Agenda-Based User Simulation for Bootstrapping a POMDP Dialogue System

Jost Schatzmann,Blaise Thomson,Karl Weilhammer,Hui Ye,Steve J. Young

North American Chapter of the Association for Computational Linguistics (NAACL)（2007）CCF C

Cambridge University

被引用509|浏览16

摘要

This paper investigates the problem of bootstrapping a statistical dialogue manager without access to training data and proposes a new probabilistic agenda-based method for simulating user behaviour. In experiments with a statistical POMDP dialogue system, the simulator was realistic enough to successfully test the prototype system and train a dialogue policy. An extensive study with human subjects showed that the learned policy was highly competitive, with task completion rates above 90%.

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关键词

dialogue policy,statistical POMDP dialogue system,statistical dialogue manager,prototype system,extensive study,human subject,new probabilistic agenda-based method,simulating user behaviour,task completion rate,training data,Agenda-based user simulation

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