Our research group is currently studying and developing listening services using spoken dialogue agents and IoT technologies to assist the "mind" of the elderly at home. However, the user identification function, an essential part of the service, has not yet been realized. It is difficult to determine the identity of the person who interacts with the spoken dialogue agent. Although with the rapid development of the artificial intelligence field, various smart devices and services using deep learning have appeared in the face recognition technology, problems exist, including costs and computational resources to build and apply a recognition model. The purpose of this paper is to develop a facial identification system using the pre-trained model and spoken dialogue agent. Our key ideas include automatic training data generation by spoken dialogue between the user and the agent and the acquisition and comparison of facial features using a pre-trained model. In this way, our face identification system can be easier introduced and expected with only a general-purpose computer and a Web camera, without needing a conventional Internet connection and manual labeling of training data.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.