چکیده مقاله
This study evaluates the performance of Google Translate GT in translating Arabic news headlines into English, focusing on clarity, accuracy, and stylistic quality Headlines were collected from reputable news agencies, including Al Jazeera, BBC, Oman Daily Observer, Al Watan, and Al Arabiya Ten headlines were translated using GT and compared with human translations, which were then evaluated by eight professional translators through a structured grid based survey Results indicate that GT performed well in clarity 95% and accuracy 93 7% but scored lower in style 90 6% While GT demonstrates remarkable progress in machine translation, the findings highlight its limitations in maintaining stylistic nuances in complex linguistic contexts such as media translation This underscores the importance of human oversight and the potential for hybrid approaches combining machine and human translation for optimal results
کلیدواژهها
نویسندگان
Rawan Khalfan Al Nadabi
Department of Foreign Languages, College of Arts and Sciences, University of Nizwa, Sultanate of Oman
Hassan Obaid Alfadly
Department of Foreign Languages, College of Arts and Sciences, University of Nizwa, Sultanate of Oman
شیوه ارجاع
Khalfan Al Nadabi, Rawan and Obaid Alfadly, Hassan,1403,Evaluating Google Machine Translation in Translating Arabic News Articles Headlines into English,The 10th International Conference on Languages, Linguistics, Translation and Literature,Ahvaz
ارائهشده در
مجموعه مقالات دهمین کنفرانس بین المللی بررسی مسائل جاری زبان ها، زبان شناسی، ترجمه و ادبیات13 بهمن 1403 · اهواز