The rapid development of computer and network technologies has led to the increasing acceptance and application of the “machine translation＋post-editing” translation model by language service providers. While the quality of machine translation has significantly improved, errors still persist in the output, indicating that human translation cannot be entirely replaced. Therefore, manual post-editing and proofreading play a crucial role in enhancing the quality of machine-translated texts. This study takes an excerpt from Hubei Industrial Culture and Design as an example, employs a case study method and chooses two machine translation tools including DocHero.ai and Google. By contrasting the machine-translated versions with manually edited English translations, the study analyzes errors in machine translation in industrial text translation and highlights the differences between machine translation and human translation. It also discusses considerations for machine translation, proposes corresponding post-editing methods for different types of machine translation errors, and summarizes English translation strategies and methods for industrial texts, aiming to provide insights for Chinese-English translation of industrial information texts.
Yue Li (Thu,) studied this question.
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