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Neural networks for simultaneous classification and parameter estimation in musical instrument control
Mon, 09/21/2009 - 11:57 — AdrianFreed
| Title | Neural networks for simultaneous classification and parameter estimation in musical instrument control |
| Publication Type | Conference Paper |
| Year of Publication | 1992 |
| Authors | Lee, Michael, Freed Adrian, and Wessel David |
| Conference Name | Adaptive and Learning Systems |
| Date Published | 1992/04/16 |
| Conference Location | Orlando, FL, USA |
| Keywords | machine learning, neural networks |
| Abstract | In this report we present our tools for prototyping adaptive user interfaces in the context of real-time musical instrument control. Characteristic of most human communication is the simultaneous use of classified events and estimated parameters. We have integrated a neural network object into the MAX language to explore adaptive user interfaces that considers these facets of human communication. By placing the neural processing in the context of a flexible real-time musical programming environment, we can rapidly prototype experiments on applications of adaptive interfaces and learning systems to musical problems. We have trained networks to recognize gestures from a Mathews radio baton, Nintendo Power GloveTM, and MIDI keyboard gestural input devices. In one experiment, a network successfully extracted classification and attribute data from gestural contours transduced by a continuous space controller, suggesting their application in the interpretation of conducting gestures and musical instrument control. We discuss network architectures, low-level features extracted for the networks to operate on, training methods, and musical applications of adaptive techniques. |
| URL | https://www.spiedigitallibrary.org/conference-proceedings-of-spie/1706/1/Neural-networks-for-simultaneous-classification-and-parameter-estimation-in-musical/10.1117/12.139949.short?SSO=1 |
| DOI | 10.1117/12.139949 |