Engineering statistical dialog state trackers: A case study on DSTC

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 47
  • Download : 0
We describe our experience with engineering the dialog state tracker for the first Dialog State Tracking Challenge (DSTC). Dialog trackers are one of the essential components of dialog systems which are used to infer the true user goal from the speech processing results. We explain the main parts of our tracker: the observation model, the belief refinement model, and the belief transformation model. We also report experimental results on a number of approaches to the models, and compare the overall performance of our tracker to other submitted trackers. An extended version of this paper is available as a technical report (Kim et al., 2013).
Publisher
Association for Computational Linguistics (ACL)
Issue Date
2013-08
Language
English
Citation

14th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2013, pp.462 - 466

URI
http://hdl.handle.net/10203/313458
Appears in Collection
AI-Conference Papers(학술대회논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0