Shared knowledge in natural conversations: can entropy metrics shed light on information transfers?

Eliot Maës, P. Blache, Leonor Becerra
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Abstract

The mechanisms underlying human communication have been under investigation for decades, but the answer to how understanding between locutors emerges remains incomplete. Interaction theories suggest the development of a structural alignment between the speakers, allowing for the construction of a shared knowledge base (common ground). In this paper, we propose to apply metrics derived from information theory to quantify the amount of information exchanged between participants, the dynamics of information exchanges, to provide an objective way to measure the common ground instantiation. We focus on a corpus of free conversations augmented with prosodic segmentation and an expert annotation of thematic episodes. We show that during free conversations, the amount of information remains globally constant at the scale of the conversation, but varies depending on the thematic structuring, underlining the role of the speaker introducing the theme. We propose an original methodology applied to uncontrolled material.
自然对话中的共享知识:熵度量能揭示信息传递吗?
人类交流的潜在机制已经被研究了几十年,但言语者之间的理解是如何产生的,答案仍然不完整。互动理论建议在说话者之间发展一种结构一致性,允许建立一个共享的知识库(共同点)。在本文中,我们建议应用信息论衍生的度量来量化参与者之间交换的信息量,信息交换的动态,以提供一种客观的方法来衡量共同基础实例化。我们专注于一个自由对话的语料库,增强了韵律分割和主题剧集的专家注释。我们表明,在自由对话中,信息的总量在对话的规模上保持全局不变,但根据主题结构而变化,强调说话者介绍主题的作用。我们提出了一种应用于非受控材料的原始方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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