DocumentCode
3585049
Title
A generalized rule based tracker for dialogue state tracking
Author
Kai Sun ; Lu Chen ; Su Zhu ; Kai Yu
Author_Institution
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2014
Firstpage
330
Lastpage
335
Abstract
Dialogue state tracking plays an important role in statistical dialogue management. Domain-independent rule-based approaches are attractive due to their efficiency, portability and interpretability. However, recent rule-based models are still not quite competitive to statistical tracking approaches. In this paper, a novel framework is proposed to formulate rule-based models in a general way. In the framework, a rule is considered as a special kind of polynomial function satisfying certain linear constraints. Under some particular definitions and assumptions, rule-based models can be seen as feasible solutions of an integer linear programming problem. Experiments showed that the proposed approach can not only achieve competitive performance compared to statistical approaches, but also have good generalisation ability. It is one of the only two entries that outperformed all the four baselines in the third Dialog State Tracking Challenge.
Keywords
integer programming; interactive systems; knowledge based systems; linear programming; polynomials; statistical analysis; dialogue state tracking; domain-independent rule-based approach; generalized rule based tracker; integer linear programming problem; linear constraints; polynomial function; statistical dialogue management; Accuracy; Bayes methods; Data models; Joints; Markov processes; Polynomials; Speech recognition; Dialogue management; Dialogue state tracking; Rule-based model;
fLanguage
English
Publisher
ieee
Conference_Titel
Spoken Language Technology Workshop (SLT), 2014 IEEE
Type
conf
DOI
10.1109/SLT.2014.7078596
Filename
7078596
Link To Document