A dual-branch fusion model with XLS-R, BEATs, Matching Head, and cross-attention achieves 70.20% F1-score and 16.54% environmental EER on CompSpoofV2, outperforming the baseline for component-level deepfake detection.
Deep attention mechanism residual network for audio deepfake detection using multi scale cepstral coeffi- cient features
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Deepfake Audio Detection Using Self-supervised Fusion Representations
A dual-branch fusion model with XLS-R, BEATs, Matching Head, and cross-attention achieves 70.20% F1-score and 16.54% environmental EER on CompSpoofV2, outperforming the baseline for component-level deepfake detection.