典型文献
Progress in Machine Translation
文献摘要：
After more than 70 years of evolution,great achievements have been made in machine translation.Especially in recent years,translation quality has been greatly improved with the emergence of neural machine translation(NMT).In this article,we first review the history of machine translation from rule-based machine translation to example-based machine translation and statistical machine transla-tion.We then introduce NMT in more detail,including the basic framework and the current dominant framework,Transformer,as well as multilingual translation models to deal with the data sparseness problem.In addition,we introduce cutting-edge simultaneous translation methods that achieve a balance between translation quality and latency.We then describe various products and applications of machine translation.At the end of this article,we briefly discuss challenges and future research directions in this field.
文献关键词：
中图分类号：
作者姓名：
Haifeng Wang;Hua Wu;Zhongjun He;Liang Huang;Kenneth Ward Church
作者机构：
Baidu Inc.,Beijing 100193,China;Baidu Research,Sunnyvale,CA 94089,USA
文献出处：
引用格式：
[1]Haifeng Wang;Hua Wu;Zhongjun He;Liang Huang;Kenneth Ward Church-.Progress in Machine Translation)[J].工程（英文）,2022(11):143-153
A类：
sparseness
B类：
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AB值：
0.576605
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