Audio Deepfake & Voice Clone Detector using Spectral Phase Analysis
Acoustic forensics model analyzing high-frequency bispectrum phase incoherencies to expose AI-generated ElevenLabs and VITS voice clones.
Project Overview
Extracts Constant Q-Transform (CQT) and Linear Frequency Cepstral Coefficients (LFCC) from audio files. A convolutional ResNet-SE architecture detects phase discrepancies and unnatural vocoder harmonics inherent to state-of-the-art voice cloning tools.
Extracts Constant Q-Transform (CQT) and Linear Frequency Cepstral Coefficients (LFCC) from audio files. A convolutional ResNet-SE architecture detects phase discrepancies and unnatural vocoder harmonics inherent to state-of-the-art voice cloning tools.
Acoustic forensics model analyzing high-frequency bispectrum phase incoherencies to expose AI-generated ElevenLabs and VITS voice clones.
Core Project Objectives
Capture continuous analog/digital sensor readings with robust noise filtering and hardware calibration.