YouTube’s Automated Subtitling from English into Arabic: A Case Study of Harry Potter and the Prisoner of Azkaban

Recently, the development of speech-to-text technology, together with machine translation, has led to the developmentof simultaneously translating the captions of videos into other languages. YouTube, a video-sharing platform, offersmultilingual subtitles using this feature. The current automated caption system captures audio data during video uploadsand generates a subtitle file in text format. The current study aims at examining whether YouTube machine translation fromEnglish into Arabic is reliable in rendering the intended meaning on subtitling, depending on the FAR model (functionalequivalence, readability, and acceptability). The data of this study consisted of 30 examples that were taken from theYouTube platform and their translated versions into Arabic using YouTube’s machine translation. The study is bothdescriptive and comparative. The results of the study indicate that YouTube machine translation represents varying levelsof inadequate translation according to its system and database, revealing many deficiencies. The total approval rate is68.5%, which gives the impression that the translation is very poor. Therefore, the machine requires the development of itssystem and the enrichment of its databases, specifically the Arabic ones.