Reference : Interaction Profiles for an Artificial Conversational Companion

	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/21983

Title :	Interaction Profiles for an Artificial Conversational Companion
Language :	English
Author, co-author :	Höhn, Sviatlana [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Busemann, Stephan [Deutsches Forschungszentrum für Künstliche Intelligenz GmbH > Language Technology Lab]
	Max, Charles [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Education, Culture, Cognition and Society (ECCS) >]
	Schommer, Christoph [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Ziegler, Gudrun [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Languages, Culture, Media and Identities (LCMI) >]
Publication date :	Sep-2015
Peer reviewed :	Yes
Audience :	International
Event name :	International Symposium on Companion Technology
Event date :	23-25. September 2015
Event place (city) :	Ulm
Event country :	Germany
Keywords :	[en] artificial companions ; interaction profiles ; foreign language practice ; conversation analysis ; instant messaging ; German
Abstract :	[en] Using Artificial Companions for tasks requiring long-term interaction like language learning or coaching can be approached by creating local computational models for particular interaction structures, and models reflecting changes in interaction over time. An Artificial Conversational Companion (ACC) that helps to practice conversation in a foreign language is expected to play the role of a language expert in conversation. We apply methods of Conversation Analysis to obtain data- driven models of interaction profiles for language experts and language novices from a corpus of instant messaging based dialogues between native speakers of German and advanced learners of German as a foreign language. We show different ways how the artificial agent can simulate ”doing being expert” in conversation and promote learning.
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/21983
Other URL :	http://isct2015.informatik.uni-ulm.de/#NaN

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