A New Approach to Measure User Experience with Voice-Controlled Intelligent Assistants: A Pilot Study

Abstract

Voice-controlled intelligent assistants use a conversational user interface (CUI), a system that relies on natural language processing and artificial intelligence to have verbal interactions with end-users. In this research, we propose a multi-method approach to assess user experience with a smart voice assistant through triangulation of psychometric and psychophysiological measures. The approach aims to develop a richer understanding of what the users experience during the interaction, which could provide new insights to researchers and developers in the field of voice assistant. We apply this new approach in a pilot study, and we show that each method captures a part of emotional variance during the interaction. Results suggest that emotional valence is better captured with psychometric measures, whereas arousal is better detected with psychophysiological measures.