JOURNAL ARTICLE

Intelligent Text-to-Presentation System: An NLPDriven Web Application for Automated PowerPoint Generation with Multi-Format Document Processing and Secure Authentication.

  • Published In: Grenze International Journal of Engineering & Technology (GIJET), 2026, v. 12, n. Part2. P. 2726 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: M., Umarani; A. D., Chitra; V. S., Abinayashree; S., Ramalakshmi 3 of 3

Abstract

The increasing demand for efficient presentation creation in academic and professional environments has highlighted the need for intelligent automation tools. This paper presents a novel web-based application that automatically converts raw text and multiple document formats (DOCX, PDF, TXT, CSV) into structured PowerPoint presentations using advanced Natural Language Processing techniques. The system addresses the time-consuming manual effort in presentation creation by implementing automated text summarization, intelligent title generation, and dynamic slide structuring with optimized bullet point organization. Key innovations include seamless CSV-to-chart visualization, secure dual-factor authentication (email and mobile OTP), and scalable architecture supporting 20 concurrent users. Performance evaluation demonstrates a 85-90% reduction in presentation creation time while maintaining professional formatting consistency. The system processes up to 1500-word inputs and 10MB files within a 4GB capacity framework, producing downloadable presentations with standardized headers, footers, and reference integration. Results show high user satisfaction with improved presentation quality and significant time savings, establishing this as a comprehensive solution for automated academic and professional presentation generation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Grenze International Journal of Engineering & Technology (GIJET). 2026/01, Vol. 12, Issue Part2, p2726
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2026
  • ISSN:23955287
  • Accession Number:192272963
  • Copyright Statement:Copyright of Grenze International Journal of Engineering & Technology (GIJET) is the property of GRENZE Scientific Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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