Dialogue state tracking (DST) is a process to estimate the distribution of
the dialogue states as a dialogue progresses. Recent studies on constrained
Markov Bayesian polynomial (CMBP) framework take the first step towards
bridging the gap between rule-based and statistical approaches for DST...
paper, the gap is further bridged by a novel framework -- recurrent polynomial
network (RPN). RPN's unique structure enables the framework to have all the
advantages of CMBP including efficiency, portability and interpretability. Additionally, RPN achieves more properties of statistical approaches than CMBP. RPN was evaluated on the data corpora of the second and the third Dialog State
Tracking Challenge (DSTC-2/3). Experiments showed that RPN can significantly
outperform both traditional rule-based approaches and statistical approaches
with similar feature set. Compared with the state-of-the-art statistical DST
approaches with a lot richer features, RPN is also competitive.