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:IJSREM62019

Transcripto

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM62019

Volume:

10 |

4 |

April 2026

Pages:

1-10

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM62019

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

AM

Abitha M

, Department of Computer Science and Engineering

Sri Shakthi Institute of Engineering and Technology, India.

Download Author Certificate

Mentors

KR

Kalaiyarasi R

, Department of Computer Science and Engineering

Sri Shakthi Institute of Engineering and Technology, India.

Download Mentor Certificate

Author Services & Downloads

Full ArticlesAcceptance Certificate

Abstract

The Transcripto AI Audio & Video Transcription Platform is designed to convert multimedia content into accurate and structured text through an intelligent and automated system. It enables users to upload audio files, video files, or provide YouTube links, which are then processed using advanced AI- based speech recognition models such as OpenAI Whisper. The platform performs preprocessing tasks including file validation and audio extraction from video using tools like FFmpeg to ensure efficient transcription. The system generates timestamped transcripts that can be edited, searched, and highlighted, improving content accessibility and usability.The platform also provides multiple export options, allowing users to download transcripts in formats such as PDF, Word, PowerPoint, TXT, and SRT. A user-friendly dashboard is included to manage transcription history, saved summaries, and exported files, enabling efficient data organization. Built using a modern tech stack with React.js for the frontend and Node.js with Express.js for the backend, the system ensures a seamless, responsive, and secure user experience. The platform reduces manual effort and improves productivity by automating transcription workflows while maintaining high accuracy. It transforms multimedia content processing into a structured and efficient task, making it useful for students, professionals, and content creators who require reliable transcription and documentation solutions.

KEYWORDS

Keywords: AI transcription audio to text video transcription YouTube transcription speech-to-text timestamped transcripts OpenAI Whisper FFmpeg processing transcript editing keyword search multi- format export PDF DOCX PPTX SRT transcription dashboard content accessibility automated transcription system.

Cite This Article

Abitha M, Kalaiyarasi R, "Transcripto," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, pp. 1-10, April 2026. https://doi.org/10.55041/IJSREM62019

Full Article/Conclusion

The future development of the Transcripto AI Audio & Video Transcription Platform can focus on enhancing transcription accuracy, speed, and overall user experience by integrating more advanced AI models and intelligent features. The system can be upgraded to support real-time transcription, enabling users to convert live audio streams such as meetings, lectures, and webinars into text instantly. Additionally, incorporating multilingual transcription and translation capabilities will allow users to process content in multiple languages, making the platform more inclusive and globally accessible.   Another important area of improvement is the integration of AI-based summarization and keyword extraction. By leveraging advanced Natural Language Processing techniques, the system can automatically generate concise summaries and identify important keywords from transcripts. This will help users quickly understand large volumes of content and improve productivity. Enhanced search capabilities, such as semantic search, can further improve content navigation and analysis.   The platform can also expand its analytics and personalization features by providing insights such as frequently accessed content, usage patterns, and smart recommendations. Adaptive features can suggest summaries, highlights, or edits based on user behavior, making the system more intelligent and user-centric.   Furthermore, Transcripto can be extended to include collaborative editing and sharing features, allowing multiple users to work on transcripts in real time. Integration with cloud storage platforms and development of mobile applications can improve accessibility and scalability, enabling users to access their data anytime and anywhere.   The system can also incorporate speaker diarization to identify and separate multiple speakers in conversations, improving transcript clarity for meetings and interviews. Enhanced export features with customizable formats and styling options can further increase usability.   By continuously evolving with advancements in AI and web technologies, Transcripto has the potential to become a comprehensive multimedia processing and content analysis platform, supporting a wide range of applications across education, business, research, and content creation domains.

References

1.     Radford, A. et al. (2023). Whisper: Robust Speech Recognition via Large-Scale Weak Supervision. OpenAI Research. Available: https://openai.com 2.     Jurafsky, D., & Martin, J. (2023). Speech and Language Processing (3rd Edition). Stanford University.                        Available: https://web.stanford.edu/~jurafsky/slp3 3.     Vaswani, A. et al. (2017). Attention is All You Need. Neural Information Processing Systems (NeurIPS), 30, 5998–6008. Available: https://arxiv.org/abs/1706.03762 4.     Bengio, Y., Goodfellow, I., & Courville, A. (2023). Deep Learning. MIT Press. Available: https://www.deeplearningbook.org 5.     Google Research. (2022). GigaSpeech: An Evolving Dataset for Speech Recognition. Available: https://arxiv.org/abs/2106.06909 6.     Microsoft. (2021). Real-Time Speech-to-Text Systems and Applications. Microsoft Research. Available: https://www.microsoft.com 7.     FFmpeg Developers. (2024). FFmpeg Multimedia Framework Documentation. Available: https://ffmpeg.org 8.     Node.js Foundation. (2024). Node.js Documentation. Available: https://nodejs.org 9.     Express.js. (2024). Express Web Framework Guide. Available: https://expressjs.com 10.  React Documentation. (2024). Building User Interfaces with React. Meta Developers. Available: https://react.dev 11.  MongoDB Inc. (2024). MongoDB Database Documentation.        Available: https://www.mongodb.com 12.  Mozilla. (2023). Web Audio API Documentation.  Available: https://developer.mozilla.org 13.  W3C. (2023). Web Security and Authentication Standards. World Wide Web Consortium. Available: https://www.w3.org

Editorial & Review Transparency

Publication Date

4/30/2026

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...