Marc-André Rappaz

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Musical performance is a viable test case for studying the behavioural processes of the production and decoding of body expressivity in a naturalistic setting. The present study focuses on how a violinist's body expression can adapt to a variety of expressive styles. Using a motion capture system, we were able to capture body segments and the instrumental(More)
Music is often described in terms of emotion. This notion is supported by empirical evidence showing that engaging with music is associated with subjective feelings, and with objectively measurable responses at the behavioural, physiological, and neural level. Some accounts, however, reject the idea that music may directly induce emotions. For example, the(More)
In this paper, an abstract model to predict the genre of a music audio file is proposed (specifically a wave file). The output of the model is the probability distribution along the considered genres. A machine learning approach is employed. The adaptive learning process is modeled by neural networks with back-propagation as its learning algorithm and cross(More)
This study explores a unique experimental protocol that evaluates how a musician’s sensitivity to social context during performance can be analysed through a combination of behavioral analysis, self-report and Immersive Virtual Environment (IVE). An original application has been developed to create audience of avatars that display different motivational(More)
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