ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems

Gong, Yuan; Yang, Jian; Huber, Jacob; MacKnight, Mitchell; Poellabauer, Christian

doi:10.21437/interspeech.2019-1541

Cited by 30 publications

(20 citation statements)

References 29 publications

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“…Due to its implementation simplicity, score fusion is the most commonly used fusion method in multibiometric systems [98]. However, recent works [32,55] have shown that the scored fusion outperformed feature fusion as a fused feature is more complex and may lose its significant traits, which can be used to distinguish accurately between different speaking individual [55].…”

Section: Searching Speaker Modelmentioning

confidence: 99%

A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction

Tan

Hijazi

Khamis

et al. 2021

Multimed Tools Appl

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The emergence of biometric technology provides enhanced security compared to the traditional identification and authentication techniques that were less efficient and secure. Despite the advantages brought by biometric technology, the existing biometric systems such as Automatic Speaker Verification (ASV) systems are weak against presentation attacks. A presentation attack is a spoofing attack launched to subvert an ASV system to gain access to the system. Though numerous Presentation Attack Detection (PAD) systems were reported in the literature, a systematic survey that describes the current state of research and application is unavailable. This paper presents a systematic analysis of the state-of-the-art voice PAD systems to promote further advancement in this area. The objectives of this paper are two folds: (i) to understand the nature of recent work on PAD systems, and (ii) to identify areas that require additional research. From the survey, a taxonomy of voice PAD and the trend analysis of recent work on PAD systems were built and presented, whereby the recent and relevant articles including articles from Interspeech and ICASSP Conferences, mostly indexed by Scopus, published between 2015 and 2021 were considered. A total of 172 articles were surveyed in this work. The findings of this survey present the limitation of recent works, which include spoof-type dependent PAD. Consequently, the future direction of work on voice PAD for interested researchers is established. The findings of this survey present the limitation of recent works, which include spoof-type dependent PAD. Consequently, the future direction of work on voice PAD for interested researchers is established.

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Section: Searching Speaker Modelmentioning

confidence: 99%

A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction

Tan

Hijazi

Khamis

et al. 2021

Multimed Tools Appl

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“…In this work, publicly available ReMASC dataset is used which aims to develop effective countermeasures against replay spoofing attack on VAs [5]. The details of the dataset collection strategies can be found in [5]. The details of the data partition for the experiments in this paper are available in [19].…”

Section: Dataset Feature Set and Classifiersmentioning

confidence: 99%

“…Among the various spoofing attacks, replay attack is becoming major concern for the community as it is easy to mount, but difficult to detect. Although, the design of countermeasure (CM) systems for ASV and VAs looks similar, there are important differences in anti-spoofing strategies for these systems, which are explained in [5]. Considering these differences, recently, Realistic Replay Attack Microphone Array Speech Corpus (ReMASC) has been released, which is specifically designed to develop countermeasures against replay spoofing attack on VAs [5].…”

Section: Introductionmentioning

confidence: 99%

“…Although, the design of countermeasure (CM) systems for ASV and VAs looks similar, there are important differences in anti-spoofing strategies for these systems, which are explained in [5]. Considering these differences, recently, Realistic Replay Attack Microphone Array Speech Corpus (ReMASC) has been released, which is specifically designed to develop countermeasures against replay spoofing attack on VAs [5]. In this paper, authors propose a CM system against replay spoofing attacks using cross Teager energy operator (CTEO)-based feature set for VAs.…”

Section: Introductionmentioning

confidence: 99%

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Cross-Teager Energy Cepstral Coefficients for Replay Spoof Detection on Voice Assistants

Acharya

Kotta

Patil

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Voice assistants (VAs) are highly vulnerable to replay attacks, where the impostor plays pre-recorded voice samples to gain an unauthorized access to personalised devices. To that effect, we present an optimal microphone-channel selection scheme using Cross-Teager Energy Operator (CTEO) for spoofed speech detection (SSD) task. Here, a channel refers to the speech signal obtained from a single microphone among the microphone array. The key idea of this work is optimal channel selection based on maximum cross-energies from a multichannel input, which is suitable for SSD task. This newly proposed feature set is named as Cross-Teager Energy Cepstal Coefficients (CTECC max ). The reason behind maximizing the cross-energies is to identify the distortions in replay speech signal which is added due to intermediate devices. This key idea is also cross-validated by selecting the least estimated cross-energies as feature set CTECC min . The noticeable improvement in the performance is observed for CTECC max over CTECC min for two classifiers, namely, Gaussian Mixture Model (GMM) and Light Convolutional Neural Network (LCNN).

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“…The ReMASC (Realistic Replay Attack Microphone Array Speech Corpus) is the first publicly available database that is designed specifically for the protection of voice-controlled systems (VCSs) against various replay attacks in various conditions and environments [84]. The ASVspoof 2019 challenge consists of simulated data for clear theoretical analysis of audio spoofing attacks in physical environments, however, it brings a simulation-to-reality gap.…”

Section: E) Remascmentioning

confidence: 99%

Advances in anti-spoofing: from the perspective of ASVspoof challenges

Kamble

Sailor

Patil

et al. 2020

SIP

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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.

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ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems

Cited by 30 publications

References 29 publications

A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction

A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction

Cross-Teager Energy Cepstral Coefficients for Replay Spoof Detection on Voice Assistants

Advances in anti-spoofing: from the perspective of ASVspoof challenges

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