IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v43y2024i3p433-444.html
   My bibliography  Save this article

Voice orientation of conversational interfaces in vehicles

Author

Listed:
  • Kwan Min Lee
  • Yohan Moon
  • Inyoung Park
  • Jae-gil Lee

Abstract

Connected vehicles have become a promising platform for conversational agents. However, drivers might struggle to control systems that feature multiple AI agents. To improve the usability of increasingly complex systems and the user’s interaction experience, the integration of various conversational agents needs to be carefully considered. This study aims to investigate the following: What constitutes an efficient, user-friendly arrangement of the tasks performed by a home and a car artificial intelligence (AI) agent? What is the optimal method to trigger the use of such agents? A between-subjects factorial experiment was conducted with three types of AI agent setting (home AI generalist vs. vehicle AI generalist vs. home and vehicle AI specialists) and two activation methods (voice activation vs. push-to-talk activation). The results indicate that interacting with specialist AI agents enhances the perceived ease of use and the credibility of these agents. Furthermore, voice activation improves the social presence and attractiveness of an AI agent. The findings suggest that an AI agent that offers role specialization and a natural interaction method will improve drivers’ interaction experience.

Suggested Citation

  • Kwan Min Lee & Yohan Moon & Inyoung Park & Jae-gil Lee, 2024. "Voice orientation of conversational interfaces in vehicles," Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(3), pages 433-444, February.
    • Handle: RePEc:taf:tbitxx:v:43:y:2024:i:3:p:433-444
    DOI: 10.1080/0144929X.2023.2166870
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2023.2166870
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0144929X.2023.2166870?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tbitxx:v:43:y:2024:i:3:p:433-444. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.