An Adaptive Classification Algorithm For Semiotic Musical Gestures

Publication Type:

Conference Paper


SMC Conference 2011 (2011)


This paper presents a novel machine learning algorithm that has been specifically developed for the classification of semiotic musical gestures.  We demonstrate how our algorithm, called the Adaptive Naive Bayes Classifier, can be quickly trained with a small number of training examples and then classify a set of musical gestures in a continuous stream of data that also contains non-gestural data.  The algorithm also features an adaptive function that enables a trained model to slowly adapt itself as a performer refines and modifies their own gestures over, for example, the course of a rehearsal period.  The paper is concluded with a study that shows a significant overall improvement in the classification abilities of the algorithm when the adaptive function is used.

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