用结构化对话行为生成多语言对话，更自然更符合文化习惯。
Multilingual Dialogue Generation and Localization with Dialogue Act Scripting
- 用对话行为框架替代直接翻译，从意图生成本地化对话
- 中/德/意语评估显示，生成对话在文化相关性上优于机器与人工翻译
- 适合做跨语言对话系统、本地化内容生成的研究者
非英语对话数据集稀缺，现有模型常基于英语对话的翻译进行训练或评估，这会引入不自然且文化不恰当的偏差。本文提出对话行为脚本（Dialogue Act Script, DAS），一种从抽象意图表示出发，编码、本地化并生成多语言对话的结构化框架。DAS不直接翻译语句，而是生成符合目标语言文化背景和情境的全新对话，提升自然度与适切性。通过结构化对话行为表示，该方法支持跨语言灵活本地化，减少翻译腔，实现更流畅自然的交流。在意大利语、德语和中文上的真人评估表明，DAS生成的对话在文化相关性、连贯性和情境适切性方面均持续优于机器与人工翻译结果。
原文摘要 · Abstract (English)
Non-English dialogue datasets are scarce, and models are often trained or evaluated on translations of English-language dialogues, an approach which can introduce artifacts that reduce their naturalness and cultural appropriateness. This work proposes Dialogue Act Script (DAS), a structured framework for encoding, localizing, and generating multilingual dialogues from abstract intent representations. Rather than translating dialogue utterances directly, DAS enables the generation of new dialogues in the target language that are culturally and contextually appropriate. By using structured dialogue act representations, DAS supports flexible localization across languages, mitigating translationese and enabling more fluent, naturalistic conversations. Human evaluations across Italian, German, and Chinese show that DAS-generated dialogues consistently outperform those produced by both machine and human translators on measures of cultural relevance, coherence, and situational appropriateness.
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