# A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures

arXiv: https://arxiv.org/abs/2303.00164 · HTML: https://mlsanity.com/paper/2303.00164/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2023.

## Built on by (most cited first, 11 of 11)

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- [AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure](https://mlsanity.com/paper/2409.17642/) (2024)
- [LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBot](https://mlsanity.com/paper/2406.10590/) (2024)
- [A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants](https://mlsanity.com/paper/2510.06223/) (2025)
- [TurnNat: Automatic Evaluation of Turn-Taking Naturalness in Dyadic Spoken Dialogue](https://mlsanity.com/paper/2607.01345/) (2026)
- [Mapping the Trust Terrain: LLMs in Software Engineering -- Insights and Perspectives](https://mlsanity.com/paper/2503.13793/) (2025)
- [Unheard in the Digital Age: Rethinking AI Bias and Speech Diversity](https://mlsanity.com/paper/2601.18641/) (2026)
- [Beyond Naturalness: Probing Automated Text-To-Speech Evaluators on Linguistically Grounded Dimensions](https://mlsanity.com/paper/2608.09930/) (2026)

## Abstract (arXiv)

Despite huge gains in performance in natural language understanding via large language models in recent years, voice assistants still often fail to meet user expectations. In this study, we conducted a mixed-methods analysis of how voice assistant failures affect users' trust in their voice assistants. To illustrate how users have experienced these failures, we contribute a crowdsourced dataset of 199 voice assistant failures, categorized across 12 failure sources. Relying on interview and survey data, we find that certain failures, such as those due to overcapturing users' input, derail user trust more than others. We additionally examine how failures impact users' willingness to rely on voice assistants for future tasks. Users often stop using their voice assistants for specific tasks that result in failures for a short period of time before resuming similar usage. We demonstrate the importance of low stakes tasks, such as playing music, towards building trust after failures.