Human brain activity displays distinct patterns when exposed to fake versus real audio, offering insights for deepfake detection algorithms.
Developing real-time deepfake audio detection models for communication platforms is crucial for enhancing audio stream security and ensuring robust detection capabilities.
The study proposes a pipeline for detecting fake environmental sounds using CLAP audio embeddings, achieving high accuracy in identifying deepfake audio.
Combining human intuition with machine precision enhances deepfake detection capabilities.