S. Bakhshaei, Shahram Khadivi, N. Riahi, H. Sameti
{"title":"A study to find influential parameters on a Farsi-English statistical machine translation system","authors":"S. Bakhshaei, Shahram Khadivi, N. Riahi, H. Sameti","doi":"10.1109/ISTEL.2010.5734165","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to analyze the Farsi-English statistical machine translation systems as a useful communication tool. Improvement of the nation's communication increases the need of easier way of translating between different languages in front of expensive human translators. In this work, a statistical phrase-based system is run on Farsi - English pair languages and the effect of its parameters on the translation quality has been deeply studied. Using BLEU as a metric of translation accuracy, the system achieves an improvement of 1.84%, relative to the baseline accuracy, which is increment from 16.97% to 18.81% in the best case.","PeriodicalId":306663,"journal":{"name":"2010 5th International Symposium on Telecommunications","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 5th International Symposium on Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISTEL.2010.5734165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The aim of this paper is to analyze the Farsi-English statistical machine translation systems as a useful communication tool. Improvement of the nation's communication increases the need of easier way of translating between different languages in front of expensive human translators. In this work, a statistical phrase-based system is run on Farsi - English pair languages and the effect of its parameters on the translation quality has been deeply studied. Using BLEU as a metric of translation accuracy, the system achieves an improvement of 1.84%, relative to the baseline accuracy, which is increment from 16.97% to 18.81% in the best case.