An Intelligent Vehicle Alarm User Terminal System Based on Emotional Identification Technology

Abstract

Negative emotions could increase the risks of traffic accidents. However, the driver’s emotional identification is rarely considered in the current design of intelligent vehicle alarm user terminals (IVAUTs). To solve the problem, this paper tries to design an IVAUT system based on emotional identification technology. Firstly, the transformer network was combined with a convolutional neural network (CNN) into a voice emotional identification system for intelligent vehicle alarm, and an emotional labeling approach was provided. Next, a bimodal fusion model was developed based on decompose-CNNs, which includes an appearance module, an optical flow module, and a bimodal fusion module. The proposed emotional identification approach was proved effective through experiments.