Analysis of Multimodal Human-Computer Interactive Techniques for Emotion Regulation

Abstract

Multimodal interaction is a technique that integrates multiple perceptual modalities and emotion modeling methods. This paper explores the importance and application prospects of this technique in the field of affective computing and human-computer interaction by synthesizing and analyzing existing research. This paper describes the traditional unimodal interaction methods and their limitations, and discusses in detail several key components of multimodal interaction technology, including how facial expression recognition, speech emotion analysis, and body gesture recognition can be used in an integrated manner. Deep learning-based emotion modeling methods are described, and how to combine these methods with multimodal interaction techniques is explored. Finally, the potential applications of the technology in human-computer interaction and mental health are demonstrated by designing a new multimodal interaction system. The aim of this paper is to provide an insight for researchers to promote research and innovation in the field of emotional intelligence for the development and application of human-computer interaction systems with more emotion-aware and emotion-regulating capabilities.