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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 51–60 of 74 papers

TitleStatusHype
Audios Don't Lie: Multi-Frequency Channel Attention Mechanism for Audio Deepfake Detection—0
ALLM4ADD: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection—0
Benchmarking Audio Deepfake Detection Robustness in Real-world Communication Scenarios—0
Spoofing-Robust Speaker Verification Based on Time-Domain Embedding—0
Strong Alone, Stronger Together: Synergizing Modality-Binding Foundation Models with Optimal Transport for Non-Verbal Emotion Recognition—0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Complex-valued neural networks for voice anti-spoofing—0
Targeted Augmented Data for Audio Deepfake Detection—0
Cross-Domain Audio Deepfake Detection: Dataset and Analysis—0
DeePen: Penetration Testing for Audio Deepfake Detection—0
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