Fake Audio

Fake audio detection is a rapidly evolving field focused on identifying manipulated audio, including deepfakes, to mitigate the risks of fraud, misinformation, and other malicious activities. Current research emphasizes developing robust detection models using diverse architectures, such as ResNets, attention mechanisms, and bidirectional state-space models, often incorporating multiple audio features and addressing challenges like partially fake audio and cross-dataset generalization. The ability to reliably detect fake audio is crucial for maintaining information integrity, supporting forensic investigations, and enhancing the security of voice-based authentication systems.