scholarly journals Hand Gesture Alphabet Recognition for American Sign Language using Deep Learning

2021 ◽  
pp. 213-220
Author(s):  
Krutika S. Kale ◽  
Milind B. Waghmare
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Hand Gesture ◽  
American Sign ◽  
Speech Impairment ◽  
Feature Identification ◽  
Design And Implementation ◽  
Detection Tool ◽  
Hand Gesture Detection ◽  
Communication Methods

Speech impairment limits a person's capacity to speak and communicate with others, forcing them to adopt other communication methods such as sign language. Sign language is not that widely used technique by the deaf. To solve this problem, we developed a powerful hand gesture detection tool that can easily monitor both dynamic and static hand motions with ease. Gesture recognition aims to translate sign language into voice or text for individuals who have a rudimentary comprehension of that, which will be a tremendous help in communication between deaf-mute and hearing people. We describe the design and implementation of an American Sign Language (ASL) fingerspelling translator based on spatial feature identification using a convolutional neural network.

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