Examining the Quality of Machine Translation Subtitling for Saudi Series: Tash Ma Tash a Model

This study examines the quality of machine-translated subtitles for the Saudi comedy series Tash Ma Tash using YouTube-generated subtitles. The research focuses on assessing how well machine translation (MT) tools convey the meaning of the source text, with a particular emphasis on the challenges posed by idiomatic expressions, dialectal vocabulary, and humor in Arabic to English translation. A thematic analysis was conducted to examine the application of Pedersen's FAR model, focusing on its three main dimensions: Functional Equivalence (do the subtitles convey speaker meaning?); Acceptability (do the subtitles sound correct and natural in the target language?); and Readability (can the subtitles be read in a fluent and non-intrusive way?). Particular attention was paid to how machine translation (MT) systems handle culturally and linguistically complex content. The findings indicated that although machine translation is effective in translating straightforward terms, it frequently struggles to convey more profound cultural meanings and subtleties, resulting in considerable mistranslations. This research emphasizes the vital need to comprehend the cultural context during translation processes, as numerous idiomatic expressions and culturally specific references are often either lost or inaccurately represented in machine-generated subtitles. Additionally, the study highlights the importance of human involvement in the subtitling process to improve the accuracy and effectiveness of translations. The implications of this research go beyond the particular instance of Tash Ma Tash, suggesting that similar issues may occur in the translation of other culturally nuanced audiovisual materials and so this study contributes to the effectiveness of the machine translation.