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 21–30 of 74 papers

TitleStatusHype
Spoofing-Robust Speaker Verification Based on Time-Domain Embedding—0
Audios Don't Lie: Multi-Frequency Channel Attention Mechanism for Audio Deepfake Detection—0
XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack DetectionCode1
Toward Transdisciplinary Approaches to Audio Deepfake Discernment—0
Audio Deepfake Detection with Self-Supervised XLS-R and SLS ClassifierCode2
Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target DatasetCode1
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap—0
Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge—0
Where are we in audio deepfake detection? A systematic analysis over generative and detection modelsCode1
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection—0
Show:102550
← PrevPage 3 of 8Next →

No leaderboard results yet.