A Hybrid Deep Learning Framework for Real and Deepfake Voice Detection

Puntos clave

• Voice detection accuracy improves in distinguishing real from deepfake audio using the proposed framework.
• The model achieves 92% accuracy, indicating a strong capacity for detecting altered voices under various conditions.
• Hybrid deep learning approach uses advanced algorithms and neural networks to analyze audio datasets effectively.
• Highlights the necessity for ongoing advancements in AI to combat deepfake technologies in digital media.