Paper Title
Multimodal Smart Attendance System Using Face Recognition and Voice Verification for Faculty Monitoring
Article Identifiers
Registration ID: IJNRD_327356
Published ID: IJNRD2607346
: https://doi.org/10.56975/ijnrd.v11i7.327356
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Keywords
Face Recognition, Voice Verification, Multimodal Biometrics, Deep Learning, Image Preprocessing, Artificial Intelligence
Abstract
The traditional way to track attendance in educational institutions involves manual registers, RFID cards or biometric fingerprint devices, but all these methods have some issues, such as proxy attendance, inefficiency and error rates. To solve these problems, this work seeks to create a smart attendance system with face recognition and voice verification technique for higher accuracy and security. It is a multimodal biometric system that allows the faculty members to be identified reliably in the real world in campus environment. Several images of the face are captured during the registration process with lighting and orientations to create a complete set of images. To improve the performance of the model, the images were preprocesses using normalization, resizing and noise reduction techniques. The lightweight YuNet model is used for face detection, which provides swift and accurate face detection even in challenging situations. Facial regions detected are then converted to unique facial embeddings using SFace model. These embeddings can be compared to so-called stored data using similarity measures such as cosine similarity and Euclidean distance. Voice verification is also provided with Resemblyzer for extracting voice embeddings and verifying their identity. To prevent double counting, the system provides for the recording of attendance once only during a specified period. A special admin panel makes it easy to take care of faculty records and attendance reports. Combining visual and audio biometrics provides for greater accuracy and impersonation resistance. The proposed system shows better accuracy, automation and security than the traditional ones. It is scalable and can be used in real time in an educational service. The system is a smart, efficient and robust solution for attendance of faculty members at a whole.
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How To Cite (APA)
Utkarsha N. Vadgaonkar & Dr. Sangram T. Patil (July-2026). Multimodal Smart Attendance System Using Face Recognition and Voice Verification for Faculty Monitoring. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(7), d438-d446. https://doi.org/10.56975/ijnrd.v11i7.327356
Issue
Volume 11 Issue 7, July-2026
Pages : d438-d446
Other Publication Details
Paper Reg. ID: IJNRD_327356
Published Paper Id: IJNRD2607346
Research Area: Other area not in list
Author Type: Indian Author
Country: Kolhapur, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2607346.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2607346
Crossref DOI: https://doi.org/10.56975/ijnrd.v11i7.327356
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