Information Navigation System Based on POMDP that Tracks User Focus

Abstract

We present a spoken dialogue system for navigating information (such as news articles), and which can engage in small talk. At the core is a partially observable Markov decision process (POMDP), which tracks user’s state and focus of attention. The input to the POMDP is provided by a spoken language understanding (SLU) component implemented with logistic regression (LR) and conditional random fields (CRFs). The POMDP selects one of six action classes; each action class is implemented with its own module.