A computational architecture for conversation
A computational architecture for conversation
复制标题
用于对话的计算架构
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
Tim Paek
中科院分区：
文献类型：
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作者：
E. Horvitz;Tim Paek
我们描述了表示，推理策略，并在一个自动化的对话系统命名为贝叶斯接待员的控制程序。该原型的重点是对话域的目标通常由接待员在前台的建筑物在微软公司园区。该系统采用了一组贝叶斯用户模型来解释扬声器的目标，从他们的话语的自然语言解析收集到的证据。除了语言特征之外，领域模型还考虑了上下文证据，包括视觉发现。我们讨论了不确定性和系统的整体架构下的对话行动的关键原则，突出使用贝叶斯模型的层次结构在不同层次的细节，使用价值的信息来控制提问，并应用预期效用来控制进展和回溯对话。
We describe representation, inference strategies, and control procedures employed in an automated conversation system named the Bayesian Receptionist. The prototype is focused on the domain of dialog about goals typically handled by receptionists at the front desks of buildings on the Microsoft corporate campus. The system employs a set of Bayesian user models to interpret the goals of speakers given evidence gleaned from a natural language parse of their utterances. Beyond linguistic features, the domain models take into consideration contextual evidence, including visual findings. We discuss key principles of conversational actions under uncertainty and the overall architecture of the system, highlighting the use of a hierarchy of Bayesian models at different levels of detail, the use of value of information to control question asking, and application of expected utility to control progression and backtracking in conversation.