EAGER: Collaborative Research: Modeling Distinctive Partners in Adaptive Spoken Dialog

人类灵活使用语言的能力是强大智力的标志。在互动对话中，话语是根据与特定伙伴的共同基础或特定语境而动态调整的。然而，与口语对话系统的互动是高度受限的，当系统呈现预先确定的信息时，说话者在说话内容上的灵活性很小。为了使交互式对话技术广泛使用，这个探索性的跨学科项目收集了一个展示一些重要变化源的对话语料库，分析语料库，并使用结果分析来开发动态对话策略的模型和原型实现。这项工作的最终目标是支持能够适应在线的全新的、灵活的和健壮的口语对话系统的综合。行走- around语料库由40个人与人之间的对话交互组成，其中远程位置的人为在城市或校园环境中行走的行人提供指示。实验范式改变了对话伙伴的友谊关系，导演是否能看到行人所看到的，以及导演和行人对环境的熟悉程度。没有其他现有的给出方向的语料库在室外实时环境中模拟对话交互，在这种环境中，物理上下文是对话上下文的基础。由此产生的语料库用于测试关于本地和全球对话适应策略演变的假设，并开发模型。我们努力的关键是确定哪些适应实际上是功能性的，也就是说，对口语对话系统中的特定任务或上下文有益。

The human ability to use language flexibly is a hallmark of robust intelligence. In interactive dialog, utterances are dynamically tailored to the common ground or specific context with specific partners. However, interaction with spoken dialog systems is highly constrained and constraining, allowing speakers very little flexibility in what they can say while the system presents pre-determined messages. To make interactive dialog technology broadly useful, this exploratory interdisciplinary project collects a corpus of dialogs exhibiting some important sources of variation, analyzes the corpus, and uses the resulting analyses to develop models and prototype implementations of dynamic dialog strategies. The ultimate goal of this effort is to support the synthesis of entirely new, flexible, and robust spoken dialog systems that are capable of adapting on-line. The Walking-Around corpus consists of 40 human-human dialog interactions where a remotely located person gives directions to a pedestrian walking around in an urban or campus environment. The experimental paradigm varies the friendship relationship of the dialog partners, whether the director can see what the pedestrian sees, and the familiarity of both the director and the pedestrian with the environment. No other existing direction-giving corpora model dialog interaction in an outdoor real-time environment where the physical context grounds the dialog context. The resulting corpus is used to test hypotheses about, and develop models of, the evolution of local and global dialog adaptation strategies. Key to our effort is determining which adaptations are actually functional, that is, beneficial for a particular task or context in spoken dialog systems.