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Deepfake Audio Detection V2
A Deepfake audio detection model fine-tuned on audio folder datasets, achieving 99.73% accuracy
Downloads 2,289
Release Time : 6/17/2024
Model Overview
This model is used to detect Deepfake-generated forged audio, effectively identifying artificially synthesized speech content
Model Features
High accuracy
Achieves 99.73% accuracy on the evaluation set
Optimized training
Trained using cosine annealing learning rate scheduler and Adam optimizer
Model Capabilities
Audio classification
Deepfake audio detection
Voice authenticity verification
Use Cases
Security verification
Voice identity verification
Detects forged audio in voice calls or voice verification
Effectively prevents voice spoofing attacks
Content moderation
Forged audio identification
Identifies Deepfake audio on social media or audio/video platforms
Helps platforms maintain authentic content
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