{"title":"基于神经网络的GMM优化语言检测","authors":"A. Shadmand, K. Monfaredi","doi":"10.1109/CSO.2010.21","DOIUrl":null,"url":null,"abstract":"The automatic language recognition of the speech signal consists of algorithms and methods which are used for modeling and classifying different languages. GMM (Gaussian Mixture Model), as a powerful instrument, can be used in classifying feature vectors. Persian language verification system, reported in [1], uses GMM as a basic system for tokenizing and Neural Network as the backend processor. In this paper a \"Persian language detection system\" is optimized to be used in \"language verification system\".","PeriodicalId":427481,"journal":{"name":"2010 Third International Joint Conference on Computational Science and Optimization","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Language Detection with GMM Optimization Using Neural Networks\",\"authors\":\"A. Shadmand, K. Monfaredi\",\"doi\":\"10.1109/CSO.2010.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automatic language recognition of the speech signal consists of algorithms and methods which are used for modeling and classifying different languages. GMM (Gaussian Mixture Model), as a powerful instrument, can be used in classifying feature vectors. Persian language verification system, reported in [1], uses GMM as a basic system for tokenizing and Neural Network as the backend processor. In this paper a \\\"Persian language detection system\\\" is optimized to be used in \\\"language verification system\\\".\",\"PeriodicalId\":427481,\"journal\":{\"name\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2010.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Joint Conference on Computational Science and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2010.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Language Detection with GMM Optimization Using Neural Networks
The automatic language recognition of the speech signal consists of algorithms and methods which are used for modeling and classifying different languages. GMM (Gaussian Mixture Model), as a powerful instrument, can be used in classifying feature vectors. Persian language verification system, reported in [1], uses GMM as a basic system for tokenizing and Neural Network as the backend processor. In this paper a "Persian language detection system" is optimized to be used in "language verification system".
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
