An Intelligent Psychological Emotion Management System based on Multi-turn Voice Dialogue

This research explores an intelligent psychological emotion management system based on multi-turn voice dialogue technology. The system aims to recognize users' emotional states in real time by analyzing their voice interaction content and tone characteristics, and provide intelligent emotion management suggestions. By constructing a supervised hybrid emotion recognition model and integrating natural language processing and emotion recognition technologies, we have achieved the monitoring and regulation of user emotions. Compared to large language models and unsupervised learning methods, our model demonstrates superior accuracy and real-time performance in emotion recognition. Experimental results validate the effectiveness and feasibility of the system, providing a new technological solution for the field of psychological emotion management and advancing the application of intelligent technology in the realm of mental health. Through algorithm optimization and user experience enhancement, this research aims to bring practical emotion management tools to a wider audience, contributing to improved mental well-being.