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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 26–50 of 74 papers

TitleStatusHype
End-to-end anti-spoofing with RawNet2Code1
IndieFake Dataset: A Benchmark Dataset for Audio Deepfake Detection—0
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations—0
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake DetectionCode0
Few-Shot Speech Deepfake Detection Adaptation with Gaussian ProcessesCode0
EnvSDD: Benchmarking Environmental Sound Deepfake Detection—0
Forensic deepfake audio detection using segmental speech features—0
Replay Attacks Against 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
Measuring the Robustness of Audio Deepfake DetectorsCode0
DeePen: Penetration Testing for Audio Deepfake Detection—0
A Preliminary Exploration with GPT-4o Voice Mode—0
Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation—0
What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain—0
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
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