Sign Language to Text Conversion in Real Time using Transfer Learning

• URL: http://arxiv.org/abs/2211.14446v1
• Date: Sun, 13 Nov 2022 17:20:19 GMT
• Title: Sign Language to Text Conversion in Real Time using Transfer Learning
• Authors: Shubham Thakar, Samveg Shah, Bhavya Shah, Anant V. Nimkar
• Abstract summary: We propose a deep learning model trained on the American Sign Language. There has been an improvement in accuracy from 94% of CNN to 98.7% by Transfer Learning.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The people in the world who are hearing impaired face many obstacles in communication and require an interpreter to comprehend what a person is saying. There has been constant scientific research and the existing models lack the ability to make accurate predictions. So we propose a deep learning model trained on the ASL i.e. American Sign Language which will take action in the form of American Sign Language as input and translate it into text. To achieve the former a Convolution Neural Network based VGG16 architecture is used as well as a TensorFlow model for image classification and we have improved the accuracy of the latter by over 4%. There has been an improvement in accuracy from 94% of CNN to 98.7% by Transfer Learning. An application with the deep learning model integrated has also been built.

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