This study assesses the translation accuracy of ChatGPT-4 against two human translators, Donald Keene and Mark Gibeau, focusing on the first 50 sentences of Osamu Dazai's Japanese novel "Ningen Shikkaku" translated into English. In the rapidly advancing field of artificial intelligence, where AI increasingly integrates into fields such as translation traditionally occupied by humans, it examines the effectiveness and reliability of AI incapturing both the literal and figurative meaning of a literary text. A significant gap in the field is the scarcity of comparative studies between AI and human translators, and all the more so in Japanese-English translation. Most existing research on AI translation focuses on European languages or evaluates AI against other machine translation tools. The study employs a translation quality assessment framework based on how erroneous the translations are, where either one or two points are deducted for each error depending on severity to evaluate the accuracy of each translation. The identified error types are grounded on the standardized error marking system utilized by the American Translators Association, and endeavors to provide an objective measure of translation quality. The results of the study show that ChatGPT-4's translation incurred the least number of point deductions, roughly half as many as those of Gibeau and Keene. Gibeau's translation rankedsecond in accuracy, with Keene's trailing closely behind. The results also reveal that Keene's translation errors typically stemmed from altered words and phrases, while Gibeau's translation rather added, intensified, or omitted elements. ChatGPT-4's translation had fewer errors overall, except in relation to literalness. It is discussed that the utility of AI in literary translation varies depending on whether accuracy or aesthetic is most valued. Nevertheless, translators can already at present utilize AI to manage routine tasks and accelerate translation processes, enabling them to concentrate on aspects such as flow, rhythm, and readability.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:du-48712 |
| Date | January 2024 |
| Creators | Malmqvist, Emilia |
| Publisher | Högskolan Dalarna, Institutionen för språk, litteratur och lärande |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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