Conference proceeding
Modeling Behavior Patterns with an Unfamiliar Voice User Interface
ACM UMAP '19: PROCEEDINGS OF THE 27TH ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION
01 Jan 2019
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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Details
- Title
- Modeling Behavior Patterns with an Unfamiliar Voice User Interface
- Creators
- Chelsea M. Myers - Drexel UniversityDavid Grethlein - Drexel UniversityAnushay Furcian - Drexel Univ, Philadelphia, PA 19104 USASantiago Ontanon - Drexel UniversityJichen Zhu - Drexel UniversityAssoc Comp Machinery
- Publication Details
- ACM UMAP '19: PROCEEDINGS OF THE 27TH ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION
- Conference
- ACM UMAP '19: 27TH ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION, 27th
- Publisher
- Assoc Computing Machinery
- Number of pages
- 5
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Digital Media; Computer Science
- Web of Science ID
- WOS:000482185300028
- Scopus ID
- 2-s2.0-85068052044
- Other Identifier
- 991019167771904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Theory & Methods