Students’ Ability to Conduct Pre-Editing of Text Procedure for Google Neural Machine Translation

Abstract

This study aimed to find out students’ ability to conduct pre-editing on the text procedure inputs to Google Neural Machine Translation (GNMT). The participants in this study were students of the English Education Program, Faculty of Teacher Training and Education, Mataram University that took “Translation and Interpreting” subject in the fourth semester in Academic Year 2021/2022. The data were collected from assignments completed by 26 students in class A. Supporting data were collected through observation during the class. The data were analyzed using content analysis procedures such as identifying, categorizing, describing, and explaining. The results of this study indicate that almost all students could conduct pre-editing, but not perfectly, and some students failed to conduct pre-editing on the text. The result of pre-editing looked like a revised version of text. The pre-editing shows how the source text changes especially in language structure, word choice, and punctuation. The ability of the students in conducting the pre-editing on the the source text is represented by the good or bad quality of translated text by GNMT. Thus, the more effort performed in the pre-editing of the text context, the more likely it is to generate text to be in better quality in translation by GNMT.

Academic Text Quality Improvement By English Department Students of University of Mataram : A Study on Pre-Editing of Google Neural Machine Translation

“…Ayob (2015) identifies human, and machine translation as the two forms of translation available based on subject and technology. The translation process in human translation is carried out either entirely by humans or with the use of computer technology (Zulaika, Baharuddin, Wardana, & Farmasari, 2022). There are several techniques to translate our language into English nowadays.…”