Multimodal foundation models outperform speech and music models for closed-set source attribution of singing voice deepfakes on CtrSVDD, with Chernoff-distance fusion of LanguageBind and ImageBind reaching 91.2% accuracy.
Ctrsvdd: A benchmark dataset and baseline analysis for controlled singing voice deepfake detection,
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Towards Source Attribution of Singing Voice Deepfake with Multimodal Foundation Models
Multimodal foundation models outperform speech and music models for closed-set source attribution of singing voice deepfakes on CtrSVDD, with Chernoff-distance fusion of LanguageBind and ImageBind reaching 91.2% accuracy.