Investigating Variable Dependencies in Dialogue States

Authors

Anh Duong Trinh, Technological University DublinFollow
Robert J. Ross, Technological University DublinFollow
John D. Kelleher, Technological University DublinFollow

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences

Publication Details

The 23rd Workshop on the Semantics and Pragmatics of Dialogue, SEMDIAL 2019

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.

DOI

https://doi.org/10.21427/1csd-yv51

Recommended Citation

Trinh, A, & Ross, R.J. & Kelleher, J.D. (2019). Investigating Variable Dependencies in Dialogue States,The 23rd Workshop on the Semantics and Pragmatics of Dialogue, SEMDIAL 2019, London, September 4-6th, 2019. doi:10.21427/1csd-yv51

Funder

Science Foundation Ireland, European Regional Development Fund (ERDF)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.