{"title":"A New Approach To Accent Restoration Of Vietnamese Texts Using Dynamic Programming Combined With Co-Occurrence Graph","authors":"Ho Trong Nghia, Do Phuc","doi":"10.1109/RIVF.2009.5174609","DOIUrl":null,"url":null,"abstract":"In this paper, we would like to introduce a new approach to recover Vietnamese text's accents. Given a Vietnamese text in which accents are lost, our goal is to seek for a recovered text that yields a best lexical probability. Using a dynamic programming approach, we first build a model of language for Vietnamese as a lexical database which gives lexical probabilities to Vietnamese sentences. Second, we construct a map of literal translations of Vietnamese words to restrict our searching space. Finally, we apply dynamic programming as a searching engine to seek out the most probable sentence. We also use the co-occurrence graph to increase the accuracy of selection, the experimental results show that the average accuracy of our approach is about 93%-94%.","PeriodicalId":243397,"journal":{"name":"2009 IEEE-RIVF International Conference on Computing and Communication Technologies","volume":"538 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE-RIVF International Conference on Computing and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIVF.2009.5174609","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
In this paper, we would like to introduce a new approach to recover Vietnamese text's accents. Given a Vietnamese text in which accents are lost, our goal is to seek for a recovered text that yields a best lexical probability. Using a dynamic programming approach, we first build a model of language for Vietnamese as a lexical database which gives lexical probabilities to Vietnamese sentences. Second, we construct a map of literal translations of Vietnamese words to restrict our searching space. Finally, we apply dynamic programming as a searching engine to seek out the most probable sentence. We also use the co-occurrence graph to increase the accuracy of selection, the experimental results show that the average accuracy of our approach is about 93%-94%.