MADBench introduces a component-aware audio-visual deepfake benchmark with independently manipulated speech and environmental audio, and shows environmental manipulation is easier to detect than synthetic speech.
Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SD 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection
MADBench introduces a component-aware audio-visual deepfake benchmark with independently manipulated speech and environmental audio, and shows environmental manipulation is easier to detect than synthetic speech.