Noise-Resilient Audio Deepfake Detection: Survey and Benchmarks
Analysis
This research addresses a critical vulnerability in audio deepfake detection: noise. By focusing on signal-to-noise ratio (SNR) and providing practical recipes, the study offers valuable contributions to the robustness of deepfake detection systems.
Key Takeaways
- •The paper surveys existing methods for audio deepfake detection.
- •It introduces SNR-based benchmarks to evaluate performance in noisy environments.
- •Practical recipes are provided to improve the resilience of detectors.
Reference
“The research focuses on Signal-to-Noise Ratio (SNR) in audio deepfake detection.”