What Do Deepfake Speech Detectors Actually Hear?
Researchers have developed a new method to understand how deepfake speech detectors make their decisions. By using Integrated Gradients on self-supervised representations, the technique can pinpoint specific moments in audio where evidence of a deepfake is detected. This analysis revealed that different detectors, such as AASIST, CA-MHFA, and SLS, rely on distinct audio cues, ranging from environmental sounds to phoneme artifacts and spectral integrity. AI
IMPACT Provides crucial insights into the decision-making processes of AI systems used for detecting synthetic media.