Real Time Sign Language Translator Using Machine Learning

https://doi.org/10.55529/jaimlnn.44.22.30

Authors

  • Ms. Pradnya Repal Department of Computer Science and Engineering, SVERI’S College of Engineering, Pandharpur, P.A.H. Solapur University, India

Keywords:

Department of Computer Science and Engineering, SVERI’S College of Engineering, Pandharpur, P.A.H. Solapur University, India.

Abstract

In today's interconnected world, effective communication is fundamental. For the deaf and mute community, communicating with those who don't understand sign language is challenging. To bridge this gap, we propose a web app translating sign language into spoken or written language and vice versa. Users capture gestures with a camera, and our system, powered by Tensor Flow and advanced image processing, converts them into coherent text. Supporting various sign languages and spoken languages, it enables real-time two-way communication. This innovative solution fosters inclusivity by empowering meaningful interactions between the deaf and mute community and the general population, promoting understanding and integration.

Published

2024-06-05

How to Cite

Ms. Pradnya Repal. (2024). Real Time Sign Language Translator Using Machine Learning. Journal of Artificial Intelligence,Machine Learning and Neural Network , 4(04), 22–30. https://doi.org/10.55529/jaimlnn.44.22.30

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