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Hybrid Dialog State Tracker
October 13, 2015 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Miroslav Vodolรกn, Rudolf Kadlec, Jan Kleindienst
arXiv ID
1510.03710
Category
cs.CL: Computation & Language
Citations
9
Venue
arXiv.org
Last Checked
5 months ago
Abstract
This paper presents a hybrid dialog state tracker that combines a rule based and a machine learning based approach to belief state tracking. Therefore, we call it a hybrid tracker. The machine learning in our tracker is realized by a Long Short Term Memory (LSTM) network. To our knowledge, our hybrid tracker sets a new state-of-the-art result for the Dialog State Tracking Challenge (DSTC) 2 dataset when the system uses only live SLU as its input.
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