Abstract
The problem of the aging of the world's population is becoming more and more serious. Home care based on the Internet of Things technology is one of the solutions to the problem of elderly living alone. Elderly emotion recognition is an important challenge facing smart home care. To solve this problem, this paper proposes a deep learning based emotion recognition framework for the elderly living alone, composed of four deep learning networks, of which three deep learning networks process speech, text, and image data respectively. These data come from companion robots deployed in elderly homes is used as input data for the fourth deep learning network. Through the training of the annotated data set, an elderly emotion recognition model that can handle heterogeneous data (i.e., voice, text, and image data) is obtained.
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