CHATBOTEMOTIONRECOGNITIONAND MUSIC RECOMMENDATION

Abstract

In recent years, intelligent chatbots have become an integral part of human-computer interaction, enabling personalized user experiences. Recognizing a user’s emotions accurately allows chatbots to respond empathetically and provide relevant suggestions. This project presents a chatbot system capable of emotion recognition using natural language processing (NLP) and machine learning techniques. The detected emotions are then used to recommend personalized music playlists, enhancing user engagement and satisfaction. The system leverages sentiment analysis, deep learning modelssuch as LSTMor CNN, and amusic database tomap emotional states to appropriate songs. Experimental results demonstrate that the hybrid approach effectively identifies user emotions and provides context-aware music recommendations, creating an interactive and emotionally intelligent chatbot experience. This integration of emotion recognition with music recommendation has potential applications in entertainment, mental health support, and personalized digital assistants.