Authors: Nicholas Gillian, R. Benjamin Knapp, and Sile O'Modhrain.
Title: A machine learning toolbox for musician computer interaction.
Abstract: 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 humancomputer interaction.
Recorded at: 11th International Conference on New Interfaces for Musical Expression. 30 May - 1 June 2011, Oslo, Norway. http://www.nime2011.org