The aim of the research is to assess the quality of machine translation result in translating pragmatic speech acts. The translation result quality is analyzed using Rochayah Machali theory as the quality assessment parameter. The data used comprises utterance excerpts containing illocutionary speech acts performed by the main character, Otto. From the findings, a total of 160 illocutionary speech acts were identified in A Man Called Otto (2022) movie script and the most frequently performed by Otto is declarative illocutionary acts. The findings were subsequently translated using Google Translate and DeepL Translate, and then the result were analyzed using Rochayah Machali's Translation Quality Assessment Theory. Based on the analysis, it was observed that Google Translate and DeepL Translate produce fair translations in translating illocutionary acts. This is attributed to the fact that Google Translate and DeepL Translate still generate translations that, to some extent, retain the characteristics of literal translations and exhibit grammatical errors, although these errors do not surpass 25% of the total text correspondences.

SI23103

SKR BSI 23103

Perpustakaan FAH (Skripsi)

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