MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection

arXiv:2608. 09593v1 Announce Type: cross Abstract: Recent advances in speech synthesis and audio generation have made high-fidelity acoustic forgery low-cost and difficult to attribute, enabling a realistic attack scenario in which speech and background audio are independently manipulated over otherwise authentic video.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

• llms
• robotics
• multimodal
• benchmarks