{"title":"Moses-based Chinese-Uyghur statistical machine translation systems","authors":"Xinghua Dong, Yating Yang, Xiaoping Zhou, Junlin Zhou","doi":"10.1109/YCICT.2010.5713076","DOIUrl":null,"url":null,"abstract":"This paper is an initial explore to Chinese-Uyghur statistical machine translation. We experimented on three systems, which are based on moses framework, on Uyghur word-level corpus and morpheme-level corpus, then combine their 1-best translation hypothesis by constructing consensus network using TER alignment. The experiments show the combination of hypothesis that are from different systems can obtain a better result.","PeriodicalId":179847,"journal":{"name":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2010.5713076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper is an initial explore to Chinese-Uyghur statistical machine translation. We experimented on three systems, which are based on moses framework, on Uyghur word-level corpus and morpheme-level corpus, then combine their 1-best translation hypothesis by constructing consensus network using TER alignment. The experiments show the combination of hypothesis that are from different systems can obtain a better result.