1 code implementation • 13 Jun 2023 • Michele Panariello, Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans
We present Malafide, a universal adversarial attack against automatic speaker verification (ASV) spoofing countermeasures (CMs).
1 code implementation • 13 Mar 2023 • Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans
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.
1 code implementation • 1 Sep 2022 • Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans
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.
1 code implementation • 28 Feb 2022 • Wanying Ge, Massimiliano Todisco, Nicholas Evans
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.
2 code implementations • 7 Oct 2021 • Wanying Ge, Jose Patino, Massimiliano Todisco, Nicholas Evans
Substantial progress in spoofing and deepfake detection has been made in recent years.
1 code implementation • 26 Jul 2021 • Wanying Ge, Jose Patino, Massimiliano Todisco, Nicholas Evans
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.
1 code implementation • 7 Apr 2021 • Wanying Ge, Michele Panariello, Jose Patino, Massimiliano Todisco, Nicholas Evans
This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems.