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Voice user interfaces (VUIs) offer an intuitive, fast and convenient way for humans to interact with machines and computers. Yet, whether they’ll be truly successful and find widespread uptake in the near future depends on the user experience (UX) they offer. With this survey-based study (n = 108), we aim to identify the major annoyances German voice assistant users are facing in voice-driven human-computer interactions. The results of our questionnaire show that irritations appear in six categories: privacy issues, unwanted activation, comprehensibility, response quality, conversational design and voice characteristics. Our findings can help identify key areas of work to optimize voice user experience in order to achieve greater adaptation of the technology. In addition, they can provide valuable information for the further development and standardization of voice user experience (VUX) research.
Digitale Kundeninteraktionen haben in den letzten Jahren enorm an Bedeutung gewonnen: Sowohl im B2B als auch im B2C sind weite Teile der Interaktion digital bzw. hybrid konzipiert. Ob ein bargeldloser Bezahlvorgang an der Kasse, ein Bestellformular beim Onlinekauf oder der Kauf einer Bahnfahrkarte am Automaten – die Kunden und Kundinnen haben digitale Interaktionen in vielfältigen Varianten bereits erlebt und kommen mehr oder weniger gut damit zurecht.
Empirische Forschung als Herausforderung im laufenden Lehrbetrieb – Lösungsansätze aus der Praxis
(2022)
Um empirische Forschung auch unter außergewöhnlichen Bedingungen zu ermöglichen, ist es notwendig, flexibel zu reagieren und neue Konzepte zu entwickeln. Dieser Beitrag befasst sich mit den Herausforderungen, die sich aufgrund der Corona-Pandemie im Lehralltag ergeben und bietet verschiedene Ansätze, um diesen Herausforderungen zu begegnen und Forschung zu betreiben. Er betrachtet ein Fallbeispiel aus der quantitativen Marktforschung, sowie Online-Alternativen zu Eye-Tracking-Studien und Möglichkeiten für User-Experience-Testings im Labor unter strengen Hygienemaßnahmen.
Due to the increasing aging of the population, the number of elderly people requiring care is growing in most European countries. However, the number of caregivers working in nursing homes and on daily care services is declining in countries like Germany or Italy. This limits the time for interpersonal communication. Furthermore, as a result of the Covid-19 pandemic, social distancing during contact restrictions became more important, causing an additional reduction of personal interaction. This social isolation can strongly increase emotional stress. Robotic assistance could contribute to addressing this challenge on three levels: (1) supporting caregivers to respond individually to the needs of patients and residents in nursing homes; (2) observing patients’ health and emotional state; (3) complying with high hygiene standards and minimizing human contact if required. To further the research on emotional aspects and the acceptance of robotic assistance in care, we conducted two studies where elderly participants interacted with the social robot Misa. Facial expression and voice analysis were used to identify and measure the emotional state of the participants during the interaction. While interpersonal contact plays a major role in elderly care, the findings reveal that robotic assistance generates added value for both caregivers and patients and that they show emotions while interacting with them.