# Eliciting and Analysing Users' Envisioned Dialogues with Perfect Voice Assistants

arXiv: https://arxiv.org/abs/2102.13508 · HTML: https://mlsanity.com/paper/2102.13508/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2021.

## Built on by (most cited first, 9 of 9)

- [CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models](https://mlsanity.com/paper/2402.15265/) (2024)
- [Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts](https://mlsanity.com/paper/2304.12810/) (2023)
- [Rewriting the Script: Adapting Text Instructions for Voice Interaction](https://mlsanity.com/paper/2306.09992/) (2023)
- [Coimagining the Future of Voice Assistants with Cultural Sensitivity](https://mlsanity.com/paper/2403.17599/) (2024)
- [Not My Truce: Personality Differences in AI-Mediated Workplace Negotiation](https://mlsanity.com/paper/2604.00464/) (2026)
- [Digital Modeling for Everyone: Exploring How Novices Approach Voice-Based 3D Modeling](https://mlsanity.com/paper/2307.04481/) (2023)
- [LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBot](https://mlsanity.com/paper/2406.10590/) (2024)
- [StepWrite: Adaptive Planning for Speech-Driven Text Generation](https://mlsanity.com/paper/2508.04011/) (2025)
- [Situated, Dynamic, and Subjective: Envisioning the Design of Theory-of-Mind-Enabled Everyday AI with Industry Practitioners](https://mlsanity.com/paper/2602.11342/) (2026)

## Abstract (arXiv)

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".