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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 41–50 of 74 papers

TitleStatusHype
Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech DetectionCode2
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake DetectionCode0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Harder or Different? Understanding Generalization of Audio Deepfake Detection—0
Generalized Source Tracing: Detecting Novel Audio Deepfake Algorithm with Real Emphasis and Fake Dispersion StrategyCode1
The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake AudioCode2
Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models—0
CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive LearningCode1
Retrieval-Augmented Audio Deepfake Detection—0
Cross-Domain Audio Deepfake Detection: Dataset and Analysis—0
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