Semi-automated dialogue act classification for situated social agents in games

As a step toward simulating dynamic dialogue between agents and humans in virtual environments, we describe learning a model of social behavior composed of interleaved utterances and physical actions. In our model, utterances are abstracted as {speech act, propositional content, referent} triples. A...

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Main Authors: Orkin, Jeffrey David, Roy, Deb K.
Other Authors: Massachusetts Institute of Technology. Media Laboratory
Format: Article
Language:en_US
Published: Springer Berlin / Heidelberg 2011
Online Access:http://hdl.handle.net/1721.1/66125
https://orcid.org/0000-0002-4333-7194
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author Orkin, Jeffrey David
Roy, Deb K.
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Orkin, Jeffrey David
Roy, Deb K.
author_sort Orkin, Jeffrey David
collection MIT
description As a step toward simulating dynamic dialogue between agents and humans in virtual environments, we describe learning a model of social behavior composed of interleaved utterances and physical actions. In our model, utterances are abstracted as {speech act, propositional content, referent} triples. After training a classifier on 100 gameplay logs from The Restaurant Game annotated with dialogue act triples, we have automatically classified utterances in an additional 5,000 logs. A quantitative evaluation of statistical models learned from the gameplay logs demonstrates that semi-automatically classified dialogue acts yield significantly more predictive power than automatically clustered utterances, and serve as a better common currency for modeling interleaved actions and utterances.
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spelling mit-1721.1/661252022-09-28T11:32:41Z Semi-automated dialogue act classification for situated social agents in games Orkin, Jeffrey David Roy, Deb K. Massachusetts Institute of Technology. Media Laboratory Roy, Deb K. Orkin, Jeffrey David Roy, Deb K. As a step toward simulating dynamic dialogue between agents and humans in virtual environments, we describe learning a model of social behavior composed of interleaved utterances and physical actions. In our model, utterances are abstracted as {speech act, propositional content, referent} triples. After training a classifier on 100 gameplay logs from The Restaurant Game annotated with dialogue act triples, we have automatically classified utterances in an additional 5,000 logs. A quantitative evaluation of statistical models learned from the gameplay logs demonstrates that semi-automatically classified dialogue acts yield significantly more predictive power than automatically clustered utterances, and serve as a better common currency for modeling interleaved actions and utterances. 2011-09-30T12:33:29Z 2011-09-30T12:33:29Z 2011-01 Article http://purl.org/eprint/type/ConferencePaper 978-3-642-18180-1 http://hdl.handle.net/1721.1/66125 Orkin, Jeff, and Deb Roy. “Semi-Automated Dialogue Act Classification for Situated Social Agents in Games.” Agents for Games and Simulations II. Ed. Frank Dignum. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. 148-162. https://orcid.org/0000-0002-4333-7194 en_US http://dx.doi.org/10.1007/978-3-642-18181-8_11 Agents for Games and Simulations II: Trends in Techniques, Concepts and Design Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Springer Berlin / Heidelberg MIT web domain
spellingShingle Orkin, Jeffrey David
Roy, Deb K.
Semi-automated dialogue act classification for situated social agents in games
title Semi-automated dialogue act classification for situated social agents in games
title_full Semi-automated dialogue act classification for situated social agents in games
title_fullStr Semi-automated dialogue act classification for situated social agents in games
title_full_unstemmed Semi-automated dialogue act classification for situated social agents in games
title_short Semi-automated dialogue act classification for situated social agents in games
title_sort semi automated dialogue act classification for situated social agents in games
url http://hdl.handle.net/1721.1/66125
https://orcid.org/0000-0002-4333-7194
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