Different Types of Voice User Interface Failures May Cause Different Degrees of Frustration
Not on the map. Why?
Abstract (arXiv)
We report on an investigation into how different types of failures in a voice user interface (VUI) affects user frustration. To this end, we conducted a pilot user study (n=10) and a main user study (n=30), both with a simple voice-operated calendar application that we built using the Alexa Skills Kit. In our pilot study, we identified three major failure types as perceived by the users, namely, Reason Unknown, Speech Misrecognition, and Utterance Pattern Match Failure, along with more fine-grained failure types from the developer's viewpoint such as Intent Pattern Match Failure and Intent Misclassification. Then, in our main study, we set up three user tasks that were designed to each induce a specific failure type, and collected user frustration ratings for each task. Our main findings are: (a)Users may be relatively tolerant to user-perceived Speech Misrecognition, and not so to user-perceived Reason Unknown and Utterance Mattern Match Failures; (b)Regarding the relationship between developer-perceived and user-perceived failure types, 68.8% of developer-perceived Intent Misclassification instances caused user-perceived Reason Unkown failures. From (a) and (b), a practical design implication would be to try to prevent Intent Misclassification from happening by carefully crafting the utterance patterns for each intent.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). First posted on arXiv 10 Feb 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 1; 2026: 2.
4 papers.
- 2024"Stupid robot, I want to speak to a human!" User Frustration Detection in Task-Oriented Dialog Systemscited by 1
- 2025A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistantscited by 1
- 2026Unheard in the Digital Age: Rethinking AI Bias and Speech Diversitycited by 0
- 2026Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision Peoplecited by 0
- 2026Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision People10 Mar 2026
- 2026Unheard in the Digital Age: Rethinking AI Bias and Speech Diversity26 Jan 2026
- 2025A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants31 Aug 2025
- 2024"Stupid robot, I want to speak to a human!" User Frustration Detection in Task-Oriented Dialog Systems26 Nov 2024