictionaries Improve Neural Machine Translation (2010.05997v2)

Published 12 Oct 2020 in cs.CL, cs.AI, and cs.LG

Abstract: Despite advances in neural machine translation (NMT) quality, rare words continue to be problematic. For humans, the solution to the rare-word problem has long been dictionaries, but dictionaries cannot be straightforwardly incorporated into NMT. In this paper, we describe a new method for "attaching" dictionary definitions to rare words so that the network can learn the best way to use them. We demonstrate improvements of up to 1.8 BLEU using bilingual dictionaries.

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Authors (2)
  1. Xing Jie Zhong (1 paper)
  2. David Chiang (59 papers)
Citations (1)