International Journal of Scientific Research and Engineering Development

This project introduces a Song Recommendation Bot designed to suggest music tracks based on the user's daily experiences and emotional states. By leveraging natural language processing (NLP) techniques, the bot interprets user input describing their day, identifying key emotions and themes. It then maps these insights to a curated music database to provide personalized song recommendations that resonate with the user's current mood and experiences. The bot integrates with popular music streaming services, enabling seamless access to a wide array of tracks. The aim of this project is to enhance the user's music discovery journey by aligning song suggestions with their emotional context, thus creating a more meaningful and engaging listening experience. This documentation outlines the system's architecture, implementation details, key features, and evaluation metrics, demonstrating the bot's capability to understand user sentiments and deliver appropriate music recommendations