The Evaluation of Machine Translation and Human Translation on YouTube: A Comparative Study
The Evaluation of Machine Translation and Human Translation
Abstract
This study compared machine translation and human translation quality, particularly in the context of selected "Sukses Daily" videos on YouTube. In achieving these goals, this research used mixed-method approaches. It was analyzed based on the Translation Quality Assessment (TQA) model by Nababan et. al. (2012): accuracy, acceptability, and readability. Meanwhile, the data was collected through questionnaires distributed and opinions were sought through interviews with the raters. The analysis showed that human translation generally outperformed machine translation in accuracy, acceptability, and readability. Machine translation scored an average of 1.48 out of 3 for accuracy, 1.81 out of 3 for acceptability, and 1.99 out of 3 for readability, indicating poor quality. On the other hand, human translation scored an average of 2.65 out of 3 for accuracy, 2.52 out of 3 for acceptability, and 2.72 out of 3 for readability, indicating good quality. The findings could contribute to the advancement of translation knowledge and encourage further research in the field.
Keywords: Translation Quality Assessment, Machine Translation, Human Translation.
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