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Neural machine translation: Challenges, progress and future - 2020

Neural Machine Translation: Challenges, Progress And Future

Research Area:  Machine Learning


Machine translation (MT) is a technique that leverages computers to translate human languages automatically. Nowadays, neural machine translation (NMT) which models direct mapping between source and target languages with deep neural networks has achieved a big breakthrough in translation performance and become the de facto paradigm of MT. This article makes a review of NMT framework, discusses the challenges in NMT, introduces some exciting recent progresses and finally looks forward to some potential future research trends.


Author(s) Name:  JiaJun Zhang & ChengQing Zong

Journal name:  Science China Technological Sciences

Conferrence name:  

Publisher name:  Springer


Volume Information:  volume 63, pages 2028–2050