NotetheNote: An AI Study Companion with a Music Recommendation System Utilizing Mood Detection
摘要
In the expanding digital era where innovations are the foundation of economic drive, the innovation of AI technologies is changing the way we learn, relax, and interact with systems. Multiple-platform users struggle without an integrated learning and entertainment system. We solve this challenge with AI-based question-answer creation, real-time emotion-based music recommendation, and an interactive LLM-based questioning system. This paper introduces a creative web application that combines optical character recognition (OCR) using PyTesseract, a large language model (LLM) interface, and convolutional neural networks (CNN) to create a flexible and user-friendly platform. This application offers three main functionalities. The first one generates questions and answers based on user-inputted text or text extracted from images; the second one recommends songs by detecting real-time facial expressions; and the last one allows users to ask questions or search for information using a built-in LLM interface. This paper aims to increase user interaction by combining learning and entertainment on one platform. We evaluated its performance using metrics such as text recognition accuracy, question relevance, emotion detection accuracy, and user satisfaction. Results showed high efficiency and accuracy across all features. The recommended solution minimizes dependency on other platforms, providing users with a smooth and combined experience. We are getting 96% accuracy in text extraction, 94% accuracy in question-answer relevance, and 73% emotion detection. This solution fills the gap between education and entertainment, providing one platform for education, entertainment, and intelligent support.