From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910738926272512 |
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| author | Ravishan, Kavindu Szabó, Dániel van Berkel, Niels Visuri, Aku Yang, Chi-Lan Yatani, Koji Hosio, Simo |
| author_facet | Ravishan, Kavindu Szabó, Dániel van Berkel, Niels Visuri, Aku Yang, Chi-Lan Yatani, Koji Hosio, Simo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05445 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go Ravishan, Kavindu Szabó, Dániel van Berkel, Niels Visuri, Aku Yang, Chi-Lan Yatani, Koji Hosio, Simo Human-Computer Interaction Artificial Intelligence 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. |
| title | From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2412.05445 |