A Machine Learning Toolbox For Musician Computer Interaction

Gillian, Nicholas and Knapp, Benjamin and O’Modhrain, Sile

Proceedings of the International Conference on New Interfaces for Musical Expression

This paper presents the SARC EyesWeb Catalog, (SEC),a machine learning toolbox that has been specifically developed for musician-computer interaction. The SEC features a large number of machine learning algorithms that can be used in real-time to recognise static postures, perform regression and classify multivariate temporal gestures. The algorithms within the toolbox have been designed to work with any N -dimensional signal and can be quickly trained with a small number of training examples. We also provide the motivation for the algorithms used for the recognition of musical gestures to achieve a low intra-personal generalisation error, as opposed to the inter-personal generalisation error that is more common in other areas of human-computer interaction.