Mühl, LisaHorstmann, Aike C.Wittenborn, AndréStorch, DunjaKrajewski, JarekSchneegass, StefanPfleging, BastianKern, Dagmar2021-09-032021-09-032021https://dl.gi.de/handle/20.500.12116/37294Many refugees experience critical life events or traumatic injuries during their flights. Here, underaged, (un)accompanied refugees are a particularly vulnerable group. To date, there are insufficient support structures that recognize the specific demands and allow for careful and early identification of indicators of traumatization or behavioral problems. As an approach to counteract these deficits and support underage refugees, the TraM project investigates the potential of an AI-based screening tool providing indications of post-traumatic stress disorder via speech-emotion-recognition. A data collection for standardized learning data was conducted as a basis for the described screening module and the planned algorithms for automatic classification. We encountered several challenges such as insufficient data quality, uncertain classifications, and comorbidities such as depression as potentially confounding factors. Accordingly, emphasis lays on using the screening module for an initial examination of mental health and potential traumatization. This may encourage affected underage refugees to seek the help that is often highly needed.enspeech-emotion recognitionpost-traumatic stress disorderfeature extractionbehavioral markersrefugee minorsText/Conference Paper10.1145/3473856.3474011