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Steering the conversation: a linguistic exploration of natural language interactions with a digital assistant during simulated driving

Large, David R.; Clark, Leigh; Quandt, Annie; Burnett, Gary; Skrychuk, Lee

Authors

DAVID LARGE David.R.Large@nottingham.ac.uk
Senior Research Fellow

Leigh Clark

Annie Quandt

GARY BURNETT GARY.BURNETT@NOTTINGHAM.AC.UK
Professor of Transport Human Factors

Lee Skrychuk



Abstract

Given the proliferation of ‘intelligent’ and ‘socially-aware’ digital assistants embodying everyday mobile technology – and the undeniable logic that utilising voice-activated controls and interfaces in cars reduces the visual and manual distraction of interacting with in-vehicle devices – it appears inevitable that next generation vehicles will be embodied by digital assistants and utilise spoken language as a method of interaction. From a design perspective, defining the language and interaction style that a digital driving assistant should adopt is contingent on the role that they play within the social fabric and context in which they are situated. We therefore conducted a qualitative, Wizard-of-Oz study to explore how drivers might interact linguistically with a natural language digital driving assistant. Twenty-five participants drove for 10 min in a medium-fidelity driving simulator while interacting with a state-of-the-art, high-functioning, conversational digital driving assistant. All exchanges were transcribed and analysed using recognised linguistic techniques, such as discourse and conversation analysis, normally reserved for interpersonal investigation. Language usage patterns demonstrate that interactions with the digital assistant were fundamentally social in nature, with participants affording the assistant equal social status and high-level cognitive processing capability. For example, participants were polite, actively controlled turn-taking during the conversation, and used back-channelling, fillers and hesitation, as they might in human communication. Furthermore, participants expected the digital assistant to understand and process complex requests mitigated with hedging words and expressions, and peppered with vague language and deictic references requiring shared contextual information and mutual understanding. Findings are presented in six themes which emerged during the analysis – formulating responses; turn-taking; back-channelling, fillers and hesitation; vague language; mitigating requests and politeness and praise. The results can be used to inform the design of future in-vehicle natural language systems, in particular to help manage the tension between designing for an engaging dialogue (important for technology acceptance) and designing for an effective dialogue (important to minimise distraction in a driving context).

Citation

Large, D. R., Clark, L., Quandt, A., Burnett, G., & Skrychuk, L. (in press). Steering the conversation: a linguistic exploration of natural language interactions with a digital assistant during simulated driving. Applied Ergonomics, 63, https://doi.org/10.1016/j.apergo.2017.04.003

Journal Article Type Article
Acceptance Date Apr 4, 2017
Online Publication Date Apr 12, 2017
Deposit Date Apr 7, 2017
Publicly Available Date Apr 12, 2017
Journal Applied Ergonomics
Print ISSN 0003-6870
Electronic ISSN 1872-9126
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 63
DOI https://doi.org/10.1016/j.apergo.2017.04.003
Keywords natural language interface, digital assistant, social Als, driving, simulation, Wizard-of-Oz
Public URL http://eprints.nottingham.ac.uk/id/eprint/41814
Publisher URL http://www.sciencedirect.com/science/article/pii/S0003687017300790
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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