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A Survey of Deep Learning Techniques for Neural Machine Translation

  • arXiv (Cornell University)
  • Cornell University
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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.

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Publication details

DOI
10.48550/arxiv.2002.07526
OpenAlex
W3005724337
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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