A Survey on Sign Language Recognition

Authors

  • Abilash S Dept. Of Computer Science & Engineering, Jyothy Institute of Technology, Bangalore, India
  • Ashish Ashish Dept. Of Computer Science & Engineering, Jyothy Institute of Technology, Bangalore, India
  • Shreyas K S Dept. Of Computer Science & Engineering, Jyothy Institute of Technology, Bangalore, India
  • Shreyas S Nadig Dept. Of Computer Science & Engineering, Jyothy Institute of Technology, Bangalore, India
  • Vallabh Mahale Dept. Of Computer Science & Engineering, Jyothy Institute of Technology, Bangalore, India

DOI:

https://doi.org/10.5281/zenodo.4902967

Keywords:

Sign Language Recognition (SLR), Hand Gesture Recognition, Machine Learning (ML), Artificial Intelligence (AI), Real-Time Application

Abstract

The modern day applications are more user experience-oriented. Every application tends to gather information specific to each person’s operation and then provide customized features. The methods used to achieve such feats are a product of Machine Learning (ML) and Artificial Intelligence (AI) techniques. Using these techniques, real-time applications are reaching new heights in interacting with humans almost seamlessly. When living in such times, we can use these methods effectively to explore ways to overcome challenging problems. One such problem that we are taking upon is Sign Language Recognition (SLR). The project aims at bridging the communication gap with voice and hearing-impaired people, helping them to converse with the world more fluently. Using hand gestures as the primary input, we convert those into understandable language.

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Published

2021-06-04

How to Cite

[1]
A. S, A. Ashish, S. . K S, S. S. Nadig, and V. Mahale, “A Survey on Sign Language Recognition”, pices, vol. 5, no. 2, pp. 34-36, Jun. 2021.

Issue

Vol. 5 No. 2 (2021): Issue 2 - May 2021

Section

Articles

URN

http://nbn-resolving.de/urn:nbn:de:101:1-2021060509253432726327

License

Copyright (c) 2021 Perspectives in Communication, Embedded-systems and Signal-processing - PiCES

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.