4 citations · 4 across the 3 of their papers we have counts for
5 papers
Benchmarking Audio Deepfake Detection Robustness in Real-world Communication Scenarios
Haohan Shi, Xiyu Shi, Safak Dogan +3
Existing Audio Deepfake Detection (ADD) systems often struggle to generalise effectively due to the significantly degraded audio quality caused by audio codec compression and chann…
Confusion-Aware Spectral Regularizer for Long-Tailed Recognition
Ziquan Zhu, Gaojie Jin, Hanruo Zhu +11
Long-tailed image classification remains a long-standing challenge, as real-world data typically follow highly imbalanced distributions where a few head classes dominate and many t…
Audio Deepfake Detection at the First Greeting: "Hi!"
Haohan Shi, Xiyu Shi, Safak Dogan +2
This paper focuses on audio deepfake detection under real-world communication degradations, with an emphasis on ultra-short inputs (0.5-2.0s), targeting the capability to detect sy…
Beyond Segmentation: An Oil Spill Change Detection Framework Using Synthetic SAR Imagery
Chenyang Lai, Shuaiyu Chen, Tianjin Huang +4
Marine oil spills are urgent environmental hazards that demand rapid and reliable detection to minimise ecological and economic damage. While Synthetic Aperture Radar (SAR) imagery…
Multi-Granularity Adaptive Time-Frequency Attention Framework for Audio Deepfake Detection under Real-World Communication Degradations
Haohan Shi, Xiyu Shi, Safak Dogan +2
The rise of highly convincing synthetic speech poses a growing threat to audio communications. Although existing Audio Deepfake Detection (ADD) methods have demonstrated good perfo…