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Audio Deepfake Detection

Nowadays, deepfake is now generically used by the media or people to refer to any audio or video in which important attributes have been either digitally altered or swapped, with the help of artificial intelligence (AI). Audio deepfake detection is a task that aims to distinguish genuine utterances from fake ones via machine learning techniques.

Papers

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Showing 21–30 of 74 papers

TitleStatusHype
Attack Agnostic Dataset: Towards Generalization and Stabilization of Audio DeepFake DetectionCode1
Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentationCode1
WaveFake: A Data Set to Facilitate Audio Deepfake DetectionCode1
AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention NetworksCode1
End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake DetectionCode1
End-to-end anti-spoofing with RawNet2Code1
IndieFake Dataset: A Benchmark Dataset for Audio Deepfake Detection—0
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations—0
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake DetectionCode0
Few-Shot Speech Deepfake Detection Adaptation with Gaussian ProcessesCode0
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