MRI
MRI India Journals Vol. 9 No. 4 (2025): Volume 9 Issue 4 2025

YouTube Transcript Summarizer

Authors

  • Prof. Shivani Karhale Information Technology, Parvatibai Genba Moze College Of Engineering Wagholi, Pune, Maharashtra, India
  • Isha Temkar Information Technology, Parvatibai Genba Moze College Of Engineering Wagholi, Pune, Maharashtra, India.
  • Disha Salve Information Technology, Parvatibai Genba Moze College Of Engineering Wagholi, Pune, Maharashtra, India
  • Shubham Giri Information Technology, Parvatibai Genba Moze College Of Engineering Wagholi, Pune, Maharashtra, India
  • Sakshi Mane Information Technology, Parvatibai Genba Moze College Of Engineering Wagholi, Pune, Maharashtra, India.

DOI:

https://doi.org/10.65521/ijasret.v9i4.1749

Keywords:

NLP Machine Learning Abstractive Text Summarization

Abstract

In today's world, a video transcript summarizer serves various purposes. It emphasizes the key points of a video, making it easier
for viewers to absorb relevant content. Many people watch YouTube videos for a range of reasons, such as entertainment, learning, gaining important information, or pursuing personal hobbies. However, finding a video that focuses solely on relevant content can be challenging, as many videos include unnecessary details. The main goal in most cases is to extract meaningful information from the video. This project aims to develop a video summarization system utilizing natural language processing and machine learning techniques to create concise abstractive text summaries from YouTube video transcripts, ensuring that vital aspects and information are retained. The primary focus of this project is to shorten the video scripts effectively.

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Published

2025-04-15

How to Cite

Karhale, P. S., Temkar, I., Salve, D., Giri, S., & Mane, S. (2025). YouTube Transcript Summarizer. International Journal of Advanced Scientific Research and Engineering Trends, 9(4), 62–64. https://doi.org/10.65521/ijasret.v9i4.1749

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