This study aims to investigate accuracy and fluency of COVID-19 words generated by the three MT tools, namely, Google Translate, Baidu Translate and DeepL Translator. Data analysis is done through human evaluation toward translation texts by using a translation rubric at the word, sentence and paragraph level. To ensure the credibility of translation texts analysis, ten raters are involved to analyse the translation texts at sentence and paragraph levels. It is found that the three machine translation tools can maintain a high accuracy rate in the translation of simple words and short sentences, but the collection of new words is relatively slow and the translation of longer sentences or paragraphs is not adequate and fluent enough. Further, there are language problems such as grammar and logical coherence.

Zhang Li, Chi Lixia, Yang Wenyi. Accuracy and Fluency of High-frequency COVID-19 Words Translated by Three Machine Translation(MT) Tools. Academic Journal of Humanities & Social Sciences (2023) Vol. 6, Issue 24: 98-103. https://doi.org/10.25236/AJHSS.2023.062417.

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