Win Zaw, Shwe Sin Moe, Ye Kyaw Thu, Nyein Nyein Oo
{"title":"缅甸名字罗马化的加权有限状态传感器和下波规则应用","authors":"Win Zaw, Shwe Sin Moe, Ye Kyaw Thu, Nyein Nyein Oo","doi":"10.1109/ecti-con49241.2020.9158231","DOIUrl":null,"url":null,"abstract":"Romanization known as Latinization that refers to the representation of names with Roman (Latin) alphabets. The Romanization process is not trivial especially for Myanmar Language (Burmese) due to different Roman variations of a single Myanmar proper noun. The Myanmar Name Romanization project has so far developed a 55K Romanized word pairs of Myanmar personal names. We apply Weighted Finite State Transducers (WFST) and Ripple Down Rules (RDR) based tagging approaches to the task of Myanmar name Romanization and vice versa. We perform experiments on one closed test data set (5,000 of training data) and three open test data sets: 5,000 Myanmar personal names, 571 city and town names of Myanmar, and 292 Myanmar food names. The result shows that RDR approach gives better performance than WFST for open test data sets.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applying Weighted Finite State Transducers and Ripple Down Rules for Myanmar Name Romanization\",\"authors\":\"Win Zaw, Shwe Sin Moe, Ye Kyaw Thu, Nyein Nyein Oo\",\"doi\":\"10.1109/ecti-con49241.2020.9158231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Romanization known as Latinization that refers to the representation of names with Roman (Latin) alphabets. The Romanization process is not trivial especially for Myanmar Language (Burmese) due to different Roman variations of a single Myanmar proper noun. The Myanmar Name Romanization project has so far developed a 55K Romanized word pairs of Myanmar personal names. We apply Weighted Finite State Transducers (WFST) and Ripple Down Rules (RDR) based tagging approaches to the task of Myanmar name Romanization and vice versa. We perform experiments on one closed test data set (5,000 of training data) and three open test data sets: 5,000 Myanmar personal names, 571 city and town names of Myanmar, and 292 Myanmar food names. The result shows that RDR approach gives better performance than WFST for open test data sets.\",\"PeriodicalId\":371552,\"journal\":{\"name\":\"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ecti-con49241.2020.9158231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ecti-con49241.2020.9158231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying Weighted Finite State Transducers and Ripple Down Rules for Myanmar Name Romanization
Romanization known as Latinization that refers to the representation of names with Roman (Latin) alphabets. The Romanization process is not trivial especially for Myanmar Language (Burmese) due to different Roman variations of a single Myanmar proper noun. The Myanmar Name Romanization project has so far developed a 55K Romanized word pairs of Myanmar personal names. We apply Weighted Finite State Transducers (WFST) and Ripple Down Rules (RDR) based tagging approaches to the task of Myanmar name Romanization and vice versa. We perform experiments on one closed test data set (5,000 of training data) and three open test data sets: 5,000 Myanmar personal names, 571 city and town names of Myanmar, and 292 Myanmar food names. The result shows that RDR approach gives better performance than WFST for open test data sets.