ASL Mobile Translator with CNN Algorithm

Year : 2023 | Volume : 01 | Issue : 02 | Page : 31-38
By

    Sasikumar M.

  1. Lekha Achuth

  1. Student, Department of Computer Applications, People’s Education Society University, Bengaluru, Karnataka, India
  2. Associate Professor, Department of Computer Applications, People’s Education Society University, Bengaluru, Karnataka, India

Abstract

There are around 63 million people in India with speech and hearing disabilities, and the number goes all the way up to 300 million across the world. All of them face issues in their day-to-day life as they can only have conversations with gestures. American Sign Language (ASL) mobile translator with convolutional neural network (CNN) algorithm is an easy-to-use mobile application, which uses complex images and video recognizing models built with an open-source tool called OpenCV. It efficiently recognizes gestures being shown to the camera and translates it to voice message, which can be understood by a normal person. Being a mobile application, it is portable and can be carried anywhere.

Keywords: American Sign Language, convolutional neural networks, image classification, machine learning, object detection

[This article belongs to International Journal of Algorithms Design and Analysis Review(ijadar)]

How to cite this article: Sasikumar M., Lekha Achuth ASL Mobile Translator with CNN Algorithm ijadar 2023; 01:31-38
How to cite this URL: Sasikumar M., Lekha Achuth ASL Mobile Translator with CNN Algorithm ijadar 2023 {cited 2023 Nov 23};01:31-38. Available from: https://journals.stmjournals.com/ijadar/article=2023/view=129066

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Regular Issue Subscription Review Article
Volume 01
Issue 02
Received October 27, 2023
Accepted November 2, 2023
Published November 23, 2023