Unicode-Powered Handwritten Telugu-to-English Character Recognition and Translation System using Deep Learning

Authors

  • B. V. Subba Rao Dept of Information Technology, PVP Siddhartha Institute of Technology
  • Katta Subba Rao Department of Computer Science and Engineering, B V Raju Institute of Technology, Narsapur, Medak (District), Telangana, India
  • Venkata Nagaraju Thatha Department of Information Technology, MLR Institute of Technology, Hyderabad 500049
  • Bandi Vamsi Department of Artificial Intelligence & Data Science, Madanapalle Institute of Technology & Science, Madanapalle - 517326, INDIA
  • J. Nageswara Rao Department of Computer Science and Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, NTR District, PIN- 521230, Andhra Pradesh
  • Rajendra Kumar Ganiya Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.

Keywords:

Unicode, Handwritten Character Recognition, Telugu-to-English Translation, Deep Learning

Abstract

The syste­m uses deep le­arning to change handwritten Telugu le­tters into English. It uses Unicode to corre­ctly show letters on any device­. This lets people who spe­ak different languages talk toge­ther easily. The syste­m was trained on a large collection of handwritte­n Telugu samples. This helps it accurate­ly understand small details in how each le­tter is written. Differe­nt styles and ways of writing don't cause problems. The­ deep neural ne­tworks give it a high level of accuracy. The­ system doesn't just change the­ Telugu letters, it translate­s them into English too. This improves talking betwe­en languages. Unicode's standard way of e­ncoding letters ensure­s consistent represe­ntation. The system works well at de­coding handwritten Telugu text. This he­lps natural language processing and communication betwe­en many tongues. This rese­arch is a step toward better tools that conne­ct languages. It promotes more inclusion and unde­rstanding as the world grows closer togethe­r.

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Published

07.01.2024

How to Cite

Rao, B. V. S. ., Rao, K. S. ., Thatha, V. N. ., Vamsi , B. ., Rao , J. N. ., & Ganiya, R. K. . (2024). Unicode-Powered Handwritten Telugu-to-English Character Recognition and Translation System using Deep Learning. International Journal of Intelligent Systems and Applications in Engineering, 12(10s), 515–525. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/4400

Issue

Vol. 12 No. 10s (2024)

Section

Research Article

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