30 citations · 69 across the 11 of their papers we have counts for
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cs.SD2022★ 1 cited
Defense Against Adversarial Attacks on Audio DeepFake Detection
Piotr Kawa, Marcin Plata, Piotr Syga
Audio DeepFakes (DF) are artificially generated utterances created using deep learning, with the primary aim of fooling the listeners in a highly convincing manner. Their quality i…
cs.SD2022
SpecRNet: Towards Faster and More Accessible Audio DeepFake Detection
Piotr Kawa, Marcin Plata, Piotr Syga
Audio DeepFakes are utterances generated with the use of deep neural networks. They are highly misleading and pose a threat due to use in fake news, impersonation, or extortion. In…
cs.SD2022★ 30 cited
Attack Agnostic Dataset: Towards Generalization and Stabilization of Audio DeepFake Detection
Piotr Kawa, Marcin Plata, Piotr Syga
Audio DeepFakes allow the creation of high-quality, convincing utterances and therefore pose a threat due to its potential applications such as impersonation or fake news. Methods…