Information Navigation System Based on POMDP that Tracks User Focus
Koichiro Yoshino, Tatsuya Kawahara · 2014
We present a spoken dialogue system for navigating information (such as news ar-ticles), and which can engage in small talk. At the core is a partially observ-able Markov decision process (POMDP), which tracks user’s state and focus of at-tention. The input to the POMDP is pro-vided by a spoken language understanding (SLU) component implemented with lo-gistic regression (LR) and conditional ran-dom fields (CRFs). The POMDP selects one of six action classes; each action class is implemented with its own module. 1