{"title":"Speech Visualization Technology and Its Application in English Listening Teaching","authors":"Fang Li-xia","doi":"10.1109/ICSGEA.2018.00079","DOIUrl":null,"url":null,"abstract":"Effectively analyze and visualize speech signals is of great importance to enhance the quality of English listening teaching, therefore, in this paper, we aim to study on how to utilize the speech visualization technology in English listening teaching. Firstly, we discuss how to design the speech signal process and visualization system, and what features should be extracted from speech signals. Secondly, we exploit the Kernel principal component analysis to conduct dimensionality reduction, and visualize speech signals by computing coordinates of combined features. Thirdly, we introduce the speech visualization technology in English listening teaching, and experimental results demonstrate that listening ability of students can be significantly improved using speech visualization technology.","PeriodicalId":445324,"journal":{"name":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGEA.2018.00079","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
Effectively analyze and visualize speech signals is of great importance to enhance the quality of English listening teaching, therefore, in this paper, we aim to study on how to utilize the speech visualization technology in English listening teaching. Firstly, we discuss how to design the speech signal process and visualization system, and what features should be extracted from speech signals. Secondly, we exploit the Kernel principal component analysis to conduct dimensionality reduction, and visualize speech signals by computing coordinates of combined features. Thirdly, we introduce the speech visualization technology in English listening teaching, and experimental results demonstrate that listening ability of students can be significantly improved using speech visualization technology.