EMOTIONAL AWARENESS CHATBOT

Abstract

In recent years, speech recognition and natural language processing technologies have become important in web applications. They allow for hands-free interaction, improve user convenience, and increase accessibility. This project details the design and implementation of an Emotion-Aware AI Chatbot built with Node.js and the Express.js web framework .The system functions as a web application that captures user text input through a browser interface. It processes this text using Natural Language Processing (NLP) libraries and converts it into an emotion-classified format. The detected emotion is shown immediately on the application interface, ensuring smooth user interaction and minimal processing delays. Unlike traditional chatbot systems that only focus on response speed and accuracy, this system adds functionality by including an intelligent emotion detection module. After processing the text, the system analyses the content using keywords, sentiment analysis, and pattern recognition techniques to determine the user's emotional state. The possible states include happy, sad, angry, anxious, excited, confused, or neutral. When the system detects an emotion, it automatically creates an empathetic response suited to the user's feelings. This response appears on the chat interface along with real-time emotion analytics, such as confidence scores and sentiment metrics. All conversation logs and emotion records are securely stored in a database for documentation and future analysis. By combining real-time text processing, web technologies, structured data management, and emotion analysis, this system provides an efficient, scalable, and user-friendly way for emotionally intelligent communication. The integration of NLP with automated emotion detection shows how modern technologies can be used to improve accessibility, convenience, and empathetic human-computer interaction. System access, and supporting inclusive health through machine learning–based disease prediction.