ML.* MACHINE LEARNING LIBRARY AS A MUSICAL PARTNER IN THE COMPUTER-ACOUSTIC COMPOSITION FLIGHT
| dc.contributor.author | Smith, Benjamin D. | |
| dc.contributor.author | Deal, W. Scott | |
| dc.date.accessioned | 2018-03-02T13:00:18Z | |
| dc.date.available | 2018-03-02T13:00:18Z | |
| dc.date.issued | 2014-09 | |
| dc.description.abstract | This paper presents an application and extension of the ml.* library, implementing machine learning (ML) models to facilitate “creative” interactions between musician and machine. The objective behind the work is to effectuate a musical “virtual partner” capable of creation in a range of musical scenarios that encompass composition, improvisation, studio, and live concert performance. An overview of the piece, Flights, used to test the musical range of the application is given, followed by a description of the development rationale for the project. Its contribution to the aesthetic quality of the human musical process is discussed. | en_US |
| dc.identifier.citation | Smith, Benjamin D. and W. Scott Deal. "ML.* Machine Learning Library as a Musical Partner in the Computer-Acoustic Composition Flight." In the Proceedings of the 2014 International Computer Music Conference. Michigan: ICMA, 1285-1289. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1805/15340 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Michigan Publishing | en_US |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Machine Learning | en_US |
| dc.subject | Music Composition | en_US |
| dc.subject | Unsupervised machine learning | en_US |
| dc.subject | computer music | en_US |
| dc.title | ML.* MACHINE LEARNING LIBRARY AS A MUSICAL PARTNER IN THE COMPUTER-ACOUSTIC COMPOSITION FLIGHT | en_US |
| dc.type | Article | en_US |