Linear prediction residual features for automatic speaker verification anti-spoofing

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dc.authorid0000-0002-9174-0367en_US
dc.contributor.authorHanilçi, Cemal
dc.date.accessioned2021-03-20T20:13:10Z
dc.date.available2021-03-20T20:13:10Z
dc.date.issued2018
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractAutomatic speaker verification (ASV) systems are highly vulnerable against spoofing attacks. Anti-spoofing, determining whether a speech signal is natural/genuine or spoofed, is very important for improving the reliability of the ASV systems. Spoofing attacks using the speech signals generated using speech synthesis and voice conversion have recently received great interest due to the 2015 edition of Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015). In this paper, we propose to use linear prediction (LP) residual based features for anti-spoofing. Three different features extracted from LP residual signal were compared using the ASVspoof 2015 database. Experimental results indicate that LP residual phase cepstral coefficients (LPRPC) and LP residual Hilbert envelope cepstral coefficients (LPRHEC) obtained from the analytic signal of the LP residual yield promising results for anti-spoofing. The proposed features are found to outperform standard Mel-frequency cepstral coefficients (MFCC) and Cosine Phase (CosPhase) features. LPRPC and LPRHEC features give the smallest equal error rates (EER) for eight spoofing methods out of ten spoofing attacks in comparison to MFCC and CosPhase features.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [115E916]en_US
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) (project #115E916).en_US
dc.identifier.doi10.1007/s11042-017-5181-0en_US
dc.identifier.endpage16111en_US
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.issue13en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage16099en_US
dc.identifier.urihttp://doi.org/10.1007/s11042-017-5181-0
dc.identifier.urihttps://hdl.handle.net/20.500.12885/806
dc.identifier.volume77en_US
dc.identifier.wosWOS:000439750300005en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorHanilçi, Cemal
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Tools And Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSpeaker verificationen_US
dc.subjectAnti-spoofingen_US
dc.subjectCountermeasureen_US
dc.subjectLinear prediction residualen_US
dc.titleLinear prediction residual features for automatic speaker verification anti-spoofingen_US
dc.typeArticleen_US

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