witkowski17@interspeech_2017@ISCA

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#1 Audio Replay Attack Detection Using High-Frequency Features [PDF] [Copy] [Kimi1]

Authors: Marcin Witkowski ; Stanisław Kacprzak ; Piotr Żelasko ; Konrad Kowalczyk ; Jakub Gałka

This paper presents our contribution to the ASVspoof 2017 Challenge. It addresses a replay spoofing attack against a speaker recognition system by detecting that the analysed signal has passed through multiple analogue-to-digital (AD) conversions. Specifically, we show that most of the cues that enable to detect the replay attacks can be found in the high-frequency band of the replayed recordings. The described anti-spoofing countermeasures are based on (1) modelling the subband spectrum and (2) using the proposed features derived from the linear prediction (LP) analysis. The results of the investigated methods show a significant improvement in comparison to the baseline system of the ASVspoof 2017 Challenge. A relative equal error rate (EER) reduction by 70% was achieved for the development set and a reduction by 30% was obtained for the evaluation set.