A research team from the Generative Artificial Intelligence and Natural Language Processing track at the AI Center, College of Computer and Information Sciences, in collaboration with faculty members from the College of Languages at Princess Nourah bint Abdulrahman University, has published a paper titled:
“Designing AI-Supported Translation Teaching Tools: A Framework for Generating Parallel Sentences Using SauLTC and Large Language Models (LLMs)” in the peer-reviewed journal PeerJ Computer Science.
The paper aims to design a framework for developing AI-supported educational tools in the field of translation by generating parallel sentences between English and Arabic. The research leverages the Saudi Learner Translation Corpus (SauLTC) along with large language models (LLMs) to process linguistic data and generate content that contributes to building educational and experimental resources.
The study presents methods for data preparation and processing and proposes a technical framework that combines local linguistic resources with advanced AI techniques. Using this framework, the team generated 15,854 English–Arabic sentence pairs, achieving a similarity score of 85.2% and a human-evaluated quality score of 85%, paving the way for the development of reliable research tools that support applied studies in translation education.
This achievement reflects the AI center’s efforts to promote interdisciplinary research, foster collaboration between computer sciences and linguistic studies, and support applied research that employs AI in education. It also contributes to the strategic plan of Princess Nourah bint Abdulrahman University, which seeks to enhance the research, innovation, and entrepreneurship ecosystem by establishing frameworks and policies that support innovative activities, incubate business accelerators, and nurture creative ideas.
To access the paper, follow this link:
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