A Survey on Replay Attack Detection for Automatic Speaker Verification (ASV) System

In this paper, we present a brief survey of various approaches used to detect replay attack for Automatic Speaker Verification (ASV) system. The replay spoofing attack is the most challenging task to detect as only few seconds of audio samples are required to replay genuine speaker's voice. Due to large availability and the widespread usage of the mobile/smart gadgets, recording devices, it is easy and simple to record and replay the genuine speaker's voice. The challenging task, in replay spoof attack is to detect the acoustical characteristics of the speech signal between the natural and replayed version. The speech signal recorded with the playback device contains the convolutional and additive distortions from the intermediate device. Background noise and channel degradations seriously constrain the performance of the system. The goal of this paper is to provide an overview of the replay attack focusing on 2nd ASVspoof 2017 challenge which is an emerging research problem in the field of anti-spoofing. This paper presents critical analysis of state-of-the-art techniques, various countermeasures, databases, and also aims to present current limitations along with road map ahead, i.e., future research directions in this technological challenging problem.