Dialog State Tracking using Conditional Random Fields

This paper presents our approach to dialog state tracking for the Dialog State Tracking Challenge task. In our approach we use discriminative general structured conditional random fields, instead of traditional generative directed graphic models, to incorporate arbitrary overlapping features. Our approach outperforms the simple 1-best tracking approach.