AI Mood-Based Music and Task Recommender System

This paper presents an AI Mood-Based Music and Task Recommender System that intelligently detects user emotions
and provides personalized suggestions. The system leverages machine learning, computer vision, and natural language
processing techniques to analyze facial expressions, voice tone, and textual inputs. Based on the detected emotional
state, it recommends suitable music playlists and productive or relaxing tasks. The system aims to enhance user wellbeing, reduce stress, and improve productivity. Experimental results show high accuracy in emotion detection and user
satisfaction in recommendations.