让AI翻译更懂文化差异，尤其在日英职场邮件中
Designing LLMs for cultural sensitivity: Evidence from English-Japanese translation
- 用不同提示策略测试AI翻译的文化适配性
- 有文化指引的提示使译文更符合日本职场语境
- 适合需要跨文化沟通的AI系统设计者参考
大型语言模型（LLMs）越来越多地用于日常交流，包括跨文化语境下的多语言互动。尽管当前的LLMs能生成近乎完美的字面翻译，但其是否支持文化恰当的沟通仍不明确。本文研究不同LLM设计在英日职场邮件翻译中的文化敏感性。我们对比三种提示策略：(1) 简单的“仅翻译”提示，(2) 针对受众文化背景的提示，(3) 明确提供日本沟通规范指导的指令提示。通过混合方法研究，分析文化特定的语言模式，评估翻译对文化规范的适应程度，并由母语者判断语气恰当性。结果表明，文化定制化提示可显著提升翻译的文化契合度。基于此，我们提出在多语言场景中设计更具包容性的LLMs的建议。
原文摘要 · Abstract (English)
Large language models (LLMs) are increasingly used in everyday communication, including multilingual interactions across different cultural contexts. While LLMs can now generate near-perfect literal translations, it remains unclear whether LLMs support culturally appropriate communication. In this paper, we analyze the cultural sensitivity of different LLM designs when applied to English-Japanese translations of workplace e-mails. Here, we vary the prompting strategies: (1) naive "just translate" prompts, (2) audience-targeted prompts specifying the recipient's cultural background, and (3) instructional prompts with explicit guidance on Japanese communication norms. Using a mixed-methods study, we then analyze culture-specific language patterns to evaluate how well translations adapt to cultural norms. Further, we examine the appropriateness of the tone of the translations as perceived by native speakers. We find that culturally-tailored prompting can improve cultural fit, based on which we offer recommendations for designing culturally inclusive LLMs in multilingual settings.
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