Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Ge, Wanying"'
A reliable deepfake detector or spoofing countermeasure (CM) should be robust in the face of unpredictable spoofing attacks. To encourage the learning of more generaliseable artefacts, rather than those specific only to known attacks, CMs are usually
Externí odkaz:
http://arxiv.org/abs/2309.09586
We present Malafide, a universal adversarial attack against automatic speaker verification (ASV) spoofing countermeasures (CMs). By introducing convolutional noise using an optimised linear time-invariant filter, Malafide attacks can be used to compr
Externí odkaz:
http://arxiv.org/abs/2306.07655
Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verification (SASV) task. The two sub-systems are typically trained independ
Externí odkaz:
http://arxiv.org/abs/2303.07073
The spoofing-aware speaker verification (SASV) challenge was designed to promote the study of jointly-optimised solutions to accomplish the traditionally separately-optimised tasks of spoofing detection and speaker verification. Jointly-optimised sys
Externí odkaz:
http://arxiv.org/abs/2209.00506
Despite several years of research in deepfake and spoofing detection for automatic speaker verification, little is known about the artefacts that classifiers use to distinguish between bona fide and spoofed utterances. An understanding of these is cr
Externí odkaz:
http://arxiv.org/abs/2202.13693
Substantial progress in spoofing and deepfake detection has been made in recent years. Nonetheless, the community has yet to make notable inroads in providing an explanation for how a classifier produces its output. The dominance of black box spoofin
Externí odkaz:
http://arxiv.org/abs/2110.03309
Autor:
Chen, Gang, Wang, Yuhui, Li, Yongxin, Zhang, Jiaojiao, Huo, Yanrong, Ge, Wanying, Yang, Huqing
Publikováno v:
In Food Chemistry 30 August 2024 450
Publikováno v:
In Energy Reports June 2024 11:4515-4521
End-to-end approaches to anti-spoofing, especially those which operate directly upon the raw signal, are starting to be competitive with their more traditional counterparts. Until recently, all such approaches consider only the learning of network pa
Externí odkaz:
http://arxiv.org/abs/2107.12212
This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems. An example of neural architecture search, DARTS operates upon a continuous, differentiable s
Externí odkaz:
http://arxiv.org/abs/2104.03123