Manuscript Number : IJSRSET218521
Hand Gesture Alphabet Recognition for American Sign Language using Deep Learning
Authors(2) :-Krutika S. Kale, Milind B. Waghmare
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.
Krutika S. Kale
Sign Language Recognition, Deep learning, image processing, American sign Language, Hand gesture detection
Publication Details
Published in :
Volume 8 | Issue 5 | September-October 2021 Article Preview
Department of Computer Science and Engineering, Government College of Engineering Amravati, India
Milind B. Waghmare
Department of Computer Science and Engineering, Government College of Engineering Amravati, India
Date of Publication :
2021-10-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) :
213-220
Manuscript Number :
IJSRSET218521
Publisher : Technoscience Academy
Journal URL :
https://ijsrset.com/IJSRSET218521