{"title":"基于信道模式噪声的说话人识别重放攻击检测算法","authors":"Zhifeng Wang, G. Wei, Qianhua He","doi":"10.1109/ICMLC.2011.6016982","DOIUrl":null,"url":null,"abstract":"This paper proposes a channel pattern noise based approach to guard speaker recognition system against playback attacks. For each recording under investigation, the channel pattern noise severs as a unique channel identification fingerprint. Denoising filter and statistical frames are applied to extract channel pattern noise, and 6 Legendre coefficients and 6 statistical features are extracted. SVM is used to train channel noise model to judge whether the input speech is an authentic or a playback recording. The experimental results indicate that, with the designed playback detector, the equal error rate of speaker recognition system is reduced by 30%.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"106","resultStr":"{\"title\":\"Channel pattern noise based playback attack detection algorithm for speaker recognition\",\"authors\":\"Zhifeng Wang, G. Wei, Qianhua He\",\"doi\":\"10.1109/ICMLC.2011.6016982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a channel pattern noise based approach to guard speaker recognition system against playback attacks. For each recording under investigation, the channel pattern noise severs as a unique channel identification fingerprint. Denoising filter and statistical frames are applied to extract channel pattern noise, and 6 Legendre coefficients and 6 statistical features are extracted. SVM is used to train channel noise model to judge whether the input speech is an authentic or a playback recording. The experimental results indicate that, with the designed playback detector, the equal error rate of speaker recognition system is reduced by 30%.\",\"PeriodicalId\":228516,\"journal\":{\"name\":\"2011 International Conference on Machine Learning and Cybernetics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"106\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2011.6016982\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2011.6016982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Channel pattern noise based playback attack detection algorithm for speaker recognition
This paper proposes a channel pattern noise based approach to guard speaker recognition system against playback attacks. For each recording under investigation, the channel pattern noise severs as a unique channel identification fingerprint. Denoising filter and statistical frames are applied to extract channel pattern noise, and 6 Legendre coefficients and 6 statistical features are extracted. SVM is used to train channel noise model to judge whether the input speech is an authentic or a playback recording. The experimental results indicate that, with the designed playback detector, the equal error rate of speaker recognition system is reduced by 30%.