Maestre Gómez, EstebanRamírez, Rafael,1966-2011-07-122011-07-122009Maestre E, Ramírez R. An approach to predicting bowing control parameter contours in violin performance. Intelligent Data Analysis. 2010; 14(5): 587-599. DOI 10.3233/IDA-2010-04411088-467Xhttp://hdl.handle.net/10230/12399We present a machine learning approach to modeling bowing control parameter/ncontours in violin performance. Using accurate sensing techniques/nwe obtain relevant timbre-related bowing control parameters such as bow/ntransversal velocity, bow pressing force, and bow-bridge distance of each/nperformed note. Each performed note is represented by a curve parameter/nvector and a number of note classes are defined. The principal components/nof the data represented by the set of curve parameter vectors are obtained/nfor each class. Once curve parameter vectors are expressed in the new space/ndefined by the principal components, we train a model based on inductive/nlogic programming, able to predict curve parameter vectors used for rendering/nbowing controls. We evaluate the prediction results and show the potential/nof the model by predicting bowing control parameter contours from an/nannotated input score.application/pdfeng© 2010 – IOS Press, Esteban Maestre Gómez and Rafael RamírezViolí, Música per aSo -- Tractament per ordinadorinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3233/IDA-2010-0441info:eu-repo/semantics/openAccess