Abstract
Abstract In recent years, automatic speaker verification (ASV) is used extensively for voice biometrics. This leads to an increased interest to secure these voice biometric systems for real-world applications. The ASV systems are vulnerable to various kinds of spoofing attacks, namely, synthetic speech (SS), voice conversion (VC), replay, twins, and impersonation. This paper provides the literature review of ASV spoof detection, novel acoustic feature representations, deep learning, end-to-end systems, etc. Furthermore, the paper also summaries previous studies of spoofing attacks with emphasis on SS, VC, and replay along with recent efforts to develop countermeasures for spoof speech detection (SSD) task. The limitations and challenges of SSD task are also presented. While several countermeasures were reported in the literature, they are mostly validated on a particular database, furthermore, their performance is far from perfect. The security of voice biometrics systems against spoofing attacks remains a challenging topic. This paper is based on a tutorial presented at APSIPA Annual Summit and Conference 2017 to serve as a quick start for those interested in the topic.
Highlights
A biometric system aims to verify the identity of an individual from their behavioral and/or biological characteristics [1,2]
The spoofing attacks against an automatic speaker verification (ASV) system or biometric system in general are considered as a part of presentation attacks as per International Organization for Standardization (ISO) and International Electro-technical Commission (IEC) [17]
We focus on the description of ASVspoof challenge datasets
Summary
A biometric system aims to verify the identity of an individual from their behavioral and/or biological characteristics [1,2]. Processing Magazine special issue on Biometric Security and Privacy Protection [26], IEEE Journal on Selected Topics in Signal Processing special issue on Spoofing and Countermeasures for Automatic Speaker Verification [27], Special issue on Speaker and language characterization and recognition: voice modeling, conversion, synthesis, and ethical aspects [28], and Special issue on Advances in Automatic Speaker Verification Anti-spoofing [29]. The first survey paper on the ASVspoof challenge [20] discusses the past work and identifies priority research directions for the future [30] and presents the details of the dataset, protocols, and metrics of the ASVspoof 2015 challenge It provides a detailed analysis of the participating systems in the challenge.
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