Name
Title | ||
|---|---|---|
Classification and Generation of Composer-Specific Music Using Global Feature Models and Variable Neighborhood Search |
Abstract | ||
|---|---|---|
In this article a number of musical features are extracted from a large musical database and these were subsequently used to build four composer-classification models. The first two models, an if-then rule set and a decision tree, result in an understanding of stylistic differences between Bach, Haydn, and Beethoven. The other two models, a logistic regression model and a support vector machine classifier, are more accurate. The probability of a piece being composed by a certain composer given by the logistic regression model is integrated into the objective function of a previously developed variable neighborhood search algorithm that can generate counterpoint. The result is a system that can generate an endless stream of contrapuntal music with composer-specific characteristics that sounds pleasing to the ear. This system is implemented as an Android app called FuX. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1162/COMJ_a_00316 | Computer Music Journal |
Field | DocType | Volume |
Decision tree,Android app,Variable neighborhood search,Computer science,Support vector machine classifier,Musical,Speech recognition,Artificial intelligence,Counterpoint,Logistic regression,Machine learning | Journal | 39 |
Issue | ISSN | Citations |
3 | 0148-9267 | 4 |
PageRank | References | Authors |
0.52 | 42 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dorien Herremans | 1 | 54 | 16.22 |
| Kenneth Sörensen | 2 | 175 | 19.42 |
| David Martens | 3 | 66 | 9.52 |