Google Translate Versus Matecat for Religious Text Translation
A Study of Iranian Students' Speed, Accuracy, and Perceptions
Abstract
Technological advancement has led to the advent of numerous Machine Translation system and Computed-Assisted Translation (CAT) tools. This study compared the effectiveness of Google Translate as an MT system with Matecat, a CAT tool. It examined their impact on translation quality, speed, and user feedback on both systems. The research involved two classes at the Islamic Azad University of Qom, with 16 students assigned to the Matecat group and 11 to the Google Translate group. All participants first translated a 250-word religious text using dictionaries and completed a placement test showing they shared an intermediate English proficiency level. Following instructions, participants used their assigned system to translate the same text for the post-test. The research team assessed translation quality using Waddington's model. Dependent t-tests showed that while Google Translate significantly reduced translation time without improving quality, Matecat achieved faster and better quality than human translation. Independent t-tests found no significant differences between the systems regarding translation accuracy and speed. Students responded positively to both systems, noting their user-friendly interfaces and accurate religious terminology and grammar handling. They expressed satisfaction with both tools and indicated they would continue using them.
Keywords:
Google Translate, Machine Translation, Machine Translation Output, Matecat, Translation Quality AssessmentReferences
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Copyright (c) 2025 Abolfazl Khorasanizadeh Gazki, Dariush Nejad Ansari Mahabadi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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).
