Sign Language Recognition using Machine Learning: A Survey


Authors : Anagha.G; Sinchana.S.Bharadwaj; Sumana.M.R; Varshini.Krishna.Mohan; Nagaraj.A

Volume/Issue : Volume 7 - 2022, Issue 4 - April

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3wGdW7H

DOI : https://doi.org/10.5281/zenodo.6568413

It is said that more than one billion people in the world are disabled. One of the only ways they can communicate among themselves or with people who don’t have this disability is sign language. Sign language is a creative way to communicate within the deaf community by using gestures done by hand and other means that do not require talking. It involves combining hand movements, their shapes, etc. Body movements and facial expressions are also taken into consideration. All these factors help convey the person’s thoughts in a fluent manner. Most of the general public who aren’t disabled have no knowledge about sign language. Even out of the few who are aware, the majority don’t know how to use it for communication, this stops them from interacting with the deaf and mute people. Through this software, we want to raise awareness towards sign language and help bridge the gap by creating a sign language interpreter that recognizes hand gestures

Keywords : Sign Language Recognition, Mobile Application, Convolutional Neural Network, Machine Learning.

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Paper Submission Last Date
31 - July - 2022

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