YouTube Lecture Video Summarizer and Key Concept Extractor using NLP and Computer Vision

Author(s)	Mr. Bright M S
Country	India
Abstract	With the exponential growth of video content on platforms such as YouTube, there is an increasing demand for intelligent systems that can summarize videos and extract essential information automatically. This paper proposes a hybrid system that combines state-of- the-art Natural Language Processing (NLP) techniques with Computer Vision to create a YouTube video summarizer and key concept extractor. The proposed system performs automatic video downloading, audio extraction, speech transcription, text summarization, key concept extraction, scene and keyframe detection, graph identification, and finally compiles the processed information into both a downloadable PowerPoint presentation and a detailed notes PDF. The system provides a comprehensive and structured overview of a video’s content in both textual and visual form, enhancing learning efficiency and infor- mation retrieval.
Keywords	YouTube Summarization, Whisper, BART, KeyBERT, NLP, Key Concept Ex- traction, PowerPoint Generation, PDF Notes, OpenCV, Scene Detection, Graph Detection
Field	Computer Applications
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-09-28
DOI	https://doi.org/10.71097/IJSAT.v16.i3.8467
Short DOI	https://doi.org/g949v9

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