Sign Language Translator Using KNN

Authors

  •   Steve Correia Student, St. Francis Institute of Technology, Mount Poinsur, S.V.P. Road, Borivali (West), Mumbai - 400 103, Maharashtra
  •   Nathen Carneiro Student, St. Francis Institute of Technology, Mount Poinsur, S.V.P. Road, Borivali (West), Mumbai - 400 103, Maharashtra
  •   Royce Barboz Student, St. Francis Institute of Technology, Mount Poinsur, S.V.P. Road, Borivali (West), Mumbai - 400 103, Maharashtra
  •   Dheeraj Naik Student, St. Francis Institute of Technology, Mount Poinsur, S.V.P. Road, Borivali (West), Mumbai - 400 103, Maharashtra
  •   Grinal Tuscano Student, St. Francis Institute of Technology, Mount Poinsur, S.V.P. Road, Borivali (West), Mumbai - 400 103, Maharashtra

DOI:

https://doi.org/10.17010/ijcs/2024/v9/i3/174149

Keywords:

KNN

, Sign Language Translator.

Paper Submission Date

, April 18, 2024, Paper sent back for Revision, April 30, Paper Acceptance Date, May 5, Paper Published Online, June 5, 2024.

Abstract

Sign language is a profoundly rich and expressive way to communicate, and it is vital for the deaf and hard-of- hearing communities. It provides a distinct avenue for sharing thoughts, feelings, and ideas, helping these individuals to connect and share their viewpoints. Nevertheless, the digital divide remains a significant hurdle, limiting their ability to communicate effectively and integrate fully into a predominantly spoken and written linguistic environment. Our initiative serves as a ray of hope in a time when technology has the potential to close these gaps and promote inclusivity. We are committed to creating a sign language translator powered by Machine Learning. Our main objective is to deliver a real-time translation tool that overcomes these obstacles, facilitating seamless communication between the deaf community and the wider hearing population. By leveraging the power of modern technology, we strive to empower deaf and hard-of-hearing people, enabling them to fully participate in society, access information, and express themselves naturally and inclusively. Our project is a crucial step toward making the world more accessible and fair for everyone.

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Published

2024-06-05

How to Cite

Correia, S., Carneiro, N., Barboz, R., Naik, D., & Tuscano, G. (2024). Sign Language Translator Using KNN. Indian Journal of Computer Science, 9(3), 16–22. https://doi.org/10.17010/ijcs/2024/v9/i3/174149

Issue

Section

Articles

References

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