This paper explores the application of emotion recognition technology to enhance user experience in real-time environments. The study employs convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to analyze facial expressions and voice emotions, respectively. An experimental group using an emotion recognition system is compared with a control group using a traditional online learning platform. The results show that the emotion recognition system significantly improves user engagement, learning outcomes, and overall satisfaction. The system reduces task completion time by 14.3%, lowers error rates by 50%, and increases user satisfaction by 18.4%. The paper highlights the potential of emotion recognition technology in various domains, including online education, healthcare, customer service, and entertainment. However, challenges such as multimodal data integration, real-time processing, and privacy concerns remain. The study concludes that emotion recognition technology, through personalized and adaptive interactions, holds significant promise for enhancing user experiences.This paper explores the application of emotion recognition technology to enhance user experience in real-time environments. The study employs convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to analyze facial expressions and voice emotions, respectively. An experimental group using an emotion recognition system is compared with a control group using a traditional online learning platform. The results show that the emotion recognition system significantly improves user engagement, learning outcomes, and overall satisfaction. The system reduces task completion time by 14.3%, lowers error rates by 50%, and increases user satisfaction by 18.4%. The paper highlights the potential of emotion recognition technology in various domains, including online education, healthcare, customer service, and entertainment. However, challenges such as multimodal data integration, real-time processing, and privacy concerns remain. The study concludes that emotion recognition technology, through personalized and adaptive interactions, holds significant promise for enhancing user experiences.