Search Results for author: Guangke Chen

Found 9 papers, 5 papers with code

A Proactive and Dual Prevention Mechanism against Illegal Song Covers empowered by Singing Voice Conversion

no code implementations30 Jan 2024 Guangke Chen, Yedi Zhang, Fu Song, Ting Wang, Xiaoning Du, Yang Liu

To improve the imperceptibility of perturbations, we refine a psychoacoustic model-based loss with the backing track as an additional masker, a unique accompanying element for singing voices compared to ordinary speech voices.

Voice Conversion

QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems

no code implementations23 May 2023 Guangke Chen, Yedi Zhang, Zhe Zhao, Fu Song

Current adversarial attacks against speaker recognition systems (SRSs) require either white-box access or heavy black-box queries to the target SRS, thus still falling behind practical attacks against proprietary commercial APIs and voice-controlled devices.

Speaker Recognition

Towards Understanding and Mitigating Audio Adversarial Examples for Speaker Recognition

1 code implementation7 Jun 2022 Guangke Chen, Zhe Zhao, Fu Song, Sen Chen, Lingling Fan, Feng Wang, Jiashui Wang

According to the characteristic of SRSs, we present 22 diverse transformations and thoroughly evaluate them using 7 recent promising adversarial attacks (4 white-box and 3 black-box) on speaker recognition.

Speaker Recognition speech-recognition +1

AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker Recognition Systems

no code implementations7 Jun 2022 Guangke Chen, Zhe Zhao, Fu Song, Sen Chen, Lingling Fan, Yang Liu

Recent work has illuminated the vulnerability of speaker recognition systems (SRSs) against adversarial attacks, raising significant security concerns in deploying SRSs.

Adversarial Attack Speaker Recognition

SEC4SR: A Security Analysis Platform for Speaker Recognition

1 code implementation4 Sep 2021 Guangke Chen, Zhe Zhao, Fu Song, Sen Chen, Lingling Fan, Yang Liu

To bridge this gap, we present SEC4SR, the first platform enabling researchers to systematically and comprehensively evaluate adversarial attacks and defenses in SR. SEC4SR incorporates 4 white-box and 2 black-box attacks, 24 defenses including our novel feature-level transformations.

Speaker Recognition

Attack as Defense: Characterizing Adversarial Examples using Robustness

1 code implementation13 Mar 2021 Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang, Fu Song, Jun Sun

Though various defense mechanisms have been proposed to improve robustness of deep learning software, many of them are ineffective against adaptive attacks.

BDD4BNN: A BDD-based Quantitative Analysis Framework for Binarized Neural Networks

no code implementations12 Mar 2021 Yedi Zhang, Zhe Zhao, Guangke Chen, Fu Song, Taolue Chen

Verifying and explaining the behavior of neural networks is becoming increasingly important, especially when they are deployed in safety-critical applications.


Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems

1 code implementation3 Nov 2019 Guangke Chen, Sen Chen, Lingling Fan, Xiaoning Du, Zhe Zhao, Fu Song, Yang Liu

In this paper, we conduct the first comprehensive and systematic study of the adversarial attacks on SR systems (SRSs) to understand their security weakness in the practical blackbox setting.

Adversarial Attack Speaker Recognition +2

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