This study investigates the growing importance of voice assistants, particularly focusing on their usage patterns and associated user characteristics, trust perceptions, and concerns about data security. While previous research has identified correlations between the use of voice assistants and trust in these technologies, as well as data security concerns, little evidence exists regarding the relationship between individual user traits and perceived trust and security concerns. The study design involves surveying various user attributes, including technical proficiency, personality traits, and experience with digital technologies, alongside attitudes toward and usage of voice assistants. A comparison between Germany and Finland is conducted to explore potential cultural differences. The findings aim to inform strategies for enhancing voice assistant acceptance, including the implementation of anonymization methods.

We report about design and characteristics of the LAST MINUTE corpus. The recordings in this data collection are taken from a WOZ experiment that allows to investigate how users interact with a companion system in a mundane situation with the need for planning, re-planning and strategy change. The resulting corpus is distinguished with respect to aspects of size (e.g. number of subjects, length of sessions, number of channels, total length of records) as well as quality (e.g. balancedness of cohort, well designed scenario, standard based transcripts, psychological questionnaires, accompanying in-depth interviews).

The LAST MINUTE corpus comprises multimodal recordings (e.g. video, audio, transcripts) from WOZ interactions in a mundane planning task (Rösner et al., 2011). It is one of the largest corpora with naturalistic data currently available. In this paper we report about first results from attempts to automatically and manually analyze the different modes with respect to emotions and affects exhibited by the subjects. We describe and discuss difficulties encountered due to the strong contrast between the naturalistic recordings and traditional databases with acted emotions.