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Unsupervised Chord-Sequence Generation from an Ausio Example
| Title | Unsupervised Chord-Sequence Generation from an Ausio Example |
| Publication Type | Conference Paper |
| Year of Publication | 2012 |
| Conference Name | International Society for Music Information Retrieval Conference (ISMIR 2012) |
| Authors | Kosta, K. , Marchini M. , & Purwins P. |
| Abstract | A system is presented that generates a sound sequence from an original audio chord sequence, having the following characteristics: The generation can be arbitrarily long, preserves certain musical characteristics of the original and has a reasonable degree of interestingness. The procedure comprises the following steps: 1) chord segmentation by onset detection, 2) representation as Constant Q Profiles, 3) multi-level clustering, 4) cluster level selection, 5) metrical analysis, 6) building of a suffix tree, 7) generation heuristics. The system can be seen as a computational model of the cognition of harmony consisting of an unsupervised formation of harmonic categories (via multi-level clustering) and a sequence learning module (via suffix trees) which in turn controls the harmonic categoriza- tion in a top-down manner (via a measure of regularity). In the final synthesis, the system recombines the audio ma- terial derived from the sample itself and it is able to learn various harmonic styles. The system is applied to various musical styles and is then evaluated subjectively by musicians and non-musicians, showing that it is capable of producing sequences that maintain certain musical characteristics of the original. |
