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All Journal IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature
Ida Kusuma Dewi
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Languange, Linguistic, Communication & Media

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Evaluation of Machine Translation Systems: A Literature Review on ChatGPT and Google Translate Ohod Faisal Ahmed; Ida Kusuma Dewi; Mohammad Yunus Anis
IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Vol. 13 No. 1 (2025): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Lite
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/ideas.v13i1.6236

Abstract

Abstract: This is a literature review discussing 15 selected papers about ChatGPT and Google Translate study results based on keyword analysis and publication year. We applied descriptive data analysis technique to analyze the data. We selected Studies on translation performance of natural language processing tools were chosen due to their increasing prominence and diverse applications, ranging from literary to technical translations. The data for this literature review was retrieved from Scopus and Google Scholar. The search was limited to the last five years to ensure the inclusion of recent advancements, particularly those reflecting improvements in ChatGPT’s GPT-4 engine and updates in Google Translate’s neural machine translation capabilities. The results showed that ChatGPT excels in fluency and contextual understanding, particularly in literary and poetic translations, outperforming Google Translate in maintaining stylistic elements and complex language structures. Both systems demonstrated strengths in specialized translations, with ChatGPT showing notable proficiency in medical literature and technical texts. However, challenges remained in low-resource languages and specialized domains, requiring further training and development. Despite technological advancements, human translators are essential for achieving culturally nuanced translations. This study has some implications for future implementing for enhancement contextual understanding, improving accuracy for low-resource languages, and addressing specific error patterns through ongoing research and collaborative efforts between human translators and machine translation tools. These recommendations aim to optimize the performance of ChatGPT and Google Translate, thereby ensuring more accurate and contextually appropriate translations across various fields.
Translating Arabic Literary Metaphors: A Comparative Evaluation of ChatGPT-4.0 and Google Translate 2024 Ohod Faisal Ahmed; Ida Kusuma Dewi; Mohammed Yunus Anis
IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Vol. 13 No. 2 (2025): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Lite
Publisher : Universitas Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/ideas.v13i2.7439

Abstract

This research conducted a comparative evaluation of ChatGPT-4.0 and Google Translate 2024 in translating Arabic literary metaphors into English. We applied a qualitative research approach focusing on the novel "Memory in the Flesh" by Ahlam Mosteghanemi, the study analyzed metaphor types 27 out of 77 data, translation strategies employed by each tool, and the quality of translations based on accuracy, acceptability, and readability. The study identified the types of metaphors used in the novel, analyzed the translation strategies employed by each tool based on (Newmark, 2022) framework, and evaluated the output quality using (Nababan et al., 2012, n.d.) assessment model of accuracy, acceptability, and readability. Findings indicated that while Google Translate 2024 showed a slight edge in literal accuracy which achieved 2.85, in acceptability Google Translate 2024 achieved 2.62 score and in readability achieved 2.31, ChatGPT-4.0 significantly outperformed it in acceptability and readability crucial for literary texts, In acceptability ChatGPT4.0 achieved 2.98 and in readability 2.99 score. The study highlighted the evolving capabilities of machine translation in handling nuanced literary language and underscores the continued importance of human oversight in achieving high-quality literary. The research emphasized Involving capabilities of neural machine translation systems, particularly in handling complex and nuanced literary content. However, it also underscored their limitations, especially in capturing cultural subtleties and maintaining the figurative resonance of literary metaphors. It underscored the continued necessity of human oversight to ensure fidelity and artistic integrity in literary translation, offering insights for translators, educators, and MT developers alike.
Evaluation of Machine Translation Systems: A Literature Review on ChatGPT and Google Translate Ohod Faisal Ahmed; Ida Kusuma Dewi; Mohammad Yunus Anis
IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Vol. 13 No. 1 (2025): IDEAS: Journal on English Language Teaching and Learning, Linguistics and Lite
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/ideas.v13i1.6236

Abstract

Abstract: This is a literature review discussing 15 selected papers about ChatGPT and Google Translate study results based on keyword analysis and publication year. We applied descriptive data analysis technique to analyze the data. We selected Studies on translation performance of natural language processing tools were chosen due to their increasing prominence and diverse applications, ranging from literary to technical translations. The data for this literature review was retrieved from Scopus and Google Scholar. The search was limited to the last five years to ensure the inclusion of recent advancements, particularly those reflecting improvements in ChatGPT’s GPT-4 engine and updates in Google Translate’s neural machine translation capabilities. The results showed that ChatGPT excels in fluency and contextual understanding, particularly in literary and poetic translations, outperforming Google Translate in maintaining stylistic elements and complex language structures. Both systems demonstrated strengths in specialized translations, with ChatGPT showing notable proficiency in medical literature and technical texts. However, challenges remained in low-resource languages and specialized domains, requiring further training and development. Despite technological advancements, human translators are essential for achieving culturally nuanced translations. This study has some implications for future implementing for enhancement contextual understanding, improving accuracy for low-resource languages, and addressing specific error patterns through ongoing research and collaborative efforts between human translators and machine translation tools. These recommendations aim to optimize the performance of ChatGPT and Google Translate, thereby ensuring more accurate and contextually appropriate translations across various fields.
Co-Authors Mohammad Yunus Anis Mohammed Yunus Anis Ohod Faisal Ahmed