A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
A Two-Step Neural Dialog State Tracker for Task-Oriented Dialog Processing
2018
Computational Intelligence and Neuroscience
Dialog state tracking in a spoken dialog system is the task that tracks the flow of a dialog and identifies accurately what a user wants from the utterance. Since the success of a dialog is influenced by the ability of the system to catch the requirements of the user, accurate state tracking is important for spoken dialog systems. This paper proposes a two-step neural dialog state tracker which is composed of an informativeness classifier and a neural tracker. The informativeness classifier
doi:10.1155/2018/5798684
pmid:30420875
pmcid:PMC6211208
dblp:journals/cin/KimSP18
fatcat:jwcuiagnvfbb3owsybuiaprh4i