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Recent Neural Methods on Dialogue State Tracking for Task-Oriented Dialogue Systems: A Survey
2021
SIGDIAL Conferences
This paper aims at providing a comprehensive overview of recent developments in dialogue state tracking (DST) for task-oriented conversational systems. We introduce the task, the main datasets that have been exploited as well as their evaluation metrics, and we analyze several proposed approaches. We distinguish between static ontology DST models, which predict a fixed set of dialogue states, and dynamic ontology models, which can predict dialogue states even when the ontology changes. We also
dblp:conf/sigdial/BalaramanSM21
fatcat:djuzylluxjddzhraj3wsbli5s4