Evaluating Google Machine Translation in Translating Arabic News Articles Headlines into English

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 (۹۵%) and accuracy (۹۳.۷%) but scored lower in style (۹۰.۶%). 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.

کلیدواژه ها:

Machine Translation ، Google Translate ، Arabic-English Translation ، News Headlines ، Linguistic Style