摘要
本文基于语义选择与信息特征设计了英语自动化机器翻译系统。通过语义信息特征制定了机器翻译流程,以GIZA++为载体进行翻译,利用伯克利对准器对齐词语,基于反向转换语法,详细阐述汉语语言模式与英语翻译语言模式的结构关联特性,以语句动静配置,实现自动化机器翻译。最后通过系统测试,结果表明,与传统机器翻译系统相比,准确率显著提高,这就表明基于语义选择与信息特征的英语自动化机器翻译系统的翻译准确率较高,可为英汉机器翻译奠定坚实的基础支持。
Based on semantic selection and information features,this paper designs an automated machine translation system for English.By means of semantic information features,a machine translation process is developed,with GIZA++as the carrier for translation,using the Berkeley collator to align words,based on reverse transformation grammar,the structural association characteristics of Chinese language pattern and English translation language pattern are elaborated in detail,and the automatic machine translation is realized by the dynamic and static configuration of sentences.The results show that the accuracy is improved significantly.Compared with the traditional machine translation system,which indicates that the translation accuracy of English automated machine translation system based on semantic selection and information features is high,which can lay a solid foundation for English-Chinese machine translation.
作者
姚兰
YAO Lan(Shaanxi Technical College of Finance&Economics,Xianyang 712000 China)
出处
《自动化技术与应用》
2021年第2期182-185,共4页
Techniques of Automation and Applications
关键词
语义选择
信息特征
自动化
机器翻译系统
semantic preference
information features
robotization
machine translation system
