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    <abstract>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 Ma-chine 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.</abstract>
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%0 Conference Proceedings
%T Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT’s Customizability
%A Yamada, Masaru
%Y Yamada, Masaru
%Y do Carmo, Felix
%S Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track
%D 2023
%8 September
%I Asia-Pacific Association for Machine Translation
%C Macau SAR, China
%F yamada-2023-optimizing
%X 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 Ma-chine 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.
%U https://aclanthology.org/2023.mtsummit-users.19
%P 195-204

Markdown (Informal)

[Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT’s Customizability](https://aclanthology.org/2023.mtsummit-users.19) (Yamada, MTSummit 2023)

• Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT’s Customizability (Yamada, MTSummit 2023)

ACL

• Masaru Yamada. 2023. Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT’s Customizability. In Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track, pages 195–204, Macau SAR, China. Asia-Pacific Association for Machine Translation.