KAN You Hear the Truth? Audio Deepfake Detection with Kolmogorov-Arnold Networks
Résumé
Kolmogorov-Arnold Networks (KAN) have recently emerged as a promising alternative to traditional multilayer perceptrons, offering superior performance and greater interpretability. In this work, we explore the potential of KAN by demonstrating its ability to enhance audio deepfake detection and robustness. To further improvement, we employ multi-level token classification by leveraging speech representations of foundation model. Experimental results across multiple evaluation datasets demonstrate that our approach enhances both specialization and generalization. These findings provide potential insights into the integration of KAN, laying the way for future research in this domain.
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