  The dependencies between system and user utterances in the same turn and
across different turns are not fully considered in existing multidomain
dialogue state tracking (MDST) models. In this study, we argue that the
incorporation of these dependencies is crucial for the design of MDST and
propose Parallel Interactive Networks (PIN) to model these dependencies.
Specifically, we integrate an interactive encoder to jointly model the in-turn
dependencies and cross-turn dependencies. The slot-level context is introduced
to extract more expressive features for different slots. And a distributed copy
mechanism is utilized to selectively copy words from historical system
utterances or historical user utterances. Empirical studies demonstrated the
superiority of the proposed PIN model.
