Abstract
This study is proposed to review the sign language recognition system based on different classifier techniques. Mostly the Neural Network and Deep Learning-based classifiers were utilized to recognize the different sign languages and this survey is proposed to review the best classifier model to represent sign language recognition (SLR). We focused mainly on deep learning techniques and also on Arabic sign language recognition systems. Numerous classifiers like CNN, RNN, MLP, LDA, HMM, ANN, SVM, KNN and more were implemented to the SLR system. Each classifier is reviewed with the recognition accuracy, in which the deep learning-based classifiers executed the optimal recognition result as contrasted to the other types of classifiers.