Achimova Asya, Franke Michael, Butz Martin V
Department of Linguistics, University of Tübingen, Tübingen, Germany.
Department of Computer Science, University of Tübingen, Tübingen, Germany.
PLoS One. 2025 May 28;20(5):e0323839. doi: 10.1371/journal.pone.0323839. eCollection 2025.
Speakers often choose utterances under uncertainty about the potential opinion of the listener. In this case, utterances that do not signal the speaker's opinion directly may allow the speaker to avoid possible conflict: saying that an election outcome is interesting rather than amazing, even if the speaker is truly excited about it, may give her an option to retreat if it turns out that the listener's opinion is the opposite. By enhancing the Rational Speech Act framework with a turn-taking pragmatic system, we develop a model of indirect communication that is able to (1) rationalize the choice of indirect utterances when speakers' opinions do not align; (2) capture complex reasoning about the true interlocutor's opinion when facing indirect utterances and responses. The model has several novel features: in addition to standard informativeness goals, speaker choices factor in potential divergences of opinions between conversation partners. The listener model further considers multi-turn dialogues rather than isolated utterances: it is able to derive that an utterance like "interesting" can be interpreted positively or negatively depending on preceding discourse. The model, though complex, makes novel, non-trivial qualitative predictions, which are supported by data from three behavioral experiments reported here.
说话者在不确定听众潜在意见的情况下常常会选择话语。在这种情况下，那些不直接表明说话者意见的话语可能会让说话者避免潜在的冲突：即使说话者真的对选举结果感到兴奋，说选举结果“有趣”而不是“惊人”，如果结果发现听众的意见相反，这可能会给她一个退路。通过用轮流发言的语用系统增强理性言语行为框架，我们开发了一种间接交流模型，该模型能够：（1）当说话者的意见不一致时，使间接话语的选择合理化；（2）在面对间接话语和回应时，捕捉关于真实对话者意见的复杂推理。该模型有几个新颖的特点：除了标准的信息性目标外，说话者的选择还考虑了对话伙伴之间潜在的意见分歧。听众模型进一步考虑多轮对话而不是孤立的话语：它能够推断出像“有趣”这样的话语根据之前的话语可以被积极或消极地解释。该模型虽然复杂，但做出了新颖的、重要的定性预测，这些预测得到了这里报告的三个行为实验数据的支持。
