IoT Based Sign Language Recognition System

Authors

  • Raveen Wijayawickrama

  • Ravini Premachandra

  • Thilan Punsara

  • Achintha Chanaka

Keywords:

sign language, internet of things, gesture recognition, smart glove, recurrent neural network

Abstract

Sign language is the key communication medium which deaf and mute people use in their day-to-day life Talking to disabled people will cause a difficult situation since a non- mute person cannot understand their hand gestures and in many instances mute people are hearing impaired Same as Sinhala Tamil English or any other language sign language also tend to have differences according to the region This paper is an attempt to assist deaf and mute people to develop an effective communication mechanism with non-mute people The end product of this project is a combination of a mobile application that can translate the sign language into digital voice and IoT enabled light-weighted wearable glove which capable of recognizing twenty-six English alphabet 0-9 numbers and words Better user experience provide with voice-to-text feature in mobile application to reduce the communication gap within mute and non-mute communities Research findings and results from current system visualize the output of the product can be optimized up to 25 -35 with enhanced pattern recognition mechanism

How to Cite

Raveen Wijayawickrama, Ravini Premachandra, Thilan Punsara, & Achintha Chanaka. (2020). IoT Based Sign Language Recognition System. Global Journal of Computer Science and Technology, 20, 39–44. Retrieved from https://computerresearch.org/index.php/computer/article/view/2005

IoT Based Sign Language Recognition System

Published

2020-01-15