Planning and acting in partially observable stochastic domains
Artificial Intelligence
Natural Language Engineering
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
Computer Speech and Language
Persistent information state in a data-centric architecture
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
System Personality and Persuasion in Human-Computer Dialogue
ACM Transactions on Interactive Intelligent Systems (TiiS)
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We investigate the clarification strategies exhibited by a hybrid POMDP dialog manager based on data obtained from a phone-based user study. The dialog manager combines task structures with a number of POMDP policies each optimized for obtaining an individual concept. We investigate the relationship between dialog length and task completion. In order to measure the effectiveness of the clarification strategies, we compute concept precisions for two different mentions of the concept in the dialog: first mentions and final values after clarifications and similar strategies, and compare this to a rule-based system on the same task. We observe an improvement in concept precision of 12.1% for the hybrid POMDP compared to 5.2% for the rule-based system.