Abstract
This paper brings together two important aspects of the human-machine interaction in cars: the psychological aspect and the engineering aspect. The psychologically motivated part of this study addresses questions such as why it is important to automatically assess the driver’s affective state, which states are important and how a machine’s response should look like. The engineering part studies how the emotional state of a driver can be estimated by extracting acoustic features from the speech signal and mapping them to an emotion state in a multidimensional, continuous-valued emotion space. Such a feasibility study is performed in an experiment in which spontaneous, authentic emotional utterances are superimposed by car noise of several car types and various road surfaces.
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Grimm, M. et al. (2007). On the Necessity and Feasibility of Detecting a Driver’s Emotional State While Driving. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2007. Lecture Notes in Computer Science, vol 4738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74889-2_12
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DOI: https://doi.org/10.1007/978-3-540-74889-2_12
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