A Machine Learning Toolbox For Musician Computer Interaction

Nicholas Gillian, Benjamin Knapp, and Sile O'Modhrain

Proceedings of the International Conference on New Interfaces for Musical Expression

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 human-computer interaction.

Citation:

Nicholas Gillian, Benjamin Knapp, and Sile O'Modhrain. 2011. A Machine Learning Toolbox For Musician Computer Interaction. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1178031

BibTeX Entry:

  @inproceedings{Gillian2011a,
 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 human-computer interaction.},
 address = {Oslo, Norway},
 author = {Gillian, Nicholas and Knapp, Benjamin and O'Modhrain, Sile},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1178031},
 issn = {2220-4806},
 keywords = {Machine learning, gesture recognition, musician-computer interaction, SEC },
 pages = {343--348},
 presentation-video = {https://vimeo.com/26872843/},
 title = {A Machine Learning Toolbox For Musician Computer Interaction},
 url = {http://www.nime.org/proceedings/2011/nime2011_343.pdf},
 year = {2011}
}