TY  - EJOU
AU  - Kolhar, Manjur 
AU  - Alameen, Abdalla 

TI  - Artificial Intelligence Based Language Translation Platform
T2  - Intelligent Automation \& Soft Computing

PY  - 2021
VL  - 28
IS  - 1
SN  - 2326-005X

AB  - 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 bandwidths) made available for interactive translation services. The framework is deployed by linking it to a video camera, digital podium, and projector in each classroom for the translation operation. Accordingly. After employing the system, the effect on the understanding of the students of the technical aspects of the subject that was taught using English was evaluated. The results indicated that the use of the developed technology for translation during classroom sessions was beneficial. Furthermore, the engagement of students in the classes improved their performance and learning outcomes. The students also commented that the proposed framework is useful from two perspectives: vocabulary improvement and subject comprehension. Many of the students indicated that working on assignments and homework using the framework was useful because words difficult to understand were translated.
KW  - Network; information science; machine learning; multimedia; server; client; language translation; application programming

DO  - 10.32604/iasc.2021.014995