Building upon the foundation of Neural Machine Translation (NMT) and utilizing NMT tools (e.g., Baidu Translate and Youdao Translate) to assist human translators, this study investigates the necessity and effectiveness of post-editing in enhancing the quality of Chinese Intangible Cultural Heritage (ICH) texts translated into English. Despite the conveniences offered by various NMT tools, inherent limitations persist, thus necessitating human post-editing to refine the accuracy and fluency of the translated texts through remedial strategies and adjustments. Taking the translation of Chinese ICH texts into English as a case study, we conducted a comparative analysis of NMT tools and human post-editing for translating ICH texts involving eight perspectives which range from word connotation to sentence structure of ICH text. The provision of translation examples and insights can serve as a practical guide for translators engaged in NMT-based ICH and cultural translation projects, helping them resolve common translation issues and improving the overall quality of the output. This can be applied to similar cases with other languages.
Jiang et al. (Wed,) studied this question.