EAGER: An Animated Agent for Developing the Conversational Skills of Individuals with Social Interaction Difficulties

探索性研究早期的Grant试图开发一个基于计算机的动画代理的探索性版本，模拟对话伙伴，允许社交困难的用户，如患有阿斯伯格综合症的用户，练习对话技能。互动将探索通过对话与用户建立友好的融洽关系；建立这种融洽的关系是目标个人难以获得的一项重要的社交技能。根据假设，这些人将从探索性主体中获得非常显著的好处，因为他们可以练习对话技能，而不会有失败或给人留下糟糕印象的风险。这项探索性技术最令人兴奋的部分是，它将用户置于与标准化、客观和可重复的刺激互动的驾驶座上。“熟悉”场景的体系结构框架足够通用，可以适用于许多其他具有社会重要性的受限对话场景，例如求职面试、客户服务和参与群体决策。探索性代理是一个模拟的成年人，以经验丰富的顾问的成熟、耐心的方式做出反应(罗切斯特大学医学中心的一名专家顾问为该项目提供咨询)。代理将用户话语的主题和内容与伴随话语的韵律、面部表情、凝视方向和头部运动相关联。该代理还通过红/绿屏幕图标提供有关这些行为的有用的实时反馈，并在会话结束时提供行为摘要和改进行为的建议。这个探索性项目的初始领域是“熟悉”，也就是说，参与一种对于以前没有见过面的人来说是常规的闲聊。对话框架具有一些独立于主题的交易性知识，用于发起对话并在对话期间做出适当的回应。当用户对代理的问题和提示的回答偏离预期时，代理转向一系列策略，包括回避回答、请求重复、提供鼓励和提示进一步输入。该项目包括探索更一般的问题，如在动画代理中整合非语言行为和语言行为所需的体系结构。该项目还带来了新的用户界面，可以捕获反映对话动态的非语言行为分析。

This EArly Grant for Exploratory Research seeks to develop an exploratory version of a computer-based animated agent that simulates a conversational partner, allowing users with social interaction difficulties, such as ones with Asperger syndrome, to practice conversational skills. The interaction will explore establishing friendly rapport with the user through conversation; building such rapport is an important social skill that is difficult for the targeted individuals to acquire. It is hypothesized that such individuals will very significantly benefit from the exploratory agent, by allowing them to practice conversational skills without risk of failure or of making a poor impression. The most exciting part of this exploratory technology is that it puts users in the driver's seat of the interaction with a standardized, objective and repeatable stimulus. The architectural framework for the "getting acquainted" scenario is general enough to be adaptable to many other restricted conversational scenarios of societal importance such as job interviews, customer service, and participating in group decision-making. The exploratory agent is a simulated adult responding in the mature, patient manner of an experienced consultant (an expert advisor from the University of Rochester Medical Center consults on the project). The agent correlates the topic and content of the user's utterances with the prosody, facial expressions, gaze direction and head motions accompanying the utterances. The agent also provides helpful real-time feedback via red/green screen icons about these behaviors, and behavioral summaries and suggestions for improving the behavior at the end of a session. The initial domain in this exploratory project is "getting acquainted", i.e., engaging in the sort of small talk that is conventional for individuals who have not previously met. The dialogue framework has some transactional knowledge, independent of topic, to initiate a conversation and to respond appropriately during a conversation. When the user's responses to the agent's questions and prompts deviate from expectations, the agent branches to clusters of strategies including evasive answers, requesting repetition, providing encouragement and prompting further input. The project includes exploration of more general questions such as the architecture required for integrating nonlinguistic and linguistic behavior in an animated agent. The project also leads to new user interfaces that can capture nonverbal behavior analytics reflecting the dynamics of the conversation.