Papers with unified deepfake detector
A Unified Feature Mixture Framework for Joint Speech and Singing Deepfake Detection (2026.findings-acl)
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| Challenge: | Existing methods for deepfake detection fail under speech-to-singing domain shift . a speech-retentive multi-domain fine-tuning strategy enables adaptation to singing . |
| Approach: | They propose a unified deepfake detector based on a multi-branch mixture-of-experts architecture that integrates three complementary feature views. |
| Outcome: | The proposed detector achieves 1.82% EER on CtrSVDD, compared to 37–62% for existing detectors . it can generalize to unseen generators and preserve strong speech performance . |