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Aditya Tirumala Bukkapatnam

2 papers indexed

arxivcs.SDcs.AI2026-07-03

DETECT-3B-Omni is Agnostic of Content and Demographics

Nicolas M. Müller, Aditya Tirumala Bukkapatnam, Dominik Schnieders, Zohaib Ahmed

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 of semantic independence for Resemble AI's detector, DETECT-3B-Omni. Using 10,240 audio samples fro…

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arxivcs.SDcs.AI2026-06-28

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 over sequences of everyday audio transformations (codec transcoding, additive noise, reverberation,…

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