YouTube Summarization

YouTube Summarization

Dr.V. Indu Nair, Guide, SNS College of Engineering, Coimbatore, India

Dr.P. Sumathi, Head of Department, SNS College of Engineering, Coimbatore, India

Krithika M, Student, SNS College of Engineering, Coimbatore, India

SriVignesh A, Student, SNS College of Engineering, Coimbatore, India

Sudharsan S, Student, SNS College of Engineering, Coimbatore,India

 Vijith Kumar V, Student, SNS College of Engineering, Coimbatore, India

Abstract The YouTube Summarizer is an AI-powered web application designed to enhance digital content consumption by providing concise summaries of YouTube videos. Developed using the Next.js framework, the platform integrates state-of-the-art language models such as GPT, Gemini, and LLaMA to generate context-aware summaries from extracted video transcripts. It supports multilingual outputs and offers summary customization—like video-style or podcast-style formats—tailored to user preferences. The application features a sleek, responsive UI with session history tracking, making it accessible and efficient for students, researchers, and content creators aiming to quickly grasp video content without full viewing. Keywords — YouTube Summarizer, Natural Language Processing, GPT, Gemini, LLaMA, Next.js, AI-based Tool, Multilingual Summarization. This research presents an AI-powered web application that addresses the growing challenge of processing lengthy YouTube videos by generating customizable, context-aware summaries. The tool leverages cutting-edge transformer-based language models (GPT, Gemini, and LLaMA), capable of multilingual processing and summary style adjustments. Key parameters such as transcript quality, model selection, and summarization goals are evaluated and optimized. This approach enhances accessibility, efficiency, and content comprehension for diverse user groups including students, researchers, and educators.