@inproceedings{,
    author = {Pfeuffer, Ken; Geiger, Matthias; Prange, Sarah; Mecke, Lukas; Buschek, Daniel; Alt, Florian},
    title = {Behavioural Biometrics in VR : Identifying People from Body Motion and Relations in Virtual Reality},
    editor = {},
    booktitle = {CHI '19 : Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems},
    series = {},
    journal = {},
    address = {New York, NY, USA},
    publisher = {ACM},
    edition = {},
    year = {2019},
    isbn = {978-1-4503-5970-2},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {10.1145/3290605.3300340},
    keywords = {Virtual Reality ; Behavioural Biometrics ; Motion ; Relation ; Proprioception ; Adaptive UIs},
    abstract = {This paper investigates personalized voice characters for incarspeech interfaces. In particular, we report on how wedesigned different personalities for voice assistants and comparedthem in a real world driving study. Voice assistantshave become important for a wide range of use cases, yet current interfaces are using the same style of auditory responsein every situation, despite varying user needs andpersonalities. To close this gap, we designed four assistantpersonalities (Friend, Admirer, Aunt, and Butler) and comparedthem to a baseline (Default) in a between-subject studyin real traffic conditions. Our results show higher likabilityand trust for assistants that correctly match the user’s personalitywhile we observed lower likability, trust, satisfaction; and usefulness for incorrectly matched personalities, eachin comparison with the Default character. We discuss designaspects for voice assistants in different automotive use cases.},
    note = {},
    institution = {Universität der Bundeswehr München, Fakultät für Informatik, INF 5 - Institut für Anwendungssicherheit, Professur: Alt, Florian},
    
    
}