Development of Sign Language Translator based on Gesture-to-Word Conversion

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 1, Issue 6, pp. 63-69, December 2025.

https://doi.org/10.58482/ijersem.v1i6.8

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

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Development of Sign Language Translator based on Gesture-to-Word by using IoT

V Gopi

CH. Vedhasree

K. Vishnu Vardhan Reddy

K. Rohitha Sai

S. Nishitha

S. Eswer Reddy

Department of CSE, Siddartha Institute of Science and Technology, Puttur, India.

Abstract: Sign language is the primary mode of communication for individuals with hearing and speech impairments; however, the lack of sign language knowledge among the general population creates a significant communication barrier. Recent advancements in computer vision and deep learning have enabled the development of automated sign language recognition and translation systems. Despite this progress, many existing solutions depend on wearable devices, are computationally expensive, or lack real-time gesture-to-word and speech translation capabilities suitable for practical deployment. This paper presents the development of a sign language translator that maps gestures to words using a vision-based approach. The proposed system captures hand gestures through a camera, recognises sign language gestures using deep learning techniques, and converts them into meaningful text and speech output. The system is designed to be cost-effective, real-time, and user-friendly, eliminating the need for sensor-based gloves. By focusing on gesture-based translation, the proposed approach aims to enhance accessibility and enable effective communication between hearing-impaired individuals and non-signers in real-world environments.

Keywords: Sign Language Translation, Gesture Recognition, Computer Vision, Deep Learning, Assistive Technology, Human-Computer Interaction.

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This article is part of Volume 1, Issue 6 (December 2025)