Building Proactive Voice Assistants: When and How (not) to Interact
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Abstract (arXiv)
Voice assistants have recently achieved remarkable commercial success. However, the current generation of these devices is typically capable of only reactive interactions. In other words, interactions have to be initiated by the user, which somewhat limits their usability and user experience. We propose, that the next generation of such devices should be able to proactively provide the right information in the right way at the right time, without being prompted by the user. However, achieving this is not straightforward, since there is the danger it could interrupt what the user is doing too much, resulting in it being distracting or even annoying. Furthermore, it could unwittingly, reveal sensitive/private information to third parties. In this report, we discuss the challenges of developing proactively initiated interactions, and suggest a framework for when it is appropriate for the device to intervene. To validate our design assumptions, we describe firstly, how we built a functioning prototype and secondly, a user study that was conducted to assess users' reactions and reflections when in the presence of a proactive voice assistant. This pre-print summarises the state, ideas and progress towards a proactive device as of autumn 2018.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2020.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 2; 2026: 1.
7 papers.
- 2024Towards Human-centered Proactive Conversational Agentscited by 48
- 2024Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User Modelingcited by 24
- 2025LLAMAPIE: Proactive In-Ear Conversation Assistantscited by 8
- 2024Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmapcited by 6
- 2025Chronocept: Instilling a Sense of Time in Machinescited by 3
- 2023Distilling Multi-Level X-vector Knowledge for Small-footprint Speaker Verificationcited by 0
- 2026LLMs are General Asynchronous Agentscited by 0
- 2026LLMs are General Asynchronous Agents28 Sep 2026
- 2025Chronocept: Instilling a Sense of Time in Machines12 May 2025
- 2025LLAMAPIE: Proactive In-Ear Conversation Assistants7 May 2025
- 2024Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User Modeling22 Oct 2024
- 2024Towards Human-centered Proactive Conversational Agents19 Apr 2024
- 2024Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap19 Mar 2024
- 2023Distilling Multi-Level X-vector Knowledge for Small-footprint Speaker Verification2 Mar 2023