Exploring ChatGPT's potential for augmenting post-editing in machine translation across multiple domains: challenges and opportunities - Jeehaan Algaraady; Mohammad Mahyoob (Frontiers in Artificial Intelligence)
IntroductionPost-editing plays a crucial role in enhancing the quality of machine-generated translation (MGT) by correcting errors and ensuring cohesion and coherence. With advancements in artificial intelligence, Large Language Models (LLMs) like ChatGPT-4o offer promising capabilities for post-editing tasks. This study investigates the effectiveness of ChatGPT-4o as a natural language processing tool in post-editing Arabic translations across various domains, aiming to evaluate its performance in improving productivity, accuracy, consistency, and overall translation quality.MethodsThe study involved a comparative analysis of Arabic translations generated by Google Translate. These texts, drawn from multiple domains, were post-edited by two professional human translators and ChatGPT-4o. Subsequently, three additional professional human post-editors evaluated both sets of post-edited outputs. To statistically assess the differences in quality between humans and ChatGPT-4o post-edits, a paired t-test was employed, focusing on metrics such as fluency, accuracy, coherence, and efficiency.ResultsThe findings indicated that human post-editors outperformed ChatGPT-4o in most quality metrics. However, ChatGPT-4o demonstrated superior efficiency, yielding a positive t-statistic of 8.00 and a p-value of 0.015, indicating a statistically significant difference. Regarding fluency, no significant difference was observed between the two methods (t-statistic = −3.5, p-value = 0.074), suggesting comparable performance in ensuring the natural flow of text.DiscussionChatGPT-4o showed competitive performance in English-to-Arabic post-editing, particularly in producing fluent, coherent, and stylistically consistent text. Its conversational design enables efficient and consistent editing across various domains. Nonetheless, the model faced challenges in handling grammatical and syntactic nuances, domain-specific idioms, and complex terminology, especially in medical and sports contexts. Overall, the study highlights the potential of ChatGPT-4o as a supportive tool in translation post-editing workflows, complementing human translators by enhancing productivity and maintaining acceptable quality standards.