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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

Showing 5160 of 74 papers

TitleStatusHype
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio DeepfakeCode0
Exploring Green AI for Audio Deepfake DetectionCode0
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake DetectionCode1
Audio Deepfake Detection with Self-Supervised WavLM and Multi-Fusion Attentive Classifier0
HM-Conformer: A Conformer-based audio deepfake detection system with hierarchical pooling and multi-level classification token aggregation methodsCode1
Towards generalisable and calibrated synthetic speech detection with self-supervised representations0
FSD: An Initial Chinese Dataset for Fake Song DetectionCode1
Complex-valued neural networks for voice anti-spoofing0
The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 20230
TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection0
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