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Using Learned Predictions of User Utterances to Decrease Distraction
Talkamatic AB.
Talkamatic AB.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).ORCID iD: 0000-0002-2791-6647
2013 (English)In: Proceedings of the 17th Workshop on the Semantics and Pragmatics of the Dialogue / [ed] Raquel Fernandez and Amy Isard, Amsterdam, 2013, 210-212 p.Conference paper (Refereed)
Abstract [en]

Driver distraction is one of the most com- mon causes of accidents. By having a di- alogue manager request predicted user an- swers from a user model instead of ask- ing the user, we can reduce the number of utterances in the dialogue and thereby re- duce the time that the user is distracted. 

Place, publisher, year, edition, pages
Amsterdam, 2013. 210-212 p.
Series
Proceedings (SemDial), ISSN 2308-2275
National Category
Computer Systems Interaction Technologies
Identifiers
URN: urn:nbn:se:hh:diva-24199OAI: oai:DiVA.org:hh-24199DiVA: diva2:680892
Conference
the 17th Workshop on the Semantics and Pragmatics of Dialogue, SemDial 2013, Amsterdam, 16-18 December
Projects
SafeSpeech for Knowledge
Funder
Vinnova
Available from: 2013-12-18 Created: 2013-12-18 Last updated: 2014-03-18Bibliographically approved

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Proceedings of SemDial 2013

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Total: 74 hits
CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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