Tech-driven advances in audiovisual translation: developing a cloud-based English-Arabic subtitle corpus for training and practice

Ahmad Haider; Mohammed M.  Obeidat; Yousef Hamdan; Omair AlZghoul; Hussein Abu-Rayyash

doi:10.1590/1983-3652.2026.60447

Authors

Ahmad Haider Applied Science Private University, Department of English Language and Translation, Amman, Jordan https://orcid.org/0000-0002-7763-201X
Mohammed M. Obeidat Yarmouk University, Translation Department, Irbid, Jordan https://orcid.org/0000-0002-1235-0492
Yousef Hamdan Applied Science Private University, Department of English Language and Translation, Amman, Jordan https://orcid.org/0000-0002-1937-8738
Omair AlZghoul Applied Science Private University, Department of English Language and Translation, Amman, Jordan https://orcid.org/0000-0003-4430-4244
Hussein Abu-Rayyash Kent State University, College of Arts and Sciences, Department of Modern and Classical Language Studies, Kent, Ohio, USA https://orcid.org/0000-0002-9695-4030

DOI:

https://doi.org/10.1590/1983-3652.2026.60447

Keywords:

Computer-assisted translation, SDL Trados, Audiovisual translation, Cloud, Translation memory

Abstract

This study introduces a new SDL Trados-based cloud of English-Arabic subtitles. The compiled corpus consists of subtitle files extracted from Netflix, featuring high-rated and award-winning English-language films, and aims to provide a comprehensive bilingual resource for subtitlers and translation educators. The study investigates the effect of using this cloud-based corpus on the productivity and accuracy of translators and subtitlers. A comparative analysis was conducted between translators who used the compiled corpus within SDL Trados and those who relied solely on traditional translation methods. Results indicate that users of the corpus demonstrated significantly faster translation times, higher terminological consistency, and improved overall quality. Furthermore, translation students and professional translators who participated in training sessions reported that the interface was user-friendly and the corpus highly beneficial for handling genre-specific terminology. Data analysis also showed that over 60\% of the terms present in final translations matched entries from the compiled corpus. The study concludes that the cloud corpus can serve as a valuable educational and professional tool in audiovisual translation training programs.

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