activity
20242026
most citedWhat Does an Audio Deepfake Detector Focus on? A Study in the Time Domain

7 citations · 15 across the 9 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

eess.AS2024

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…

cs.SD2024★ 3 cited

SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection

Yi Zhu, Surya Koppisetti, Trang Tran +1

Audio deepfake detection (ADD) is crucial to combat the misuse of speech synthesized from generative AI models. Existing ADD models suffer from generalization issues, with a large…

cs.CV2024★ 3 cited

AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection

Trevine Oorloff, Surya Koppisetti, Nicolò Bonettini +5

With the rapid growth in deepfake video content, we require improved and generalizable methods to detect them. Most existing detection methods either use uni-modal cues or rely on…

cs.CV2024

Common Sense Reasoning for Deepfake Detection

Yue Zhang, Ben Colman, Xiao Guo +2

State-of-the-art deepfake detection approaches rely on image-based features extracted via neural networks. While these approaches trained in a supervised manner extract likely fake…

cs.CV2024★ 1 cited

Common-Sense Bias Modeling for Classification Tasks

Miao Zhang, Zee fryer, Ben Colman +2

Machine learning model bias can arise from dataset composition: correlated sensitive features can distort the downstream classification model's decision boundary and lead to perfor…