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学习运用叙事功能词来组织和交流经验。

Learning to Use Narrative Function Words for the Organization and Communication of Experience.

作者信息

Pointeau Gregoire, Mirliaz Solène, Mealier Anne-Laure, Dominey Peter Ford

机构信息

INSERM UMR 1093-CAPS, Université Bourgogne Franche-Comté, UFR des Sciences du Sport, Dijon, France.

Robot Cognition Laboratory, Marey Institute, Dijon, France.

出版信息

Front Psychol. 2021 Mar 3;12:591703. doi: 10.3389/fpsyg.2021.591703. eCollection 2021.

Abstract

How do people learn to talk about the causal and temporal relations between events, and the motivation behind why people do what they do? The narrative practice hypothesis of Hutto and Gallagher holds that children are exposed to narratives that provide training for understanding and expressing reasons for why people behave as they do. In this context, we have recently developed a model of narrative processing where a structured model of the developing situation (the situation model) is built up from experienced events, and enriched by sentences in a narrative that describe event meanings. The main interest is to develop a proof of concept for how narrative can be used to structure, organize and describe experience. Narrative sentences describe events, and they also define temporal and causal relations between events. These relations are specified by a class of narrative function words, including "because, before, after, first, finally." The current research develops a proof of concept that by observing how people describe social events, a developmental robotic system can begin to acquire early knowledge of how to explain the reasons for events. We collect data from naïve subjects who use narrative function words to describe simple scenes of human-robot interaction, and then employ algorithms for extracting the statistical structure of how narrative function words link events in the situation model. By using these statistical regularities, the robot can thus learn from human experience about how to properly employ in question-answering dialogues with the human, and in generating canonical narratives for new experiences. The behavior of the system is demonstrated over several behavioral interactions, and associated narrative interaction sessions, while a more formal extended evaluation and user study will be the subject of future research. Clearly this is far removed from the power of the full blown narrative practice capability, but it provides a first step in the development of an experimental infrastructure for the study of socially situated narrative practice in human-robot interaction.

摘要

人们是如何学会谈论事件之间的因果关系和时间关系,以及人们做某事背后的动机的呢?胡托和加拉格尔的叙事实践假说认为,儿童接触到的叙事为理解和表达人们行为的原因提供了训练。在这种背景下,我们最近开发了一种叙事处理模型,其中发展情境的结构化模型(情境模型)是从经历的事件中构建起来的,并通过描述事件意义的叙事中的句子得到丰富。主要兴趣在于为叙事如何用于构建、组织和描述经验开发一个概念验证。叙事句子描述事件,它们还定义了事件之间的时间和因果关系。这些关系由一类叙事功能词指定,包括“因为、之前、之后、首先、最后”。当前的研究开发了一个概念验证,即通过观察人们如何描述社会事件,一个发展型机器人系统可以开始获得关于如何解释事件原因的早期知识。我们从使用叙事功能词描述人机交互简单场景的天真受试者那里收集数据,然后使用算法提取叙事功能词在情境模型中链接事件的统计结构。通过使用这些统计规律,机器人可以从人类经验中学习如何在与人类的问答对话中正确使用,并为新经验生成规范的叙事。该系统的行为在几次行为交互和相关的叙事交互会话中得到了展示,而更正式的扩展评估和用户研究将是未来研究的主题。显然,这与成熟的叙事实践能力相去甚远,但它为在人机交互中研究社会情境叙事实践的实验基础设施的开发提供了第一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/7982915/66c85c7be07b/fpsyg-12-591703-g001.jpg

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