Systematic Literature Review: American Sign Language Translator

Abstract

Abstract Sign Language Recognition (SLR) is a relatively popular research area yet contrary to its popularity, the implementation of SLR in daily basis is rare; this is due to the complexity and various resources required. In this literature review, the authors have analyzed various techniques that can be used to implement an automated sign-language translator through the analysis of the methodologies and models used to make a working model of any sign-language translator from various sources. The purpose of this study is to explore various possible ways to implement Artificial Intelligence technology to improve the automated American Sign Language translator that is applicable. The authors have identified 22 different research papers within the period of the years 2015 - 2020. The analysis showed that every research studies picked have achieved respectable results, however, they are not perfect, since each research demonstrates its own unique strengths and weaknesses. There are some methods that might be suitable for our need to create an applicable Sign Language Translator, that is by using standard video camera for obtaining data, and either Convolutional Neural Network or Support Vector Machine can be used for the classification.