Abstract
We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting boundaries are found along the di- agonal of the matrix. The cost of a new segment is opti- mized by matching manual and automatic segment boundaries. We compile a small song database of 21 randomly selected popular Chinese songs which come from Chinese Mainland, Taiwan and Hong Kong. The segmenting results on the small corpus show that 78% manual segmentation points are detected and 74% auto- matic segmentation points are correct. Automatic seg- mentation achieved 100% correct detection for 5 songs. The results are very encouraging.
| Originalsprog | Engelsk |
|---|---|
| Titel | Proceeding of the ISMIR |
| Antal sider | 7 |
| Forlag | Queen Mary and Goldsmith College, University of London |
| Publikationsdato | 2005 |
| Sider | 374-380 |
| ISBN (Trykt) | 0955117909 |
| Status | Udgivet - 2005 |
| Begivenhed | International Conference on Music Information Retrieval - London, Storbritannien Varighed: 11 sep. 2005 → 15 sep. 2005 Konferencens nummer: 6 |
Konference
| Konference | International Conference on Music Information Retrieval |
|---|---|
| Nummer | 6 |
| Land/Område | Storbritannien |
| By | London |
| Periode | 11/09/2005 → 15/09/2005 |