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Computer Science > Human-Computer Interaction

arXiv:2412.05445 (cs)
[Submitted on 6 Dec 2024 (v1), last revised 10 Dec 2024 (this version, v2)]

Title:From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go

Authors:Kavindu Ravishan, Dániel Szabó, Niels van Berkel, Aku Visuri, Chi-Lan Yang, Koji Yatani, Simo Hosio
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Abstract:Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires significant effort because users must carefully organize and articulate their thoughts. This may discourage users from leaving comprehensive and high-quality reviews, especially when they are on the go. To address this challenge, we developed Vocalizer, a mobile application that enables users to provide reviews through voice input, with enhancements from a large language model (LLM). In a longitudinal study, we analysed user interactions with the app, focusing on AI-driven features that help refine and improve reviews. Our findings show that users frequently utilized the AI agent to add more detailed information to their reviews. We also show how interactive AI features can improve users self-efficacy and willingness to share reviews online. Finally, we discuss the opportunities and challenges of integrating AI assistance into review-writing systems.
Comments: \c{opyright} Kavindu Ravishan | ACM 2024. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in the Proceedings of the ACM Conference on Mobile and Ubiquitous Multimedia (MUM '24), this http URL
Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)
Cite as: arXiv:2412.05445 [cs.HC]
  (or arXiv:2412.05445v2 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2412.05445
Journal reference: International Conference on Mobile and Ubiquitous Multimedia MUM '24, December 1-4, 2024, Stockholm, Sweden
Related DOI: https://doi.org/10.1145/3701571.3701593

Submission history

From: Kavindu Ravishan [view email]
[v1] Fri, 6 Dec 2024 21:59:47 UTC (6,383 KB)
[v2] Tue, 10 Dec 2024 19:31:29 UTC (6,383 KB)
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