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A Survey of Deep Learning Techniques for Neural Machine Translation

2020-02-18 12:49:14
Shuoheng Yang, Yuxin Wang, Xiaowen Chu
arXiv_CL
           
Abstract

In recent years, natural language processing (NLP) has got great development with deep learning techniques. In the sub-field of machine translation, a new approach named Neural Machine Translation (NMT) has emerged and got massive attention from both academia and industry. However, with a significant number of researches proposed in the past several years, there is little work in investigating the development process of this new technology trend. This literature survey traces back the origin and principal development timeline of NMT, investigates the important branches, categorizes different research orientations, and discusses some future research trends in this field.

Abstract (translated)

URL

https://arxiv.org/abs/2002.07526

PDF

https://arxiv.org/pdf/2002.07526.pdf

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