{"title":"噪声环境下基于距离熵的语音活动检测","authors":"Huan Zhao, Li-xia Zhao, Kai Zhao, Gangjin Wang","doi":"10.1109/NCM.2009.134","DOIUrl":null,"url":null,"abstract":"Voice Activity Detection is considered as a crucial part of the speech signal processing. In order to improve the accuracy of Voice Activity Detection under the high-noisy environment, an algorithm named distance entropy is proposed. The algorithm firstly enhances speech with short time spectral amplitude, and then utilizes the robustness of cepstral distance and spectral entropy. The experimental results show that this method performs well on anti-noise, and is more accurate to detect the endpoint in low SNR environment.","PeriodicalId":119669,"journal":{"name":"2009 Fifth International Joint Conference on INC, IMS and IDC","volume":"377 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Voice Activity Detection Based on Distance Entropy in Noisy Environment\",\"authors\":\"Huan Zhao, Li-xia Zhao, Kai Zhao, Gangjin Wang\",\"doi\":\"10.1109/NCM.2009.134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Voice Activity Detection is considered as a crucial part of the speech signal processing. In order to improve the accuracy of Voice Activity Detection under the high-noisy environment, an algorithm named distance entropy is proposed. The algorithm firstly enhances speech with short time spectral amplitude, and then utilizes the robustness of cepstral distance and spectral entropy. The experimental results show that this method performs well on anti-noise, and is more accurate to detect the endpoint in low SNR environment.\",\"PeriodicalId\":119669,\"journal\":{\"name\":\"2009 Fifth International Joint Conference on INC, IMS and IDC\",\"volume\":\"377 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fifth International Joint Conference on INC, IMS and IDC\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCM.2009.134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fifth International Joint Conference on INC, IMS and IDC","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCM.2009.134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Voice Activity Detection Based on Distance Entropy in Noisy Environment
Voice Activity Detection is considered as a crucial part of the speech signal processing. In order to improve the accuracy of Voice Activity Detection under the high-noisy environment, an algorithm named distance entropy is proposed. The algorithm firstly enhances speech with short time spectral amplitude, and then utilizes the robustness of cepstral distance and spectral entropy. The experimental results show that this method performs well on anti-noise, and is more accurate to detect the endpoint in low SNR environment.