Spectro-temporal features for audio replay attack detection

Speaker verification can be viewed as a process of verifying the person using his/her utterance. The major challenge to implement automatic speaker verification in security applications is spoofing attacks. Speaker verification systems can be spoofed using pre-recorded speech, synthetic and voice conversion speech. Hence, there is a need to develop spoof detection system in order to make voice biometrics viable for security applications. This paper proposes to explore time-frequency representations obtained using gammatone filterbank and constant Q transform for detecting presentation attack for automatic speaker verification. The experiments are carried out for ASV spoof 2017 database and the results are compared with state-of-art replay speech detection systems based on cepstral features.