Paper: Generative Goal-Driven User Simulation for Dialog Management

ACL ID D12-1007
Title Generative Goal-Driven User Simulation for Dialog Management
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012

User simulation is frequently used to train statistical dialog managers for task-oriented domains. At present, goal-driven simula- tors (those that have a persistent notion of what they wish to achieve in the dialog) re- quire some task-specific engineering, making them impossible to evaluate intrinsically. In- stead, they have been evaluated extrinsically by means of the dialog managers they are in- tended to train, leading to circularity of argu- ment. In this paper, we propose the first fully generative goal-driven simulator that is fully induced from data, without hand-crafting or goal annotation. Our goals are latent, and take the form of topics in a topic model, clustering together semantically equivalent and phoneti- cally confusable strings, implicitly modelling synonymy and speech...