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A Smart Receptionist Implementing Facial Recognition and Voice Interaction
Osman Mohammed Ahmed, Ahmad R. Hadaegh, Yanyan Li
Pages - 37 - 47     |    Revised - 30-06-2021     |    Published - 01-08-2021
Volume - 15   Issue - 3    |    Publication Date - August 2021  Table of Contents
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KEYWORDS
Face Recognition, Deep Learning, Django Framework, Image Processing.
ABSTRACT
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
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Mr. Osman Mohammed Ahmed
Department of Computer Science and Information Systems, California State University San Marcos, San Marcos, 92096 - United States of America
Dr. Ahmad R. Hadaegh
Department of Computer Science and Information Systems, California State University San Marcos, San Marcos, 92096 - United States of America
ahadaegh@csusm.edu
Mr. Yanyan Li
Department of Computer Science and Information Systems, California State University San Marcos, San Marcos, 92096 - United States of America