中文
相关论文

相关论文: STC Antispoofing Systems for the ASVspoof2019 Chal…

200 篇论文

ASVspoof challenges are designed to advance the understanding of spoofing speech attacks and encourage the development of robust countermeasure systems. These challenges provide a standardized database for assessing and comparing…

音频与语音处理 · 电气工程与系统科学 2025-10-07 Avishai Weizman , Yehuda Ben-Shimol , Itshak Lapidot

This paper describes the BUT submitted systems for the ASVspoof 5 challenge, along with analyses. For the conventional deepfake detection task, we use ResNet18 and self-supervised models for the closed and open conditions, respectively. In…

We present our system submission to the ASVspoof 2019 Challenge Physical Access (PA) task. The objective for this challenge was to develop a countermeasure that identifies speech audio as either bona fide or intercepted and replayed. The…

计算与语言 · 计算机科学 2019-09-27 Jennifer Williams , Joanna Rownicka

Recent advances in sophisticated synthetic speech generated from text-to-speech (TTS) or voice conversion (VC) systems cause threats to the existing automatic speaker verification (ASV) systems. Since such synthetic speech is generated from…

音频与语音处理 · 电气工程与系统科学 2022-12-15 Youngsik Eom , Yeonghyeon Lee , Ji Sub Um , Hoirin Kim

This paper describes our DKU-OPPO system for the 2022 Spoofing-Aware Speaker Verification (SASV) Challenge. First, we split the joint task into speaker verification (SV) and spoofing countermeasure (CM), these two tasks which are optimized…

音频与语音处理 · 电气工程与系统科学 2022-07-18 Xingming Wang , Xiaoyi Qin , Yikang Wang , Yunfei Xu , Ming Li

Modern text-to-speech (TTS) and voice conversion (VC) systems produce natural sounding speech that questions the security of automatic speaker verification (ASV). This makes detection of such synthetic speech very important to safeguard ASV…

音频与语音处理 · 电气工程与系统科学 2020-09-22 Zhenzong Wu , Rohan Kumar Das , Jichen Yang , Haizhou Li

The automatic speaker verification spoofing (ASVspoof) challenge series is crucial for enhancing the spoofing consideration and the countermeasures growth. Although the recent ASVspoof 2019 validation results indicate the significant…

声音 · 计算机科学 2022-09-27 Chenlei Hu , Ruohua Zhou

A great deal of recent research effort on speech spoofing countermeasures has been invested into back-end neural networks and training criteria. We contribute to this effort with a comparative perspective in this study. Our comparison of…

音频与语音处理 · 电气工程与系统科学 2021-06-15 Xin Wang , Junich Yamagishi

Automatic speaker verification, like every other biometric system, is vulnerable to spoofing attacks. Using only a few minutes of recorded voice of a genuine client of a speaker verification system, attackers can develop a variety of…

声音 · 计算机科学 2019-06-20 Balamurali BT , Kin Wah Edward Lin , Simon Lui , Jer-Ming Chen , Dorien Herremans

This paper presents a description of STC Ltd. systems submitted to the NIST 2021 Speaker Recognition Evaluation for both fixed and open training conditions. These systems consists of a number of diverse subsystems based on using deep neural…

ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake detection solutions. A significant change from previous challenge editions is a new crowdsourced database collected from a…

High-performance spoofing countermeasure systems for automatic speaker verification (ASV) have been proposed in the ASVspoof 2019 challenge. However, the robustness of such systems under adversarial attacks has not been studied yet. In this…

音频与语音处理 · 电气工程与系统科学 2019-10-22 Songxiang Liu , Haibin Wu , Hung-yi Lee , Helen Meng

It becomes urgent to design effective anti-spoofing algorithms for vulnerable automatic speaker verification systems due to the advancement of high-quality playback devices. Current studies mainly treat anti-spoofing as a binary…

计算机视觉与模式识别 · 计算机科学 2023-01-19 Yongqiang Dou , Haocheng Yang , Maolin Yang , Yanyan Xu , Dengfeng Ke

This paper describes our submitted systems to the 2022 ADD challenge withing the tracks 1 and 2. Our approach is based on the combination of a pre-trained wav2vec2 feature extractor and a downstream classifier to detect spoofed audio. This…

音频与语音处理 · 电气工程与系统科学 2022-03-04 Juan M. Martín-Doñas , Aitor Álvarez

Many endeavors have sought to develop countermeasure techniques as enhancements on Automatic Speaker Verification (ASV) systems, in order to make them more robust against spoof attacks. As evidenced by the latest ASVspoof 2019…

声音 · 计算机科学 2021-09-21 Amir Mohammad Rostami , Mohammad Mehdi Homayounpour , Ahmad Nickabadi

Self-supervised speech model is a rapid progressing research topic, and many pre-trained models have been released and used in various down stream tasks. For speech anti-spoofing, most countermeasures (CMs) use signal processing algorithms…

音频与语音处理 · 电气工程与系统科学 2022-02-07 Xin Wang , Junichi Yamagishi

The performance of automatic speaker verification (ASV) systems could be degraded by voice spoofing attacks. Most existing works aimed to develop standalone spoofing countermeasure (CM) systems. Relatively little work targeted at developing…

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

Voice-based biometric systems are highly prone to spoofing attacks. Recently, various countermeasures have been developed for detecting different kinds of attacks such as replay, speech synthesis (SS) and voice conversion (VC). Most of the…

多媒体 · 计算机科学 2020-08-07 Dipjyoti Paul , Md Sahidullah , Goutam Saha

We address speaker-aware anti-spoofing, where prior knowledge of the target speaker is incorporated into a voice spoofing countermeasure (CM). In contrast to the frequently used speaker-independent solutions, we train the CM in a…

声音 · 计算机科学 2023-06-09 Xuechen Liu , Md Sahidullah , Kong Aik Lee , Tomi Kinnunen

Synthetic voice and splicing audio clips have been generated to spoof Internet users and artificial intelligence (AI) technologies such as voice authentication. Existing research work treats spoofing countermeasures as a binary…

音频与语音处理 · 电气工程与系统科学 2022-11-30 Lei Wang , Benedict Yeoh , Jun Wah Ng