HCFeb 26, 2021

Eliciting and Analysing Users' Envisioned Dialogues with Perfect Voice Assistants

arXiv:2102.13508v289 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of designing more conversational voice assistants for users, though it is incremental as it builds on existing research by eliciting user visions.

The study investigated how users imagine ideal conversations with voice assistants through an online survey with 205 participants, finding that most envisioned dialogues that are interactive, smart, and proactive, with attitudes varying on aspects like humor and opinions.

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".

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