Khushal Das1, Fazeel Abid2, Jawad Rasheed3,4,*, Kamlish5, Tunc Asuroglu6,*, Shtwai Alsubai7, Safeeullah Soomro8
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 689-711, 2024, DOI:10.32604/cmes.2024.051335
Abstract Deaf people or people facing hearing issues can communicate using sign language (SL), a visual language. Many works based on rich source language have been proposed; however, the work using poor resource language is still lacking. Unlike other SLs, the visuals of the Urdu Language are different. This study presents a novel approach to translating Urdu sign language (UrSL) using the UrSL-CNN model, a convolutional neural network (CNN) architecture specifically designed for this purpose. Unlike existing works that primarily focus on languages with rich resources, this study addresses the challenge of translating a sign language… More >
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