Abstract :

With The Rapid Advancement Of Artificial Intelligence And Natural Language Processing (NLP), Automated Content Generation Has Become Increasingly Popular Across Various Applications Such As Education, Entertainment, And Accessibility. This Project Presents A Multilingual Story Generation And Speech System That Enables Users To Generate Meaningful Stories From Simple Keyword Inputs And Convert Them Into Speech In Multiple Languages. The System Supports Languages Such As English, Telugu, And Hindi, Making It Accessible To A Diverse Range Of Users. The Proposed System Utilizes Transformer-based AI Models Combined With NLP Techniques To Process User-provided Keywords. Initially, The Input Keywords Are Cleaned And Structured Using NLP Preprocessing Methods Such As Tokenization And Normalization. The Refined Input Is Then Passed To A Transformer-based Language Model, Which Generates A Coherent And Contextually Relevant Story. Additionally, A Text-to-speech (TTS) Module Is Integrated To Convert The Generated Text Into Audio Output In The Selected Language, Enhancing User Interaction And Accessibility. The System Includes Modules For User Authentication, Story Generation, NLP Processing, And Speech Synthesis. Experimental Results Demonstrate That The System Generates Meaningful And Grammatically Correct Stories In Multiple Languages With High Efficiency. The Speech Output Is Clear And Understandable, Providing An Engaging User Experience. However, Challenges Such As Maintaining Contextual Consistency And Handling Complex Inputs Remain. Overall, This Project Highlights The Potential Of AI And NLP In Multilingual Content Generation And Speech Synthesis Applications.

Published:

08-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

1892-1898

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite