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@article{201296,
        author = {PENTI VIJAY KUMAR and Ms.T.Shakila and POGIRI SATHVIK and PITHANI SIVA RAMA PRAVEEN and PATNAM DHANUSH},
        title = {AUTOMATED ATTENDANCE MANAGEMENT USING FACE AND VOICE DUAL BIOMETRIC VERIFICATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {3273-3284},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201296},
        abstract = {This paper proposes an Automated Attendance Management System using dual biometric verification based on face and voice recognition to ensure secure and reliable attendance tracking. Traditional single- modality systems are vulnerable to spoofing attacks such as photo or audio replay, which reduces their effectiveness. To overcome these limitations, the proposed system captures a live facial image and a short voice sample during user authentication. These inputs are processed using deep learning models to extract unique embeddings, and a fusion mechanism combines both scores to make a final decision. If authentication is successful, attendance is automatically recorded with date and time in a centralized database. The system is designed with a modular architecture, enabling easy deployment in classrooms, workplaces, and remote learning environments. This approach significantly reduces proxy attendance, enhances security, and improves overall system robustness and accuracy.},
        keywords = {Automated Attendance System, Face Recognition, Voice Recognition, Dual Biometric Authentication, Multimodal Biometrics, Deep Learning, Feature Extraction, Score Fusion, Anti- Spoofing, Real-time Authentication, FastAPI, SQLite Database, Secure Access Control, Proxy Attendance Prevention, AI-based Verification},
        month = {May},
        }