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arXiv · 2004.05809

Neural Machine Translation: Challenges, Progress and Future

Jiajun Zhang·Chengqing Zong
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Abstract

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. In addition, we maintain the state-of-the-art methods for various NMT tasks at the website https://github.com/ZNLP/SOTA-MT.

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Jiajun Zhang, Chengqing Zong. 2020-04-13. Neural Machine Translation: Challenges, Progress and Future. https://arxiv.org/abs/2004.05809

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