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Comparing real-real, simulated-simulated, and simulated-real spoken dialogue corpora

Ai, H and Litman, D (2006) Comparing real-real, simulated-simulated, and simulated-real spoken dialogue corpora. In: UNSPECIFIED.

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Abstract

User simulation is used to generate large corpora for using reinforcement learning to automatically learn the best policy for spoken dialogue systems. Although this approach is becoming increasingly popular, the differences between simulated and real corpora are not well studied. We build two simulation models to interact with an intelligent tutoring system. Both models are trained on two different real corpora separately. We use several evaluation measures proposed in previous research to compare between our two simulated corpora, between the original two real corpora, and between the simulated and real corpora. We next examine the differentiating power of these measures. Our results show that although these simple statistical measures can distinguish real corpora from simulated ones, these measures cannot help us to draw a conclusion on the "reality" of the simulated corpora since even two real corpora can be very different when evaluated on the same measures. copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ai, H
Litman, Ddlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 1 December 2006
Date Type: Publication
Journal or Publication Title: AAAI Workshop - Technical Report
Volume: WS-06-
Page Range: 1 - 6
Event Type: Conference
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
ISBN: 1577352963, 9781577352969
Related URLs:
Date Deposited: 10 Oct 2014 18:01
Last Modified: 02 May 2019 13:59
URI: http://d-scholarship.pitt.edu/id/eprint/23213

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