计算机工程与应用2024，Vol.60Issue(4)：57-74,18.DOI:10.3778/j.issn.1002-8331.2305-0102
神经机器翻译综述
Survey of Neural Machine Translation
摘要
Abstract
Machine translation(MT)mainly studies how to translate the source language into the target language,which is of great significance for promoting the communication between nationalities.At present,neural machine translation(NMT)has become the mainstream MT method by translation speed and quality.In order to better sort out the context,this paper first introduces the history and methods of MT,compares and summarizes three main methods:rule-based machine translation,statistics-based machine translation and deep learning-based machine translation.Then NMT is introduced to explain its common types.Next,six main research fields of NMT are introduced,including multimodal MT,non-autoregressive MT,document-level MT,multilingual MT,data augmentation technology and preprocessing technique.Finally,the future of NMT is prospected from four aspects:low-resource languages,context-sensitive translation,unknown words and large models.This paper provides a systematic introduction to better understand the development status of NMT.关键词
机器翻译/神经机器翻译/篇章级机器翻译/数据增强/预处理技术Key words
machine translation/neural machine translation/document-level machine translation/data augmentation/pre-processing technique分类
信息技术与安全科学引用本文复制引用
章钧津,田永红,宋哲煜,郝宇峰..神经机器翻译综述[J].计算机工程与应用,2024,60(4):57-74,18.基金项目
内蒙古自治区自然科学基金(2020MS06026). （2020MS06026）
