5 papers
Investigating voiced and unvoiced regions of speech for audio deepfake detection
Ganesh Sivaraman, Hemlata Tak, Elie Khoury
Deep neural network based deepfake detection systems have achieved high levels of accuracy on benchmark datasets and competitions. However, most models lack interpretability. It is…
Pindrop it! Audio and Visual Deepfake Countermeasures for Robust Detection and Fine Grained-Localization
Nicholas Klein, Hemlata Tak, James Fullwood +5
The field of visual and audio generation is burgeoning with new state-of-the-art methods. This rapid proliferation of new techniques underscores the need for robust solutions for d…
Open-Set Source Tracing of Audio Deepfake Systems
Nicholas Klein, Hemlata Tak, Elie Khoury
Existing research on source tracing of audio deepfake systems has focused primarily on the closed-set scenario, while studies that evaluate open-set performance are limited to a sm…
Phonetic Richness for Improved Automatic Speaker Verification
Nicholas Klein, Ganesh Sivaraman, Elie Khoury
When it comes to authentication in speaker verification systems, not all utterances are created equal. It is essential to estimate the quality of test utterances in order to accoun…
Source Tracing of Audio Deepfake Systems
Nicholas Klein, Tianxiang Chen, Hemlata Tak +2
Recent progress in generative AI technology has made audio deepfakes remarkably more realistic. While current research on anti-spoofing systems primarily focuses on assessing wheth…