Sign Language Recognition (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Sign Language is mainly used by deaf (hard hearing) and dumbpeople to exchangeinformation between their own community and with other people. It is a language wherepeople use theirhand gestures to communicate as they can’t speak or hear. Sign LanguageRecognition (SLR) deals with recognizing the hand gestures acquisition and continues tilltext or speech is generated for corresponding hand gestures. Here hand gestures for signlanguage can be classified as static and dynamic.However, static hand gesture recognition issimpler than dynamic hand gesture recognition, but both recognition is important to thehuman community.We can use Deep Learning Computer Vision to recognize the handgestures by building Deep Neural Network architectures (Convolution Neural NetworkArchitectures) where the model will learn to recognize the hand gestures images over anepoch.Once the model Successfully recognizes the gesture the corresponding English text isgenerated and then text can be converted to speech.This model will be more efficient andhence communicate for the deaf (hard hearing) and dump people will beeasier. In this paper,we will discuss how Sign Language Recognition is done using Deep Learning