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Contrastive Analysis of Machine Translator (Google Translator and Chat Gpt Translator) and Human Translation of Modal Verbs of the Little Prince

Publish Year: 1403
Type: Conference paper
Language: English
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ICLP13_141

Index date: 16 April 2025

Contrastive Analysis of Machine Translator (Google Translator and Chat Gpt Translator) and Human Translation of Modal Verbs of the Little Prince abstract

The contrastive analysis of machine translation (MT) systems —Google Translate and ChatGPT — and human translation of modal verbs in The Little Prince from English to Persian reveals significant insights into the current capabilities and limitations of these technologies. This study underscores the limitations of current MT systems in literary translation tasks, particularly when dealing with linguistically and culturally complex texts. While MT technology has made significant strides in general translation tasks, translating nuanced literary elements remains a domain where human translators significantly outperform machines. These MT systems often produce translations that lack the necessary contextual sensitivity, leading to outputs that are either overly literal or fail to capture the intended meaning of the original text. The BLEU score of 0.21, observed across the translations, starkly highlights the challenges that both Google Translate and ChatGPT face in handling complex linguistic elements, particularly modal verbs when translating literary texts between languages with substantial structural differences, such as English and Persian. Modal verbs, which carry nuanced meanings related to necessity, possibility, and obligation, are deeply embedded in the source language context. The low BLEU score indicates that neither Google Translate nor ChatGPT can consistently replicate the subtleties of modal verbs as effectively as a human translator. In conclusion, this research emphasizes the need for further advancements in MT technologies to better handle the complexities of literary translation. Improving the ability of MT systems to understand and accurately translate context-dependent elements like modal verbs is essential for achieving higher translation fidelity. Until such improvements are realized, human translators will remain indispensable for preserving the integrity and subtleties of literary works in translation.

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Contrastive Analysis of Machine Translator (Google Translator and Chat Gpt Translator) and Human Translation of Modal Verbs of the Little Prince authors

Shiva Sadighi

Assistant Professor at Zand Institute of Higher Education

Mohammad Bakhshandeh

Zand Institute of Higher Education

Mohammad Mehdi Mortahan

Assistant Professor at Zand Institute of Higher Education