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Eliciting and Analysing Users' Envisioned Dialogues with Perfect Voice Assistants

Title data

Völkel, Sarah Theres ; Buschek, Daniel ; Eiband, Malin ; Cowan, Benjamin R. ; Hussmann, Heinrich:
Eliciting and Analysing Users' Envisioned Dialogues with Perfect Voice Assistants.
2021
Event: CHI Conference on Human Factors in Computing Systems , 08.05.2021 - 13.05.2021 , online (originally: Yokohama, Japan).
(Conference item: Conference , Paper )
DOI: https://doi.org/10.1145/3411764.3445536

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Project information

Project title:
Project's official title
Project's id
AI Tools - Continuous Interaction with Computational Intelligence Tools
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Abstract in another language

We present a dialogue elicitation study to assess how users envision conversations with a perfect voice assistant (VA). In an online survey, N=205 participants were prompted with everyday scenarios, and wrote the lines of both user and VA in dialogues that they imagined as perfect. We analysed the dialogues with text analytics and qualitative analysis, including number of words and turns, social aspects of conversation, implied VA capabilities, and the influence of user personality. The majority envisioned dialogues with a VA that is interactive and not purely functional; it is smart, proactive, and has knowledge about the user. Attitudes diverged regarding the assistant's role as well as it expressing humour and opinions. An exploratory analysis suggested a relationship with personality for these aspects, but correlations were low overall. We discuss implications for research and design of future VAs, underlining the vision of enabling conversational UIs, rather than single command "Q&As".

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: Adaptation; conversational agent; dialogue; personality; voice assistant
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 06 Apr 2021 11:59
Last Modified: 06 Apr 2021 11:59
URI: https://eref.uni-bayreuth.de/id/eprint/64580