Article
Authors: Oliver Guhr, Claudia Loitsch, Gerhard Weber, and Hans-Joachim Böhme
Artificial Intelligence in HCI: 5th International Conference, AI-HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings, Part III
June 2024
Pages 231 - 249
Published: 29 June 2024 Publication History
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Abstract
Voice Interfaces have become ubiquitous as they can make complex technology more usable and accessible. Current voice interfaces, however, often require the user to learn specific speech commands or sentence patterns to use them. This property does not satisfy usability heuristics and causes current language interfaces to underachieve the naturalness of language interaction. To address this issue, we developed a voice interface that is capable of understanding natural everyday language. The overall objective is to build a German language voice interface for socially assistive robots that can work in public spaces. Therefore, we cannot assume the user’s prior knowledge or experience. Based on recent advances in deep natural language processing, we have built a voice interface that is not restricted to specific speech commands. To test this voice interface, we conducted a study with 47 participants. Results indicate 93% of the given tasks were solved successfully by the target user group without prior training or experience with the voice interface.
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Published In
Artificial Intelligence in HCI: 5th International Conference, AI-HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings, Part III
Jun 2024
497 pages
ISBN:978-3-031-60614-4
DOI:10.1007/978-3-031-60615-1
- Editors:
- Helmut Degen
Siemens Corporation, Princeton, NJ, USA
, - Stavroula Ntoa
Foundation for Research and Technology - FORTH, Heraklion, Crete, Greece
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 29 June 2024
Author Tags
- Human-Robot Interaction
- Voice Interface
- User Study
Qualifiers
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