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Title: Do (and say) as I say: Linguistic adaptation in human-computer dialogs
Authors: Kolouri, T
Lauria, S
Macredie, R
Keywords: Dialog systems;Vocabulary;Sentence structure;Computer systems;Communication
Issue Date: 2014
Publisher: Taylor & Francis
Citation: Human-Computer Interaction, accepted for publication
Abstract: There is strong research evidence showing that people naturally align to each other’s vocabulary, sentence structure and acoustic features in dialogue, yet little is known about how the alignment mechanism operates in the interaction between users and computer systems let alone how it may be exploited to improve the efficiency of the interaction. This paper provides an account of lexical alignment in human-computer dialogues, based on empirical data collected in a simulated human-computer interaction scenario. The results indicate that alignment is present, resulting in the gradual reduction and stabilisation of the vocabulary-in-use, and that it is also reciprocal. Further, the results suggest that when system and user errors occur, the development of alignment is temporarily disrupted and users tend to introduce novel words to the dialogue. The results also indicate that alignment in human-computer interaction may have a strong strategic component, and is used as a resource to compensate for less optimal (visually impoverished) interaction conditions. Moreover, lower alignment is associated with less successful interaction, as measured by user perceptions. The paper distils the results of the study into design recommendations for human-computer dialogue systems and uses them to inform a model of dialogue management that supports and exploits alignment through mechanisms for in-use adaptation of the system’s grammar and lexicon.
Description: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Human-Computer Interaction on 18/06/2014, which is available online through open access at the link below:
This article has been made available through the Brunel Open Access Publishing Fund.
ISSN: 0737-0024
Appears in Collections:Computer Science
Brunel OA Publishing Fund
Dept of Computer Science Research Papers

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