A Comparative Study on Translation of Persian Colloquialism into English by ChatGPT and Other Translation Platforms
Abstract
Translating colloquialism as a basic challenge in the process of literary translation could be used as a criteria to investigate the capabilities of the translation machines and tools, most of which use artificial intelligence (AI). The present research was an attempt to investigate the performance of Yandex Translate (YT), Microsoft Bing Translate (BT), Google Translate (GT), ChatGPT, and MateCat (MC), in translating Persian colloquialism. In this process, the researchers tried to compare these platforms’ translations, demonstrate their weaknesses and propose improving suggestions to the designers of translation platforms. To this end 202 Persian sentences or phrases containing 240 colloquial expressions, words, and tones were entered into these five platforms and their translations were evaluated based on parameters including semantic accuracy and colloquial language recognition and stylistic transference. Orlando’s (2011) grid descriptor was adopted to give grades to the translations and Fuzzy-Math method was used for the precise analysis and comparison of results. In the end, the results revealed the higher position of Microsoft Bing Translate in translating Persian colloquialism.
Keywords:
Artificial intelligence, Colloquial language, Fuzzy-math, Machine translation, Stylistic equivalenceReferences
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Copyright (c) 2024 Zeynab Mirhashemi, Mahvash Gholami, Hossein Bhari
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Copyright Licensee: Iranian Journal of Translation Studies. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0 license).
