Edge AI for Real-Time Sign Language Translator

  • Ravikumar Chawhan Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering & Technology
  • Shivaraj Yaliwal Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering & Technology
  • Akash P Chandai Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering & Technology
  • Iranna Jakkali Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering & Technology
  • Puneeth Akki Department of Information Science and Engineering Smt. Kamala and Sri. Venkappa M. Agadi College of Engineering & Technology
Keywords: Convolutional Neural Networks (CNN), MediaPipe Hand Landmarks, Real-Time Translation, Computer Vision, Sign Language Recognition, Edge Computing, and Assistive Technology.

Abstract

Communicating with individuals who are deaf can often be difficult. This research aims to create a system that translates sign language into text and speech in real time. Using a camera, the system captures hand movements and converts them into written or spoken language. It relies on computer vision and a specialized computational model to analyze the hand gestures, interpret their meaning, and translate them accurately.

All processing occurs directly on the device, ensuring fast performance and protecting user privacy, since data does not need to be sent to external servers. In tests, the system was able to correctly recognize about 90% of gestures, even under poor lighting or noisy conditions. This sign language translation system provides an effective tool to help people who are deaf communicate more easily with others.

References

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Published
2026-04-19
How to Cite
Chawhan, R., Yaliwal, S., Chandai, A., Jakkali, I., & Akki, P. (2026). Edge AI for Real-Time Sign Language Translator. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 12(1), 151-153. Retrieved from https://asianssr.org/index.php/ajct/article/view/1536

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