This paper presents an AI-based Sign Language Translator developed to reduce the communication gap between hearing-impaired individuals and non-sign language users. The system utilizes computer vision and machine learning techniques to recognize hand gestures and convert them into meaningful text or speech output in real time. The proposed model aims to improve accessibility, inclusivity, and ease of communication in daily interactions. The solution demonstrates the potential of artificial intelligence in assistive technologies and highlights its practical applications in social and educational environments.
Khandelwal et al. (2026) studied this question.