O. Mamyrbayev, N. Mekebayev, M. Turdalyuly, N. Oshanova, Tolga Ihsan Medeni, A. Yessentay
{"title":"基于分类算法的语音识别","authors":"O. Mamyrbayev, N. Mekebayev, M. Turdalyuly, N. Oshanova, Tolga Ihsan Medeni, A. Yessentay","doi":"10.5772/intechopen.88239","DOIUrl":null,"url":null,"abstract":"This article discusses the classification algorithms for the problem of personality identification by voice using machine learning methods. We used the MFCC algorithm in the speech preprocessing process. To solve the problem, a comparative analysis of five classification algorithms was carried out. In the first experiment, the support vector method was determined — 0.90 and multilayer perceptron — 0.83, that showed the best results. In the second experiment, a multilayer perceptron with an accuracy of 0.93 was proposed using the Robust scaler method for personal identification. Therefore, to solve this problem, it is possible to use a multi-layer perceptron, taking into account the specifics of the speech signal.","PeriodicalId":258328,"journal":{"name":"Intelligent System and Computing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Voice Identification Using Classification Algorithms\",\"authors\":\"O. Mamyrbayev, N. Mekebayev, M. Turdalyuly, N. Oshanova, Tolga Ihsan Medeni, A. Yessentay\",\"doi\":\"10.5772/intechopen.88239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article discusses the classification algorithms for the problem of personality identification by voice using machine learning methods. We used the MFCC algorithm in the speech preprocessing process. To solve the problem, a comparative analysis of five classification algorithms was carried out. In the first experiment, the support vector method was determined — 0.90 and multilayer perceptron — 0.83, that showed the best results. In the second experiment, a multilayer perceptron with an accuracy of 0.93 was proposed using the Robust scaler method for personal identification. Therefore, to solve this problem, it is possible to use a multi-layer perceptron, taking into account the specifics of the speech signal.\",\"PeriodicalId\":258328,\"journal\":{\"name\":\"Intelligent System and Computing\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent System and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5772/intechopen.88239\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent System and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/intechopen.88239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Voice Identification Using Classification Algorithms
This article discusses the classification algorithms for the problem of personality identification by voice using machine learning methods. We used the MFCC algorithm in the speech preprocessing process. To solve the problem, a comparative analysis of five classification algorithms was carried out. In the first experiment, the support vector method was determined — 0.90 and multilayer perceptron — 0.83, that showed the best results. In the second experiment, a multilayer perceptron with an accuracy of 0.93 was proposed using the Robust scaler method for personal identification. Therefore, to solve this problem, it is possible to use a multi-layer perceptron, taking into account the specifics of the speech signal.