5 papers
Alethia: A Foundational Encoder for Voice Deepfakes
Yi Zhu, Brahmi Dwivedi, Jayaram Raghuram +1
Existing voice deepfake detection and localization models rely heavily on representations extracted from speech foundation models (SFMs). However, downstream finetuning has now rea…
ICLAD: In-Context Learning with Comparison-Guidance for Audio Deepfake Detection
Benjamin Chou, Yi Zhu, Surya Koppisetti
Audio deepfakes pose a significant security threat, yet current state-of-the-art (SOTA) detection systems do not generalize well to realistic in-the-wild deepfakes. We introduce a…
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations
Petr Grinberg, Ankur Kumar, Surya Koppisetti +1
Evaluating explainability techniques, such as SHAP and LRP, in the context of audio deepfake detection is challenging due to lack of clear ground truth annotations. In the cases wh…
What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain
Petr Grinberg, Ankur Kumar, Surya Koppisetti +1
Adding explanations to audio deepfake detection (ADD) models will boost their real-world application by providing insight on the decision making process. In this paper, we propose…
Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge
Yi Zhu, Chirag Goel, Surya Koppisetti +3
Audio deepfake detection is crucial to combat the malicious use of AI-synthesized speech. Among many efforts undertaken by the community, the ASVspoof challenge has become one of t…