Sanaullah, M. and Ahmad, B. and Kashif, M. and Safdar, T. and Hassan, M. and Hasan, M.H. and Aziz, N. (2022) A real-time automatic translation of text to sign language. Computers, Materials and Continua, 70 (2). pp. 2471-2488. ISSN 15462218
Full text not available from this repository.Abstract
Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This paper presents an architecture for an application named Sign4PSL that translates the sentences to Pakistan Sign Language (PSL) for deaf people with visual representation using virtual signing character. This research aims to develop a generic independent application that is lightweight and reusable on any platform, including web and mobile, with an ability to perform offline text translation. The Sign4PSL relies on a knowledge base that stores both corpus of PSL Words and their coded form in the notation system. Sign4PSL takes English language text as an input, performs the translation to PSL through sign language notation and displays gestures to the user using virtual character. The system is tested on deaf students at a special school. The results have shown that the students were able to understand the story presented to them appropriately. © 2022 Tech Science Press. All rights reserved.
Item Type: | Article |
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Additional Information: | cited By 7 |
Uncontrolled Keywords: | Computer software reusability; Knowledge based systems; Markup languages; Translation (languages); Visual languages, Automatic translation; Deaf communication; Deaf peoples; Hamburg notation; Human being; Learn+; Pakistan; Real- time; Sign language; Sign markup language, Machine translation |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 19 Dec 2023 03:24 |
Last Modified: | 19 Dec 2023 03:24 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/17845 |