The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index.
Talk to me: Exploring user interactions with the Amazon Alexa
Abstract
Amazon Alexa is a voice-controlled application that is rapidly gaining popularity. We examined user interactions with this technology, and focused on the types of tasks requested of Alexa, the variables that affect user behaviors with Alexa, and Alexa’s alternatives. The data about Alexa usage were collected from 19 participants via the online questionnaire and diary methods over the course of several days. The results indicate that across all age groups, Alexa was primarily used for checking weather forecasts, playing music, and controlling other devices. Several participants reported using Apple Siri and Google Now applications in addition to Alexa for similar purposes except for controlling other devices. Alexa uses over the weekends were more frequent than on weekdays, but its overall usage tended to decrease over time. The users reported being satisfied with Alexa even when it did not produce sought information, suggesting that the interaction experience is more important to the users than the interaction output. More work is required to understand whether users treat Alexa and similar voice-controlled applications as primarily a traditional information retrieval system, a casual leisure system, a control interface for smart home devices, or, simply, a new toy.
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“Research on voice assistants is focused mainly on the general population.”
From Investigating the Accessibility of Voice Assistants With Impaired Users: Mixed Methods Study (2020) · cites this paper as [10]
In the citing paper
“Indeed, the studies investigating user experience and usability of voice assistants mainly involved able-bodied users [3,8-11], thereby neglecting a broad community of users with disabilities.”
From Investigating the Accessibility of Voice Assistants With Impaired Users: Mixed Methods Study (2020) · cites this paper as [10]
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Metadata
- Authors
- Lopatovska, I., Rink, K., Knight, I., Raines, K., Cosenza, K., Williams, H., Sorsche, P., Hirsch, D., Li, Q., & Martinez, A.
- Affiliations
- Pratt Institute (US)
- Corresponding author
- Lopatovska, Irene
- Venue
- Journal of Librarianship and Information Science
- Publisher
- SAGE Publications
- Published
- 2018-03-07
- Volume
- 51
- Issue
- 4
- Pages
- 984-997
- ISSN
- 0022-2232 (ISSN-L)
- 0961-0006
- 1741-6477
- OpenAlex
- W2794297522
- Cited by
- 298
- References
- 29
- Citations by year
- 2026: 23 · 2025: 20 · 2024: 36 · 2023: 50 · 2022: 44 · 2021: 59 · 2020: 34 · 2019: 26 · 2018: 6
- FWCI
- 17.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Librarianship and Information Science (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- Amazon Alexa, voice assistants, user interaction, task type, user satisfaction, weather forecasting, music playback, Siri, usage patterns, age differences, information retrieval systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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