Published May 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Sign Language to Text Conversion using CNN

  • 1. Department of Computer Science, St. Albert's College, Kochi (Kerala), India.

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  • 1. Department of Computer Science, St. Albert's College, Kochi (Kerala), India.

Description

Abstract: Sign language is a communication strategy used by those who are unable to hear. So those people who know sign language can communicate with people who are deaf. But a majority of our people don’t know sign language therefore there comes a communication gap between the ones who know sign language and others who don’t know. This project's major purpose is to bridge this gap by developing a systemthat recognizesmultiple sign languages and translates them into text in real-time. We use machine learning technologies to construct this system especially, convolutional neural networks (cnns), which are used to recognize and translate American Sign Language (ASL) into text by capturing it using a webcam. The transformed text is then presented on the screen by which individuals can comprehend and communicate with those who use sign language. The system's performance is evaluated on a dataset of ASL gestures, attaining excellent accuracy and indicating its potential for practical usage in enhancing communication accessibility for the deaf and hard-of-hearing community.

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Additional details

Identifiers

DOI
10.54105/ijdm.A1634.04010524
EISSN
2582-9246

Dates

Accepted
2024-05-15
Manuscript received on 16 April 2024 | Revised Manuscript received on 04 May 2024 | Manuscript Accepted on 15 May 2024 | Manuscript published on 30 May 2024.

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