POMDP-based Let's Go system for spoken dialog challenge

Abstract

This paper describes a POMDP-based Let's Go system which incorporates belief tracking and dialog policy optimization into the dialog manager of the reference system for the Spoken Dialog Challenge (SDC). Since all components except for the dialog manager were kept the same, component-wise comparison can be performed to investigate the effect of belief tracking and dialog policy optimization on the overall system performance. In addition, since unsupervised methods have been adopted to learn all required models to reduce human labor and development time, the effectiveness of the unsupervised approaches compared to conventional supervised approaches can be investigated. The result system participated in the 2011 SDC and showed comparable performance with the base system which has been enhanced from the reference system for the 2010 SDC. This shows the capability of the proposed method to rapidly produce an effective system with minimal human labor and experts' knowledge.