EMOTIONALLY INTELLIGENT AI: ENHANCING HUMAN-COMPUTER INTERACTION THROUGH NLP AND SENTIMENT ANALYSIS

Abstract

The evolution of human-computer interaction (HCI) has reached a progressive stage with the development of emotionally intelligent artificial intelligence (AI) systems. These systems are designed to understand, recognize, and appropriately respond to user emotions, enhancing both Dialogue coherence and user experience. This research focuses on creating the AI with emotional intelligence inspired platform that uses the NLP, sentiment analysis to make conversation more friendly and attractive. So, rather than your typical AI-driven conversation tools, which just follow programmed responses, this one change based on your mood — creating more emotional, realistic replies. The device features real-time emotion recognition, a transformer-based model and a generative AI model to produce empathetic responses. With the aid of cutting-edge machine learning algorithms, the model reaches an emotion recognition accuracy of 92%, surpassing traditional methods. The proposed generative model is also judged by coherence, empathy, and relevance and gets high acclaim in human evaluation. This marriage of accurate emotion detection and responders that can generate a good empathetic response is a great leap forward in AI-created agents. The study resulted the broad pertinence of expressively intellectual AI across numerous areas, including patron facility, healthcare, and psychological health support. In customer care, AI has the ability to recognize frustration and modulate tone to de-escalate unwanted interactions, increasing user satisfaction. In healthcare, it can pick up on stress and offer comfort dialogues, comforting patients. These features attest to the ability of the system to increase interaction, trust, and bonding with AI-based interfaces. As more AI systems come into everyday usage, transparent and ethical management of emotional data continue to be at the forefront of importance. Future research avenues include enhancing the detection of intricate emotional states, working with multimodal information (text, speech, facial expressions), and developing AI systems for intercultural communication. In summary, this research sets the stage for the emotionally intelligent AI of the future, closing the gap between effective task execution and productive human interaction. By enhancing AI’s ability to engage with users on an emotional level, this study contributes to the development of more human-centric, empathetic, and adaptive AI systems, shaping the future of AI-driven communication and interaction.