Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM58563

YouTube Transcript Summarizer

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM58563

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM58563

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.

Share this article:

Authors

MSC

M Sharath Chandra

RV

R Vishnu

KSP

K Shanmukh Preetham

MHK

M Hari Krishna

Author Services & Downloads

Full Articles

Abstract

The volume of online video content is increasing rapidly, which creates a strong need for more effective ways to locate and utilize valuable information. YouTube is one of the largest video platforms, hosting a vast number of videos that contain useful knowledge. However, watching all these videos manually is time-consuming and not very efficient. This paper presents an AI-driven tool that automatically extracts text from YouTube videos and generates concise, clear summaries using advanced Natural Language Processing (NLP) techniques. The system uses methods to extract text from videos and then applies transformer models such as BART and T5 to create summaries. It cleans up the text to eliminate unnecessary parts, divides long texts into smaller segments for more effective processing, and produces summaries that retain the main ideas while being significantly shorter. The results demonstrate that this system significantly reduces video content while preserving the key meaning, making infor- mation more accessible and easier to use. The solution is capable of handling large volumes of content and can be expanded to support multiple languages, real-time processing, and integration with various tools like educational applications and content recommendation systems. This work contributes to the field of automated text summarization by providing a practical solution that links video content with NLP technologies.

KEYWORDS

Transcript Summarization Natural Language Processing Abstractive Summarization Transformer Models BART T5 Text Processing Machine Learning Video Content Analysis

Cite This Article

M Sharath Chandra, R Vishnu, K Shanmukh Preetham, M Hari Krishna, "YouTube Transcript Summarizer," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026. https://doi.org/10.55041/IJSREM58563

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

3/30/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

2

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...