SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 74 papers

TitleStatusHype
Forensic deepfake audio detection using segmental speech features—0
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap—0
Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation—0
Towards generalisable and calibrated synthetic speech detection with self-supervised representations—0
Harder or Different? Understanding Generalization of Audio Deepfake Detection—0
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations—0
IndieFake Dataset: A Benchmark Dataset for Audio Deepfake Detection—0
Investigating Prosodic Signatures via Speech Pre-Trained Models for Audio Deepfake Source Attribution—0
Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge—0
Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models—0
Show:102550
← PrevPage 5 of 8Next →

No leaderboard results yet.