寻找共同基础：在口语对话中标注与预测共同基础
Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations
AI总结：
本文针对自然语言处理中共同基础研究不足的问题，提出新的标注方案与语料库，并通过从对话中提取命题、按说话者视角追踪其共同基础状态的初步实验，为对话理解中的认知状态建模提供资源与方法。
摘要：
当我们与其他人类交流时，我们并不仅仅是生成一串词语。相反，我们利用自身的认知状态（信念、欲望、意图）以及我们对听众认知状态的建模，来生成能够以预期方式影响听众认知状态的话语。认知状态的一个重要组成部分是共同基础，即说话者相信的内容、说话者相信听众相信的内容，依此类推。尽管认知科学领域对共同基础给予了大量关注，但在自然语言处理领域相关工作却不多。在本文中，我们引入了一种新的标注方案和语料库来捕捉共同基础。随后，我们描述了一些初步实验，这些实验从对话中提取命题，并从每个说话者的视角追踪这些命题在共同基础中的状态。
英文摘要：
When we communicate with other humans, we do not simply generate a sequence of words. Rather, we use our cognitive state (beliefs, desires, intentions) and our model of the audience's cognitive state to create utterances that affect the audience's cognitive state in the intended manner. An important part of cognitive state is the common ground, which is the content the speaker believes, and the speaker believes the audience believes, and so on. While much attention has been paid to common ground in cognitive science, there has not been much work in natural language processing. In this paper, we introduce a new annotation and corpus to capture common ground. We then describe some initial experiments extracting propositions from dialog and tracking their status in the common ground from the perspective of each speaker.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
