Modeling behavior patterns with an unfamiliar voice user interface

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Abstract

Voice User Interfaces (VUIs) are becoming increasingly popular. However, how VUIs can adapt to user differences remains insufficiently understood. We analyze usage data from a user study (n=50) where participants interacted with an unfamiliar VUI. Through automated clustering and statistical analysis, we present user models of their behavior patterns. We found user behavior can be grouped into three clusters: people who become proficient with the system and typically stay proficient while completing different tasks, people who exhibit an exploratory approach to completing tasks, and people who struggled to complete tasks. We discuss design implications based on these behavior clusters.

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APA

Myers, C. M., Grethlein, D., Furqan, A., Ontañón, S., & Zhu, J. (2019). Modeling behavior patterns with an unfamiliar voice user interface. In ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (pp. 196–200). Association for Computing Machinery, Inc. https://doi.org/10.1145/3320435.3320475

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