Character-Level Bidirectional Sign Language Translation Using Machine Learning Algorithms
摘要
Sign language is an indispensable mode of communication for the hard of hearing and deaf population. However, there is still a substantial language barrier between users of sign language and those who do not use it. This paper presents a bidirectional character-level sign language translation system that uses various machine learning algorithms, including Support Vector Machines (SVM), Random Forest, Logistic Regression (LR), and K-Nearest Neighbors (KNN), as well as deep learning algorithm—Convolutional Neural Networks (CNN), to provide a solution to this communication issue.