Fake Voice Detection with Wav2Vec 2

This project implements a state-of-the-art deep learning model to detect synthetic or manipulated voice recordings with 99% accuracy. Using Facebook's Wav2Vec 2.0 architecture, the system analyzes audio characteristics to distinguish between genuine and fake speech.

Key Features:

• High Accuracy: Achieves 99% detection rate on test datasets
• Advanced Model: Based on Wav2Vec 2.0 transformer architecture
• Robust Detection: Identifies various types of audio deepfakes
• Efficient Processing: Optimized for performance with minimal latency

Potential applications include security systems, content verification, and fraud prevention in voice authentication scenarios.