Shun Kasahara, N. Minematsu, Han-Ping Shen, D. Saito, K. Hirose
{"title":"Structure-based prediction of English pronunciation distances and its analytical investigation","authors":"Shun Kasahara, N. Minematsu, Han-Ping Shen, D. Saito, K. Hirose","doi":"10.1109/ICIST.2014.6920396","DOIUrl":null,"url":null,"abstract":"English is the only language available for international communication and is used by approximately 1.5 billions of speakers. It is also known to have a large diversity of pronunciation partly due to the influence of the speakers' mother tongue, called accents. Our project aims at creating a global and individual-basis map of English pronunciations to be used in teaching and learning World Englishes (WE) as well as research studies of WE [1], [2]. Creating the map mathematically requires a distance matrix in terms of pronunciation differences among all the speakers considered, and technically requires a method of predicting the pronunciation distance between any pair of the speakers. Our previous but very recent study [3] combined invariant pronunciation structure analysis [4], [5], [6], [7] and Support Vector Regression (SVR) effectively to predict the interspeaker pronunciation distances. In [3], very high correlation of 0.903 was observed between reference IPA-based pronunciation distances and the distances predicted by our proposed method. In this paper, after explaining our proposed method, some new results of analytical investigation of the method are described.","PeriodicalId":306383,"journal":{"name":"2014 4th IEEE International Conference on Information Science and Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 4th IEEE International Conference on Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST.2014.6920396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
English is the only language available for international communication and is used by approximately 1.5 billions of speakers. It is also known to have a large diversity of pronunciation partly due to the influence of the speakers' mother tongue, called accents. Our project aims at creating a global and individual-basis map of English pronunciations to be used in teaching and learning World Englishes (WE) as well as research studies of WE [1], [2]. Creating the map mathematically requires a distance matrix in terms of pronunciation differences among all the speakers considered, and technically requires a method of predicting the pronunciation distance between any pair of the speakers. Our previous but very recent study [3] combined invariant pronunciation structure analysis [4], [5], [6], [7] and Support Vector Regression (SVR) effectively to predict the interspeaker pronunciation distances. In [3], very high correlation of 0.903 was observed between reference IPA-based pronunciation distances and the distances predicted by our proposed method. In this paper, after explaining our proposed method, some new results of analytical investigation of the method are described.