Detecting Replay Attacks Using Multi-Channel Audio: A Neural Network-Based Method

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Authors Christian Poellabauer, Jian Yang, Yuan Gong
Journal/Conference Name IEEE Signal Processing Letters
Paper Category
Paper Abstract With the rapidly growing number of security-sensitive systems that use voice as the primary input, it becomes increasingly important to address these systems' potential vulnerability to replay attacks. Previous efforts to address this concern have focused primarily on single-channel audio. In this paper, we introduce a novel neural network-based replay attack detection model that further leverages spatial information of multi-channel audio and is able to significantly improve the replay attack detection performance.
Date of publication 2020
Code Programming Language Python
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