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A Real-Time Automatic Translation of Text to Sign Language

Muhammad Sanaullah1,*, Babar Ahmad2, Muhammad Kashif2, Tauqeer Safdar2, Mehdi Hassan3, Mohd Hilmi Hasan4, Norshakirah Aziz4

1 Department of Computer Science, Bahauddin Zakariya University, Multan, 60,000, Pakistan
2 Department of Computer Science, Air University, Multan, 60,000, Pakistan
3 Department of Computer Science, Air University, Islamabad, 44,000, Pakistan
4 Centre for Research in Data Science, Department of Computer and Information Sciences, UniversitiTeknologi PETRONAS, Seri Iskandar, 32610, Perak, Malaysia

* Corresponding Author: Muhammad Sanaullah. Email: email

(This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)

Computers, Materials & Continua 2022, 70(2), 2471-2488. https://doi.org/10.32604/cmc.2022.019420

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.

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Cite This Article

APA Style
Sanaullah, M., Ahmad, B., Kashif, M., Safdar, T., Hassan, M. et al. (2022). A real-time automatic translation of text to sign language. Computers, Materials & Continua, 70(2), 2471-2488. https://doi.org/10.32604/cmc.2022.019420
Vancouver Style
Sanaullah M, Ahmad B, Kashif M, Safdar T, Hassan M, Hasan MH, et al. A real-time automatic translation of text to sign language. Comput Mater Contin. 2022;70(2):2471-2488 https://doi.org/10.32604/cmc.2022.019420
IEEE Style
M. Sanaullah et al., "A Real-Time Automatic Translation of Text to Sign Language," Comput. Mater. Contin., vol. 70, no. 2, pp. 2471-2488. 2022. https://doi.org/10.32604/cmc.2022.019420



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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