Abstract: The Intelligent Multimodal Notes Generation System is designed to simplify the process of note-making by integrating multiple input modes such as text, audio, and visual content. It leverages Artificial Intelligence and Natural Language Processing (NLP) to automatically analyze lectures, documents, or multimedia inputs and convert them into well-structured, concise, and context-aware notes. The system identifies key concepts, summarizes content, and organizes it in a user-friendly format, enhancing learning efficiency and retention. It supports features like speech-to-text conversion, summarization, keyword extraction, and diagram or image interpretation, making it highly beneficial for students, educators, and professionals. By reducing manual effort and ensuring accuracy, this system addresses the challenges of traditional note-taking and provides personalized, intelligent, and accessible digital notes.
Keywords: Artificial Intelligence, Multimodal Input, NLP, Note Generation, Summarization, Speech-to-Text, Educational Technology, Knowledge Extraction, Automation, Smart Learning System
Downloads:
|
DOI:
10.17148/IJARCCE.2026.15222
[1] Prof. Purushottam Chavan, Miss. Mansi Ahire, Miss. Shweta Jadhav, Miss. Ishwari Kadam, Miss. Rajshri Kale, "Intelligent Multimodal Notes Generation System," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.15222
