SignCom AI: A Real-Time Communication System for Indian Sign Language Using AI and NLP Techniques

Communication barriers between the deaf and hearing communities remain a significant challenge in today’s society. Our project aims to bridge this gap by developing a real-time Sign Language Translator App capable of converting Indian Sign Language (ISL) into both text and speech. The application uses the device's camera to capture hand gestures and leverages machine learning and computer vision techniques to recognize and interpret signs accurately. It supports translation into multiple Indian regional languages, making it accessible to a broader audience. Additionally, the app features a Learning Mode to teach ISL, and a Text-to-Sign avatar that displays user-input text in animated sign language. This comprehensive approach empowers the deaf community by facilitating inclusive communication, promoting ISL learning, and fostering societal awareness.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-05-20
DOI
https://doi.org/10.71097/ijsat.v16.i2.5180
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

SignCom AI: A Real-Time Communication System for Indian Sign Language Using AI and NLP Techniques

Venkata Satya Santhi S, G. Jemilda, A.Vinil Britus -, M. Williams Pearlson Jebus - et al.
International Journal on Science and Technology
Hand Gesture Recognition Systems
article

SignCom AI: A Real-Time Communication System for Indian Sign Language Using AI and NLP Techniques

Venkata Satya Santhi S, G. Jemilda, A.Vinil Britus -, M. Williams Pearlson Jebus -, Mohammed Muhsin Iliyas -
article en

Abstract

Communication barriers between the deaf and hearing communities remain a significant challenge in today’s society. Our project aims to bridge this gap by developing a real-time Sign Language Translator App capable of converting Indian Sign Language (ISL) into both text and speech. The application uses the device's camera to capture hand gestures and leverages machine learning and computer vision techniques to recognize and interpret signs accurately. It supports translation into multiple Indian regional languages, making it accessible to a broader audience. Additionally, the app features a Learning Mode to teach ISL, and a Text-to-Sign avatar that displays user-input text in animated sign language. This comprehensive approach empowers the deaf community by facilitating inclusive communication, promoting ISL learning, and fostering societal awareness.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 89%
Hand Gesture Recognition Systems
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