{"title":"基于小波包分解的声纹特征提取","authors":"Huang Jinjie, Lei Ming, Lu Chao, Yuan Qingyuan","doi":"10.23919/CHICC.2018.8482880","DOIUrl":null,"url":null,"abstract":"The main purpose of speech signal recognition system research is to improve the recognition rate of speech signal and reduce the recognition time. The feature extraction of speech signal in the process of recognition is one of the key aspects. In this paper, the speech feature extraction is to use the auditory characteristics of the human ear to decompose the wavelet packet into five levels and extract the dynamic features contained in the frame signal. After further processing, the speech feature parameters (DWPT parameters) are obtained. Simulation shows that the speaker recognition rate has been significantly improved compared with other traditional methods.","PeriodicalId":158442,"journal":{"name":"2018 37th Chinese Control Conference (CCC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Voiceprint Feature Extraction Based on Wavelet Packet Decomposition\",\"authors\":\"Huang Jinjie, Lei Ming, Lu Chao, Yuan Qingyuan\",\"doi\":\"10.23919/CHICC.2018.8482880\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main purpose of speech signal recognition system research is to improve the recognition rate of speech signal and reduce the recognition time. The feature extraction of speech signal in the process of recognition is one of the key aspects. In this paper, the speech feature extraction is to use the auditory characteristics of the human ear to decompose the wavelet packet into five levels and extract the dynamic features contained in the frame signal. After further processing, the speech feature parameters (DWPT parameters) are obtained. Simulation shows that the speaker recognition rate has been significantly improved compared with other traditional methods.\",\"PeriodicalId\":158442,\"journal\":{\"name\":\"2018 37th Chinese Control Conference (CCC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 37th Chinese Control Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CHICC.2018.8482880\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 37th Chinese Control Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CHICC.2018.8482880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Voiceprint Feature Extraction Based on Wavelet Packet Decomposition
The main purpose of speech signal recognition system research is to improve the recognition rate of speech signal and reduce the recognition time. The feature extraction of speech signal in the process of recognition is one of the key aspects. In this paper, the speech feature extraction is to use the auditory characteristics of the human ear to decompose the wavelet packet into five levels and extract the dynamic features contained in the frame signal. After further processing, the speech feature parameters (DWPT parameters) are obtained. Simulation shows that the speaker recognition rate has been significantly improved compared with other traditional methods.