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Replay attacks remain a critical vulnerability for automatic speaker verification systems, particularly in real-time voice assistant applications. In this work, we propose acoustic maps as a novel spatial feature representation for replay…

音频与语音处理 · 电气工程与系统科学 2026-05-21 Michael Neri , Tuomas Virtanen

Automatic Speaker Verification systems are gaining popularity these days; spoofing attacks are of prime concern as they make these systems vulnerable. Some spoofing attacks like Replay attacks are easier to implement but are very hard to…

音频与语音处理 · 电气工程与系统科学 2020-08-11 Rahul T P , P R Aravind , Ranjith C , Usamath Nechiyil , Nandakumar Paramparambath

Automatic speaker verification (ASV) systems use a playback detector to filter out playback attacks and ensure verification reliability. Since current playback detection models are almost always trained using genuine and played-back speech,…

声音 · 计算机科学 2018-09-14 Fuming Fang , Junichi Yamagishi , Isao Echizen , Md Sahidullah , Tomi Kinnunen

Audio deepfake detection has become increasingly challenging due to rapid advances in speech synthesis and voice conversion technologies, particularly under channel distortions, replay attacks, and real-world recording conditions. This…

音频与语音处理 · 电气工程与系统科学 2026-01-13 K. A. Shahriar

Fake audio detection is expected to become an important research area in the field of smart speakers such as Google Home, Amazon Echo and chatbots developed for these platforms. This paper presents replay attack vulnerability of…

密码学与安全 · 计算机科学 2019-04-16 Khalid Mahmood Malik , Hafiz Malik , Roland Baumann

Human voices can be used to authenticate the identity of the speaker, but the automatic speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as impersonation, replay, text-to-speech, and voice conversion.…

音频与语音处理 · 电气工程与系统科学 2021-06-09 You Zhang , Fei Jiang , Zhiyao Duan

In this paper, we present UR-AIR system submission to the logical access (LA) and the speech deepfake (DF) tracks of the ASVspoof 2021 Challenge. The LA and DF tasks focus on synthetic speech detection (SSD), i.e. detecting text-to-speech…

音频与语音处理 · 电气工程与系统科学 2026-02-05 Xinhui Chen , You Zhang , Ge Zhu , Zhiyao Duan

In this study, we concentrate on replacing the process of extracting hand-crafted acoustic feature with end-to-end DNN using complementary high-resolution spectrograms. As a result of advance in audio devices, typical characteristics of a…

音频与语音处理 · 电气工程与系统科学 2019-07-18 Jee-weon Jung , Hye-jin Shim , Hee-Soo Heo , Ha-Jin Yu

In this paper, we propose a replay attack spoofing detection system for automatic speaker verification using multitask learning of noise classes. We define the noise that is caused by the replay attack as replay noise. We explore the…

音频与语音处理 · 电气工程与系统科学 2018-10-26 Hye-Jin Shim , Jee-weon Jung , Hee-Soo Heo , Sunghyun Yoon , Ha-Jin Yu

The second Automatic Speaker Verification Spoofing and Countermeasures challenge (ASVspoof 2017) focused on "replay attack" detection. The best deep-learning systems to compete in ASVspoof 2017 used Convolutional Neural Networks (CNNs) as a…

音频与语音处理 · 电气工程与系统科学 2018-05-24 Bhusan Chettri , Saumitra Mishra , Bob L. Sturm , Emmanouil Benetos

The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and the development of countermeasures. ASVspoof 2021 is the 4th…

In this paper, we initiate the concern of enhancing the spoofing robustness of the automatic speaker verification (ASV) system, without the primary presence of a separate countermeasure module. We start from the standard ASV framework of…

声音 · 计算机科学 2022-04-27 Xuechen Liu , Md Sahidullah , Tomi Kinnunen

The state-of-art models for speech synthesis and voice conversion are capable of generating synthetic speech that is perceptually indistinguishable from bonafide human speech. These methods represent a threat to the automatic speaker…

机器学习 · 计算机科学 2019-07-11 Moustafa Alzantot , Ziqi Wang , Mani B. Srivastava

A number of studies have successfully developed speaker verification or presentation attack detection systems. However, studies integrating the two tasks remain in the preliminary stages. In this paper, we propose two approaches for…

音频与语音处理 · 电气工程与系统科学 2020-09-29 Hye-jin Shim , Jee-weon Jung , Ju-ho Kim , Seung-bin Kim , Ha-Jin Yu

We propose a novel approach for spoofed speech characterization through explainable probabilistic attribute embeddings. In contrast to high-dimensional raw embeddings extracted from a spoofing countermeasure (CM) whose dimensions are not…

音频与语音处理 · 电气工程与系统科学 2024-09-18 Manasi Chhibber , Jagabandhu Mishra , Hyejin Shim , Tomi H. Kinnunen

Advances in automatic speaker verification (ASV) promote research into the formulation of spoofing detection systems for real-world applications. The performance of ASV systems can be degraded severely by multiple types of spoofing attacks,…

声音 · 计算机科学 2024-08-27 Zhenyu Wang , John H. L. Hansen

Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is vulnerable to spoofing, also referred to as "presentation…

It is well known that speaker verification systems are subject to spoofing attacks. The Automatic Speaker Verification Spoofing and Countermeasures Challenge -- ASVSpoof2015 -- provides a standard spoofing database, containing attacks based…

Growing interest in automatic speaker verification (ASV)systems has lead to significant quality improvement of spoofing attackson them. Many research works confirm that despite the low equal er-ror rate (EER) ASV systems are still…

声音 · 计算机科学 2017-05-25 Galina Lavrentyeva , Sergey Novoselov , Konstantin Simonchik

Various forefront countermeasure methods for automatic speaker verification (ASV) with considerable performance in anti-spoofing are proposed in the ASVspoof 2019 challenge. However, previous work has shown that countermeasure models are…

音频与语音处理 · 电气工程与系统科学 2020-03-09 Haibin Wu , Songxiang Liu , Helen Meng , Hung-yi Lee