Vocoder Fingerprint

Vocoder fingerprinting focuses on identifying the specific vocoder used to generate synthetic speech or audio, leveraging unique artifacts left in the waveform. Current research employs machine learning models, often adapting existing architectures like RawNet2, to detect these subtle fingerprints, treating vocoder identification as a crucial step in broader fake audio detection or source attribution tasks. This research is vital for combating the spread of disinformation and deepfakes, with applications in forensic analysis, intellectual property protection, and ensuring the security of robotic systems.