This project aims to develop a deep learning model to distinguish between real and synthetic audio, addressing concerns like voice deepfakes, fraud, and misinformation. By analyzing state-of-the-art detection methods, exploring different audio representations, and training models like CNNs and Transformers, the project seeks to improve classification accuracy and thereby strengthen security in digital environments.
