Abstract
Audio replay attack poses great threat to Automatic Speaker Verification (ASV) systems. In this paper, we propose a set of features based on Teager Energy Operator and a slightly modified version of x-vector system to detect replay attacks. The proposed methods are tested on ASVspoof 2017 corpus. When using GMM with the proposed features, our best system has an EER of 6.13% on dev set and 15.53% on eval set, while the EER for the baseline system (GMM with CQCC) is 30.60% on eval set. When combined with the modified x-vector, the best EER further drops to 5.57% for dev subset and 14.21% for eval subset.
This work is supported by NSFC 61602404 and the National Basic Research Program of China (973 Program) (No. 2013CB329504).
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Zhang, Z., Zhou, L., Yang, Y., Wu, Z. (2019). Teager Energy Operator Based Features with x-vector for Replay Attack Detection. In: Sun, Z., He, R., Feng, J., Shan, S., Guo, Z. (eds) Biometric Recognition. CCBR 2019. Lecture Notes in Computer Science(), vol 11818. Springer, Cham. https://doi.org/10.1007/978-3-030-31456-9_51
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