Machine Translation In Scientific Texts: Balancing Accuracy And Content
Auteurs : Melhem Buraq . Shlool Rola .
Résumé
This study analyzes the role of machine translation within the field of scientific texts, that is, with regard to issues of terminological accuracy and contextual appropriately. With computerized translation software increasingly utilized in scholarship and research environments, there are concerns regarding such software's ability to offer accurate, reasonable, and contextually appropriate translations—especially where terminology transfers conceptual relevance. Scientific texts are not merely linguistic constructs but are also embedded in theoretical and methodological contexts that require more than literal translation; they require nuanced sensitivity to both language and discipline knowledge. The research seeks to evaluate the performance of widely used machine translation tools such as Google Translate and DeepL in scientific text translation in many fields such as biomedical sciences, physics, and artificial intelligence. It considers how these systems handle technical vocabulary, subtle syntactic organization, and situational meaning that is constitutive of the integrity of scientific discourse.
Mots clés
1: Machine translation, 2 ; Scientific texts, 3 ; Context, accuracy, 4: Scientific terminology, 5: Google Translate.
