为社交机器人提供会话记忆以进行动机经验分享

Avinash Saravanan, Maria Tsfasman, Mark Antonius Neerincx, Catharine Oertel
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引用次数: 1

摘要

在与人进行的连续对话中,社交机器人必须确定要记住哪些方面,以及如何在对话中解决这些问题。在健康领域,重要的方面涉及与健康有关的目标、经历的进展(表达的情感)和追求这些目标的持续动机。尽管语音技术和会话代理取得了进步,但大多数社交机器人缺乏这种经验分享的记忆。本文介绍了一种基于记忆的动机复述的健康营养个性化行为改变支持会话记忆的设计和评估。主要的假设是,参考以前的会议可以提高动机和目标的实现,特别是当参考资料不同时。此外,本文还探讨了动机性复述在多大程度上影响用户对会话代理(虚拟Furhat)的感知。通过Zoom进行了一项有79名参与者的实验,包括三个对话环节。结果显示,当提供多个先前会议的参考时,参与者的动机变化显著增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Giving Social Robots a Conversational Memory for Motivational Experience Sharing
In ongoing and consecutive conversations with persons, a social robot has to determine which aspects to remember and how to address them in the conversation. In the health domain, important aspects concern the health-related goals, the experienced progress (expressed sentiment) and the ongoing motivation to pursue them. Despite the progress in speech technology and conversational agents, most social robots lack a memory for such experience sharing. This paper presents the design and evaluation of a conversational memory for personalized behavior change support conversations on healthy nutrition via memory-based motivational rephrasing. The main hypothesis is that referring to previous sessions improves motivation and goal attainment, particularly when references vary. In addition, the paper explores how far motivational rephrasing affects user’s perception of the conversational agent (the virtual Furhat). An experiment with 79 participants was conducted via Zoom, consisting of three conversation sessions. The results showed a significant increase in participants’ change in motivation when multiple references to previous sessions were provided.
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