Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Comparing the utility of state features in spoken dialogue using reinforcement learning

Tetreault, JR and Litman, DJ (2006) Comparing the utility of state features in spoken dialogue using reinforcement learning. In: UNSPECIFIED.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


Recent work in designing spoken dialogue systems has focused on using Reinforcement Learning to automatically learn the best action for a system to take at any point in the dialogue to maximize dialogue success. While policy development is very important, choosing the best features to model the user state is equally important since it impacts the actions a system should make. In this paper, we compare the relative utility of adding three features to a model of user state in the domain of a spoken dialogue tutoring system. In addition, we also look at the effects of these features on what type of a question a tutoring system should ask at any state and compare it with our previous work on using feedback as the system action. © 2006 Association for Computational Linguistics.


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Tetreault, JR
Litman, DJdlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 1 January 2006
Date Type: Publication
Journal or Publication Title: HLT-NAACL 2006 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings of the Main Conference
Page Range: 272 - 279
Event Type: Conference
DOI or Unique Handle: 10.3115/1220835.1220870
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
Date Deposited: 05 Jan 2015 15:28
Last Modified: 19 Jul 2020 11:56


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item