Aaisha Sulaiman Abdullah Al Abri & Dr. Hassan Obaid Alfadly
Department of Foreign Languages, College of Arts and Sciences, University of Nizwa, Sultanate of Oman
This experimental research investigates the potential benefits of employing a literary parallel corpus tool to enhance the translation capabilities of students at Nizwa University. Motivated by the need for innovative approaches in translation training, the study utilized a tool specifically designed with Google Cloud’s AutoML service and involved thirty translation students selected through random sampling. Participants first completed a pre-test employing conventional translation aids, followed by a post-test utilizing the custom-developed literary corpus tool. Output from both stages was evaluated and compared using House’s Translation Quality Assessment Model to determine changes in performance. The findings indicated an improvement in students’ translations when using the specialized corpus tool, as evidenced by reductions in mistranslations, grammatical inaccuracies, and stylistic issues. Moreover, qualitative assessments highlighted significant enhancements in translation fluency, adequacy, and naturalness. This study underscores the crucial role of developing specialized corpus tools to enrich translation training and education, offering promising implications for enhancing translator training methodologies in academia and professional translation practice.
Keywords: Translation Tools, Literary Corpus, Specialized Translation Resources, Translation Quality Evaluation, Educational Translation Resources
The above abstract is a part of the article which was accepted at The 10th International Conference on Languages, Linguistics, Translation and Literature (WWW.TLLL.IR), 1-2 February 2025, Ahwaz.
