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
Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set ConditionCode0
Investigating Prosodic Signatures via Speech Pre-Trained Models for Audio Deepfake Source Attribution—0
Spoofing-Robust Speaker Verification Based on Time-Domain Embedding—0
Audios Don't Lie: Multi-Frequency Channel Attention Mechanism for Audio Deepfake Detection—0
Toward Transdisciplinary Approaches to Audio Deepfake Discernment—0
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap—0
Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge—0
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection—0
Strong Alone, Stronger Together: Synergizing Modality-Binding Foundation Models with Optimal Transport for Non-Verbal Emotion Recognition—0
Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?Code0
Show:102550
← PrevPage 5 of 8Next →

No leaderboard results yet.