{"title":"A Syllable-based Name Transliteration System","authors":"Xue Jiang, Le Sun, Dakun Zhang","doi":"10.3115/1699705.1699730","DOIUrl":null,"url":null,"abstract":"This paper describes the name entity transliteration system which we conducted for the \"NEWS2009 Machine Transliteration Shared Task\" (Li et al 2009). We get the transliteration in Chinese from an English name with three steps. We syllabify the English name into a sequence of syllables by some rules, and generate the most probable Pinyin sequence with the mapping model of English syllables to Pinyin (EP model), then we convert the Pinyin sequence into a Chinese character sequence with the mapping model of Pinyin to characters (PC model). And we get the final Chinese character sequence. Our system achieves an ACC of 0.498 and a Mean F-score of 0.786 in the official evaluation result.","PeriodicalId":262513,"journal":{"name":"NEWS@IJCNLP","volume":"148 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NEWS@IJCNLP","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1699705.1699730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper describes the name entity transliteration system which we conducted for the "NEWS2009 Machine Transliteration Shared Task" (Li et al 2009). We get the transliteration in Chinese from an English name with three steps. We syllabify the English name into a sequence of syllables by some rules, and generate the most probable Pinyin sequence with the mapping model of English syllables to Pinyin (EP model), then we convert the Pinyin sequence into a Chinese character sequence with the mapping model of Pinyin to characters (PC model). And we get the final Chinese character sequence. Our system achieves an ACC of 0.498 and a Mean F-score of 0.786 in the official evaluation result.
本文描述了我们为“NEWS2009机器音译共享任务”(Li et al . 2009)所做的名称实体音译系统。我们从一个英文名字中得到三个步骤的中文音译。首先按照一定的规则将英文名的音节序列分解为音节序列,然后利用英文音节到拼音的映射模型(EP模型)生成最可能的拼音序列,然后利用拼音到汉字的映射模型(PC模型)将拼音序列转换为汉字序列。我们得到了最终的汉字序列。我们的系统在官方评价结果中ACC为0.498,Mean F-score为0.786。