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Privacy-Aware Speech Recognition Using Secure AI Models

Year: 2025

Type: article

Abstract: 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.

Source: International Journal for Research in Applied Science and Engineering Technology

DOI: 10.22214/ijraset.2025.69589

Author: Shreshth Sharma

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409837130

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