Privacy-Aware Speech Recognition Using Secure AI Models

This project focuses on developing a privacy-aware speech recognition system using secure AI models to protect users' speech data. The system ensures data confidentiality by employing Federated Learning (FL), Homomorphic Encryption (HE), and Differential Privacy (DP). These techniques allow the model to process and train on encrypted data without compromising privacy. The system also minimizes data transmission to cloud servers, reducing the risk of data breaches. The results demonstrate high speech recognition accuracy while maintaining strong data privacy, making it ideal for secure voice-enabled applications.