MixFake is a new benchmark for mixed-authenticity audio and a multi-stream prompt tuning method achieves 0.95% EER foreground and 7.72% absolute gain in complex background deepfake detection.
CLAD: Robust audio Deepfake detection against manip- ulation attacks
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Proteus automates discovery of audio transformation chains that evade deepfake detectors using BFS and Q-learning, then uses the results to retrain the detector.
Cosine similarity in SupCon with a delayed negative queue on wav2vec2 XLS-R yields the lowest equal error rates for deepfake audio detection on in-the-wild and pooled evaluations.
citing papers explorer
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MixFake: Benchmarking and Enhancing Audio Deepfake Detection in Diverse Real-world Mixed Audio
MixFake is a new benchmark for mixed-authenticity audio and a multi-stream prompt tuning method achieves 0.95% EER foreground and 7.72% absolute gain in complex background deepfake detection.
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Proteus: Automated Adversarial Robustness Testing for Audio Deepfake Detectors
Proteus automates discovery of audio transformation chains that evade deepfake detectors using BFS and Q-learning, then uses the results to retrain the detector.
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Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection
Cosine similarity in SupCon with a delayed negative queue on wav2vec2 XLS-R yields the lowest equal error rates for deepfake audio detection on in-the-wild and pooled evaluations.