Applied Machine Learning: Concepts, Algorithms, and Real-World Applications
Articles

Indian Sign Language Using Customized Gesture Recognition with Machine Learning

PDF
  • Jayanta Chowdhury
Jayanta Chowdhury
Swami Vivekananda University, Barrackpore, India

Published 2026-07-06

Keywords

  • Indian Sign Language (ISL),
  • Gesture Recognition,
  • Machine Learning,
  • Deep Learning,
  • Convolutional Neural Networks (CNN),
  • Image Processing,
  • Communication,
  • Accessibility,
  • Inclusivity
    • ...More
    Less

How to Cite

Chowdhury, Jayanta. “Indian Sign Language Using Customized Gesture Recognition With Machine Learning”. Swami Vivekananda University Press, July 2026, pp. 51-55, https://swamivivekanandauniversitypress.com/index.php/svup/article/view/652.

Copyright (c) 2026 Swami Vivekananda University Press

Creative Commons License

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

Abstract

The Indian Sign Language (ISL) is an essential medium of communication for people who are deaf or hard of hearing in India. However, the integration of ISL with modern technology has remained a challenge due to the diversity of gestures, regional variations, and the lack of standardized tools for real-time recognition. This paper proposes a system for recognizing Indian Sign Language gestures using customized machine learning models tailored to the ISL context. We employ deep learning techniques to design a gesture recognition system that can interpret ISL gestures through image and video processing. The system utilizes a convolutional neural network (CNN) model, trained on a diverse dataset of ISL signs, to achieve accurate and reliable recognition of hand gestures. This approach aims to bridge the communication gap between the hearing and deaf communities, enhancing accessibility and inclusivity in digital environments.

DOI - https://doi.org/10.65525/SVUP.9788199963351.2026.51-55

PDF