Computational Linguistics and Translation Studies: Textual Corpora as a case study

Abstract

Translation into the second language has occupied the attention of researchers. While some scholars believe that only a native speaker should translate into his first language, another group believes that this ideal scenario may not be attainable. A contributing factor could be the lack of translation market to qualified translators who are also native speakers of the target language. However, the advancements in the field of technology in general, and in the field of translation studies in particular have enabled translators to carry out their work with a great deal of professionalism, even if the language into which they are translating is not their mother tongue. This applies to Arab translators, who usually translate many documents and texts into different world languages, including English. In addition, the advent of the third millennium witnessed an increasing use of computational linguistics applications in teaching foreign languages, and in translator training institutions. In line with the above discussion, the current study highlights the significance of using computational linguistics applications in the translation process, and the role such applications/tools can play in enhancing the quality of the translation product. It investigates the use of monolingual, comparative or multilingual corpora in Arabic-English translation and vice versa. It is an action research that was conducted on a group of trainee translators doing an advanced translation course during the academic year 2019-2020. The study adopted a project-based approach in which authentic translation tasks/projects were given to the trainees. The course was taught in a hybrid blended learning mode. While part of the training took place in a traditional classroom, the other part was implemented online. A cloud-based learning management system called Canvas was used for the delivery of the course.