Multilingual Dialogue Generation and Localization with Dialogue Act Scripting
This addresses the problem of generating natural and culturally appropriate dialogues for non-English languages, which is incremental as it builds on structured dialogue act representations to improve over translation-based approaches.
The paper tackles the scarcity of non-English dialogue datasets and the artifacts introduced by translation by proposing Dialogue Act Script (DAS), a framework for generating culturally appropriate multilingual dialogues from abstract intents, with human evaluations showing DAS outperforms translation-based methods in cultural relevance, coherence, and appropriateness across Italian, German, and Chinese.
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.