arXiv Artificial Intelligence

CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection

2 hours ago 15.09.2026 07:00 👁 2 views
CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection

Quick summary

arXiv:2609.13842v1 Announce Type: cross Abstract: Recent advances in speech synthesis and voice conversion have made deepfake speech increasingly realistic, making generalization to unseen spoofing attacks a critical challenge. Pretrained speech and audio models offer a promising direction for improving robustness to such unseen attacks. Self-supervised learning (SSL) models capture fine-grained, low-level acoustic characteristics, whereas Auditory Large Language Models (ALLMs) provide higher-level contextual representations. These complementary views can provide useful cues for improving gene

Key takeaways

  • arXiv:2609.13842v1 Announce Type: cross Abstract: Recent advances in speech synthesis and voice conversion have made deepfake speech increasingly realistic, making generalization to unseen spoofing attacks a critical challenge.
  • Pretrained speech and audio models offer a promising direction for improving robustness to such unseen attacks.
  • Self-supervised learning (SSL) models capture fine-grained, low-level acoustic characteristics, whereas Auditory Large Language Models (ALLMs) provide higher-level contextual representations.

Why it matters

“CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection” shows why AI risk cannot be reduced to answer accuracy. Access controls, logging, human approval and incident response need to be designed into the workflow from the start.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗