Information Navigation System Based on POMDP that Tracks User Focus
| Koichiro Yoshino and Tatsuya Kawahara |
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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.
