Assessing AI-Powered Translation Quality: Insights from the Translation of the Farewell Sermon - Metwally, Amal Abdelsattar; Bin-Hady, Wagdi Rashad Ali; Asiri, Eisa (Universitas Negeri Makassar, 2024)
Artificial Intelligence (AI) powered translation influxes in the translation industry. Yet, questions have arisen about the quality of AI-powered translation systems (AIPTSs). Therefore, this study aims to evaluate the translation quality generated by ChatGPT for the Farewell Sermon. Using House's (2015) model of translation quality assessment (TQA), the study analyzed the Farewell Sermon focusing on text, register analysis of field, tenor mode, and genre. The language/text analysis revealed that AIPTSs produced lexical and syntactic inaccuracies that hindered capturing the sermon's intended religious voice. In register, Field, the analysis pointed out that the AIPTSs captured the broad themes of the Farewell Sermon, but often missed subtleties in religious terminology. AIPTSs also adopted superficial literal translation of the sentence structures. In Tenor, the analysis revealed that the Prophet's role as a moral and spiritual guide was somewhat diluted in the translation. Likewise, AIPTSs struggled to maintain the Prophet's authoritative and compassionate stance. The AIPTSs maintained general coherence but faced challenges with cohesive devices such as conjunctions, pronouns, and references. Furthermore, the microanalysis revealed an amount of 81 overt translation errors that the AIPTSs committed while translating the Farewell Sermon into English, the most frequent were