201. Investigating Variable Dependencies in Dialogue States
- Author
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Trinh, Anh Duong, Ross, Robert J., Kelleher, John D., Science Foundation Ireland, European Regional Development Fund (ERDF), and SFI Research Centres Programme
- Subjects
dialogue state ,Artificial Intelligence and Robotics ,spoken dialogue system ,dialogue state tracking ,variable dependencies - Abstract
Dialogue State Tracking is arguably one of the most challenging tasks among dialogue processing problems due to the uncertainties of language and complexity of dialogue contexts. We argue that this problem is made more challenging by variable dependencies in the dialogue states that must be accounted for in processing. In this paper we give details on our motivation for this argument through statistical tests on a number of dialogue datasets. We also propose a machine learning-based approach called energy-based learning that tackles variable dependencies while performing prediction on the dialogue state tracking tasks.
- Published
- 2019
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