15th Annual Conference of the International Speech Communication Association

September 14-18, 2014

Introducing I-Vectors for Joint Anti-Spoofing and Speaker Verification

Elie Khoury (1), Tomi Kinnunen (2), Aleksandr Sizov (2), Zhizheng Wu (3), Sébastien Marcel (1)

(1) Idiap Research Institute, Switzerland
(2) University of Eastern Finland, Finland
(3) Nanyang Technological University, Singapore

Any biometric recognizer is vulnerable to direct spoofing attacks and automatic speaker verification (ASV) is no exception; replay, synthesis and conversion attacks all provoke false acceptances unless countermeasures are used. We focus on voice conversion (VC) attacks. Most existing countermeasures use full knowledge of a particular VC system to detect spoofing. We study a potentially more universal approach involving generative modeling perspective. Specifically, we adopt standard i-vector representation and probabilistic linear discriminant analysis (PLDA) back-end for joint operation of spoofing attack detector and ASV system. As a proof of concept, we study a vocoder-mismatched ASV and VC attack detection approach on the NIST 2006 speaker recognition evaluation corpus. We report stand-alone accuracy of both the ASV and countermeasure systems as well as their combination using score fusion and joint approach. The method holds promise.

Full Paper

Bibliographic reference.  Khoury, Elie / Kinnunen, Tomi / Sizov, Aleksandr / Wu, Zhizheng / Marcel, Sébastien (2014): "Introducing i-vectors for joint anti-spoofing and speaker verification", In INTERSPEECH-2014, 61-65.