2 papers
cs.SD2026
DETECT-3B-Omni is Agnostic of Content and Demographics
Nicolas M. Müller, Aditya Tirumala Bukkapatnam, Dominik Schnieders +1
A trustworthy and GDPR-compliant deepfake audio detector must base its decisions on acoustic artifacts, not on what is being said or who is speaking. We present a large-scale study…
cs.SD2026
Proteus: Automated Adversarial Robustness Testing for Audio Deepfake Detectors
Nicolas M. Müller, Aditya Tirumala Bukkapatnam, Zohaib Ahmed
We present Proteus, a framework developed at Resemble AI for automated robustness testing of our audio deepfake detection system. Given a detector, Proteus systematically searches…