王春苗,王继周,毛曦,马维军

• 1:辽宁工程技术大学测绘与地理科学学院
• 2:中国测绘科学研究院
• 3:首都师范大学

摘要(Abstract)：

针对传统人工地名翻译效率低、且囿于翻译者个人水平差异会导致翻译质量参差不齐,现有机器翻译不能有效解决地名翻译规则的交叉型歧义等问题,该文提出基于深度学习与先验知识相结合的英语地名音译技术,对地名翻译中音标生成、音标优化、音节划分3个核心环节进行研究,提出了基于深度学习的音标生成方法、基于先验知识的音标优化方法和基于双向最大匹配的音节划分方法,解决了机器翻译对地名单词音标识别差、汉字译写不规范的问题。实验结果表明,该地名专名音译技术比传统地名翻译方法时效性高、准确率高、翻译规范。

关键词(KeyWords)： 地名翻译;机器翻译;深度学习;先验知识;双向最大匹配算法

Abstract:

Keywords:

基金项目(Foundation): 自然资源部重大项目(12113600000018);; 科技部重点研发项目(2017-2021)(2017YFB0503600);; 中国测绘科学研究院基本科研业务经费项目(AR1912)

作者(Author): 王春苗,王继周,毛曦,马维军

DOI: 10.16251/j.cnki.1009-2307.2020.05.027

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