Escalona Cuaresma, María JoséRauschenberger, MariaKlein, Andreas M.2025-03-042025-03-042024-11-29Klein, A.M. (2024). Context-Dependent User Experience Assessment Approach for Voice User Interfaces. (Tesis Doctoral Inédita). Universidad de Sevilla, Sevilla.https://hdl.handle.net/11441/169547Voice user interfaces (VUIs) such as Amazon Alexa, Apple Siri, and Google Assistant are widely used, readily available, and seamlessly integrated into everyday life. They have become more intelligent due to recent advances in artificial intelligence, which provides new methods of processing contextual information. Despite their widespread use and recent innovations, VUIs face challenges regarding intelligibility, human-like conversation, and privacy. Only a tiny fraction of users perceive VUIs as intelligent and trustworthy as humans. User experience (UX) evaluation is anchored in the human-centered design process. UX is a holistic view of the user’s perception of interaction. The prominent role of UX evaluation methods for designs with graphical user interfaces (GUIs) reflects their dominance in computer-based technology. Furthermore, methods are often tailored to specific measurement contexts. Therefore, the human-computer interaction community requires a flexible and adaptable UX evaluation for VUIs. The core goal of this dissertation is to provide context-dependent UX measurement recommendations for VUIs. We apply the standardized design science research methodology. Our approach is based on the User Experience Questionnaire Plus (UEQ+) framework, which allows flexible assessment. One can select from several UX scales measuring distinct aspects to form a questionnaire. However, the UEQ+ was mainly developed to assess GUI-equipped designs. Thus, we contribute three scales measuring relevant UX aspects for VUIs: Response Behavior, Response Quality, and Comprehensibility. We also offer a conceptual structure of the VUI context of use. By applying this structure, we can select relevant UEQ+ scales and customize the questionnaire to fit any context. This enables recommendations for context-dependent UX assessment for VUIs and provides a new flexible measurement method for better evaluation of voice technology.application/pdf205 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccess