Architecture Overview
Our deep learning model utilizes a sophisticated architecture specifically designed for audio analysis and deepfake detection.
Key Components
- Transformer-based encoder for audio feature extraction
- Multi-head attention mechanism for pattern recognition
- Custom loss functions for improved detection accuracy
- Real-time processing capabilities
Technical Specifications
- Model Size: 500M parameters
- Training Data: 100,000+ audio samples
- Accuracy: 98.5% on test set
- Processing Time: < 1 second per audio file