Paper: Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning

ACL ID D08-1100
Title Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspects of this problem are the design of a di- alog information representation and a learning approach that supports capture of domain in- formation from in-domain dialogs. To represent a dialog for a learning purpose, we based our representation, the form-based di- alog structure representation, on an observa- ble structure. We show that this representation is sufficient for modeling phenomena that oc- cur regularly in several dissimilar task- oriented domains, including information- access and problem-solving. With the goal of ultimately reducing human annotation effort, we examine the use of unsupervise...