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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM13922
Volume:
6 |
5 |
May 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
With the ever-increasing volume of video content uploaded to YouTube daily, users often struggle to find and consume relevant information efficiently. To address this challenge, we developed a YouTube Transcript Summarizer that automatically generates concise summaries from video transcripts. The system begins by extracting the transcript from a provided YouTube URL, then processes the text using natural language processing (NLP) techniques such as tokenization, stop-word removal, and sentence segmentation. After preprocessing, the system applies a combination of extractive and abstractive summarization methods to produce a clear and coherent summary that captures the essential points of the video. The tool is designed to handle videos across a wide range of topics—including education, news, and entertainment—and supports multilingual input, making it accessible to a global audience. It features a simple web-based interface where users can enter a link and instantly receive the corresponding summary. Performance is evaluated using ROUGE metrics to ensure summary quality and relevance. By offering quick insights into lengthy videos, this summarizer serves as a valuable tool for students, educators, professionals, and casual viewers looking to save time and enhance their content consumption experience.
KEYWORDS
Publication Date
6/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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