Playback attack detection for text-dependent speaker verification over telephone channels

Abstract

Playback attacks constitute one of the biggest threats in biometric speaker verification systems, in which a previously recorded passphrase is played back by an unprivileged person in order to gain access. This paper features a description of the playback attack detection (PAD) algorithm, designed to protect text-dependent speaker verification systems from the aforementioned spoofing attacks. The paper also describes the usage of spectral landmarks and score normalization methods in the playback detection algorithm. Different factors are discussed in terms of the performance of the algorithm. The authors investigate two issues: (1) extracting the PAD features which are robust against channel variations and (2) the robustness of the algorithm in adverse acoustical environments (e.g. office, street, cocktail party noise). The experiments are performed on a prepared speech corpus containing 4187 occurrences of a passphrase spoken by 175 speakers. The results of the experiment show the equal error rate (EER) to be as low as 1.0%. These findings demonstrate that such spoofing-oriented playback attacks can be effectively detected and should not be considered a significant argument against applications of text-dependent speaker verification.