Affiliation:
1. Research Division, Genie Enterprise, Donnersbergweg 1, 67059 Ludwigshafen, Germany
2. Cognitive Systems Group, Faculty of Electrical Engineering and Information Technology, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
Abstract
Humans are considered to be communicative, usually interacting in dyads or groups. In this paper, we investigate group interactions regarding performance in a rather formal gathering. In particular, a collection of ten performance indicators used in social group sciences is used to assess the outcomes of the meetings in this manuscript, in an automatic, machine learning-based way. For this, the Parking Lot Corpus, comprising 70 meetings in total, is analysed. At first, we obtain baseline results for the automatic prediction of performance results on the corpus. This is the first time the Parking Lot Corpus is tapped in this sense. Additionally, we compare baseline values to those obtained, utilising bidirectional long-short term memories. For multiple performance indicators, improvements in the baseline results are able to be achieved. Furthermore, the experiments showed a trend that the acoustic material of the remaining group should use for the prediction of team performance.
Funder
Federal State of Saxony-Anhalt, Germany
Subject
Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Neuroscience (miscellaneous)
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