Indian Sign Language Translator Using CNN
Authors/Creators
- 1. School of Computer Science and Engineering, REVA University, Bengaluru, Karnataka, India
Description
This paper main focus is to create a real-time Indian Sign Language (ISL) translator designed to overcome the gap between the deaf and hard-of-hearing population and the hearing population. By leveraging computer vision techniques and machine learning models, the system can accurately recognize a wide range of ISL gestures and translate them into corresponding text outputs in English. The application is intended to facilitate seamless communication, enhancing accessibility in various settings such as education, healthcare, and daily interactions. This solution aims to foster greater inclusion and social integration for ISL users while addressing the lack of real-time ISL translation tools in India.
Files
v4i4p21.pdf
Files
(333.5 kB)
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