Aditya Kumawat,
Chitranshi Agarwal,
Akshita Jain,
Chirag Jain,
Tanisha Jain,
- Student, Department of Artificial Intelligence and Data Science (AIDS), JECRC Foundation (Jaipur Engineering College and Research Centre), Rajasthan, India
- Student, Department of Artificial Intelligence and Data Science (AIDS), JECRC Foundation (Jaipur Engineering College and Research Centre), Rajasthan, India
- Student, Department of Artificial Intelligence and Data Science (AIDS), JECRC Foundation (Jaipur Engineering College and Research Centre), Rajasthan, India
- Student, Department of Artificial Intelligence and Data Science (AIDS), JECRC Foundation (Jaipur Engineering College and Research Centre), Rajasthan, India
- Student, Department of Artificial Intelligence and Data Science (AIDS), JECRC Foundation (Jaipur Engineering College and Research Centre), Rajasthan, India
Abstract
Indian sign language (ISL) is the primary form of communication for a large number of deaf and hard-of-hearing people within the Indian subcontinent. However, their interactions with non-signers remain limited, mainly due to the absence of tools that could translate sign language in real time. The present study aims to develop an ISL translation system powered by AI that can automatically convert sign gestures into readable text or spoken output. The proposed system will analyze video input with the help of computer vision and deep learning techniques, estimate hand motion along with facial cues, and finally recognize ISL gestures with a high accuracy level. It deals with three major aspects: increasing recognition performance across users and environments, removing delays so as to enable real-time communication, and designing an easy-to-operate interface that could be used inside classrooms, hospitals, workplaces, and public service centers. The system is envisioned to bridge the communication gap between signed and spoken/written languages as a means to support inclusive communication and advance the accessibility of the Indian deaf community in various digital and physical spaces.
Keywords: Indian sign language, deep learning, computer vision, gesture recognition, real-time translation, accessibility
[This article belongs to Journal of Image Processing & Pattern Recognition Progress ]
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Journal of Image Processing & Pattern Recognition Progress
| Volume | 13 | |
| Issue | 02 | |
| Received | 03/02/2026 | |
| Accepted | 20/02/2026 | |
| Published | 10/03/2026 | |
| Publication Time | 35 Days |