This paper explores the influence of integrating the purpose of the translation and the target audience into prompts on the quality of translations produced by ChatGPT. Drawing on previous translation studies, industry practices, and ISO standards, the research underscores the significance of the pre-production phase in the translation process. The study reveals that the inclusion of suitable prompts in large-scale language models like ChatGPT can yield flexible translations, a feat yet to be realized by conventional Machine Translation (MT). The research scrutinizes the changes in translation quality when prompts are used to generate translations that meet specific conditions. The evaluation is conducted from a practicing translator's viewpoint, both subjectively and qualitatively, supplemented by the use of OpenAI's word embedding API for cosine similarity calculations. The findings suggest that the integration of the purpose and target audience into prompts can indeed modify the generated translations, generally enhancing the translation quality by industry standards. The study also demonstrates the practical application of the "good translation" concept, particularly in the context of marketing documents and culturally dependent idioms.

这篇论文探讨了将翻译目的和目标受众整合到ChatGPT的提示中对所生成翻译质量的影响。研究强调了翻译过程中的前期准备阶段的重要性，通过借鉴以往的翻译研究、行业实践和ISO标准进行分析。研究发现，在像ChatGPT这样的大规模语言模型中加入适当的提示可以产生灵活的翻译，而传统的机器翻译尚未实现这一目标。通过使用OpenAI的词嵌入API进行余弦相似度计算，评估从从实际翻译员的视角主观和定性地进行，结果表明将翻译目的和目标受众整合到提示中确实可以修改所生成的翻译，从而在行业标准上普遍提高翻译质量。该研究还展示了“良好的翻译”概念的实际应用，特别是在营销文件和文化习语的背景下。

通过提示工程优化机器翻译：ChatGPT可定制性的研究探讨