Machine Translation and Post-Editing in Special Education Research Titles: A Comparative Study of Google Translate and ChatGPT-4

Abstract

This qualitative study compares machine translations and post-editing of academic titles in the field of special education and rehabilitation from Serbian to English using Google Translate and ChatGPT-4. First, thirty-eight titles from two conference proceedings were machine-translated by both tools. Nineteen title pairs were then selected for the post-editing process conducted by a professional and experienced translator. Two main criteria were considered in the analysis: accuracy of specialized terminology and overall fluency and readability. The findings show that ChatGPT-4 produced more natural and fluent translations, with fewer redundancies and issues related to specialized terminology, compared to Google Translate. Still, human post-editing was necessary for both translation tools to ensure natural flow, clarity, and terminological precision. While machine translation is time-saving and cost-effective, it can only be used as a starting point in the translation process, where professional post-editing remains indispensable for highly specialized contexts. Given the small exploratory dataset, the findings should be interpreted with caution.

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