Deep Learning for Sign Language Recognition

Bhagyashri Pagar; Rutuja Shelar; Soumya Sheelavant; Avinash A. Utikar1

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Publication Date: 2023/03/18

Abstract: A sign language is a way of communicating by using the hands instead of spoken words. Sign language is used by deaf and dump people to communicate with other individuals. People who are speech-impaired and also some people who have autism spectrum disorder face problem while communicating with normal as they can converse using only sign language. So, it becomes difficult for other individuals to understand this sign language. Each country usually has its own native sign language. The Indian Sign Language recognition application proposed here aims at solving the communication problem between people. System will capture the different hand gestures through camera of mobile phone. The signs used in sign language are identified by the features extracted from the hand gestures. Then, processing of the image takes place by using convolution neural network algorithm. After all the processing we finally get the output as a text which can be easily understood by all people. We are keeping purpose of developing system that will make communication between Deaf and Dumb person and normal person easy and convenient.

Keywords: Sign Language Recognition Application, Convolution Neural Network, Deep Learning.

DOI: https://doi.org/10.5281/zenodo.7747476

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAR066.pdf

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