Machine Learning Framework for Intelligent Hand Gesture Recognition: An Application to Indian Sign Language and Hand Talk

DOI

10.2991/978-94-6463-716-8_39How to use a DOI?

Keywords

Indian sign language; Dataset; Media pipe; Classification; Neural Network; KNN; SVM; Random Forest

Abstract

Communicating with individuals with hearing disabilities poses significant challenges. The research presented in this paper represents an effort to further explore the complexities associated with character classification in Indian Sign Language (ISL). It’s important to note that sign language alone may not suffice for effective communication, especially for individuals with hearing or speech impairments. The gestures made by individuals with disabilities can appear jumbled or confusing to those who are unfamiliar with the language. Sign language recognition has long been recognized as a crucial tool to aid individuals with hearing impairments. Over the years, researchers have dedicated significant efforts to advancing this field of study. Recently, there has been a growing focus on developing solutions that can be universally applied in India, where the need for such technology is particularly pronounced. The primary objective of this paper is to develop an accurate and reliable sign language recognition system. By critically evaluating different methodologies, the aim is to identify the most effective method for accurately recognizing and interpreting sign language gestures, ultimately contributing to the advancement of assistive technologies for the deaf community.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shashi Malviya
AU  - Anita Mahajan
AU  - Kamal Kumar Sethi
PY  - 2025
DA  - 2025/05/26
TI  - Machine Learning Framework for Intelligent Hand Gesture Recognition: An Application to Indian Sign Language and Hand Talk
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 496
EP  - 512
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_39
DO  - 10.2991/978-94-6463-716-8_39
ID  - Malviya2025
ER  -