Machine Learning of Personal Gesture Variation in Music Conducting
CHI, pp. 3428-3432, 2016.
This note presents a system that learns expressive and idiosyncratic gesture variations for gesture-based interaction. The system is used as an interaction technique in a music conducting scenario where gesture variations drive music articulation. A simple model based on Gaussian Mixture Modeling is used to allow the user to configure the...More
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