Deepfake Audio Detection Model Fine tuned Wav2Vec2 model for detecting AI generated speech. Determines if audio was spoken by a human or created by AI text to speech/voice cloning software. Model Details Model Description Fine tuned Wav2Vec2 transformer for binary audio classification (real vs AI generated speech). Trained to distinguish authentic human speech from synthetic audio generated by AI text to speech and voice cloning services including: ElevenLabs Amazon Polly Hexgrad Kokoro Hume AI Speechify Luvvoice Developed by: Gary A. Stafford Note: This model uses transfer learning from a base model already trained for deepfake detection. Fast convergence is expected due to task similarity and TTS engine overlap with the base model's training data. How to Use Installation Install the required dependencies: Optional: For GPU acceleration (recommended): Quick Start Expected Input Audio format: WAV, MP3, FLAC, or any format supported by librosa Sample rate: Automatically resampled to 16kHz Channels: Converted to mono Duration: Optimal performance on 2.5 13 second clips (model training range) Output The model outputs logits (raw, unnormalized scores) for two classes: Class 0: Real (hu…
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