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- 592 creator oliver-lemon.
- 592 creator verena-rieser.
- 592 type InProceedings.
- 592 label "Automatic Learning and Evaluation of User-Centered Objective Functions for Dialogue System Optimisation".
- 592 sameAs 592.
- 592 abstract "The ultimate goal when building dialogue systems is to satisfy the needs of real users, but quality assurance for dialogue strategies is a non-trivial problem. The applied evaluation metrics and resulting design principles are often obscure, emerge by trial-and-error, and are highly context dependent. This paper introduces data-driven methods for obtaining reliable objective functions for system design. In particular, we test whether an objective function obtained from Wizard-of-Oz (WOZ) data is a valid estimate of real users preferences. We test this in a test-retest comparison between the model obtained from the WOZ study and the models obtained when testing with real users. We can show that, despite a low fit to the initial data, the objective function obtained from WOZ data makes accurate predictions for automatic dialogue evaluation, and, when automatically optimising a policy using these predictions, the improvement over a strategy simply mimicking the data becomes clear from an error analysis.".
- 592 hasAuthorList authorList.
- 592 hasTopic Linguistics.
- 592 isPartOf proceedings.
- 592 keyword "Acquisition, Machine Learning".
- 592 keyword "Dialogue & Natural Interactivity".
- 592 keyword "Usability, user satisfaction".
- 592 title "Automatic Learning and Evaluation of User-Centered Objective Functions for Dialogue System Optimisation".