Khushal Das¹, Fazeel Abid², Jawad Rasheed^3,4,*, Kamlish⁵, Tunc Asuroglu^6,*, Shtwai Alsubai⁷, Safeeullah Soomro⁸

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 689-711, 2024, DOI:10.32604/cmes.2024.051335 - 20 August 2024

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 >

Seema Sabharwal^1,2,*, Priti Singla¹

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2567-2582, 2023, DOI:10.32604/iasc.2023.035497 - 11 September 2023

Abstract Sign language is used as a communication medium in the field of trade, defence, and in deaf-mute communities worldwide. Over the last few decades, research in the domain of translation of sign language has grown and become more challenging. This necessitates the development of a Sign Language Translation System (SLTS) to provide effective communication in different research domains. In this paper, novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm (Hybrid-AO) for image segmentation is proposed for the translation of alphabet-level Indian Sign Language (ISLTS) with a 5-layer Convolution Neural Network (CNN). The focus of this… More >

Manjur Kolhar^*, Abdalla Alameen

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 1-9, 2021, DOI:10.32604/iasc.2021.014995 - 17 March 2021

Abstract The use of computer-based technologies by non-native Arabic-speaking teachers for teaching native Arabic-speaking students can result in higher learner engagement. In this study, a machine translation (MT) system is developed as a learning technology. The proposed system can be linked to a digital podium and projector to reduce multitasking. A total of 25 students from Prince Sattam Bin Abdulaziz University, Saudi Arabia participated in our experiment and survey related to the use of the proposed technology-enhanced MT system. An important reason for using this framework is to exploit the high service bandwidth (up to several… More >

Yunpeng Chang¹, Xiaoliang Wang^1,*, Meihua Xue¹, Yuzhen Liu¹, Frank Jiang²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3921-3931, 2021, DOI:10.32604/cmc.2021.012304 - 01 March 2021

Abstract Translation software has become an important tool for communication between different languages. People’s requirements for translation are higher and higher, mainly reflected in people’s desire for barrier free cultural exchange. With a large corpus, the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units. Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation, ignoring context. To support the ongoing improvement of translation methods built upon deep learning, we propose a translation algorithm… More >