Name
Abstract | ||
|---|---|---|
According to musicology, musical content and musical structure are both major components of a music work. Most approaches of music retrieval, classification, and analysis use the information of the musical content, but not the information of the musical structure. The main reason is that the musical structure usually needs to be analyzed manually by experts, which is time-consuming and impractical. We propose an approach for automatic music segmentation to extract the phrases and sentences of the musical structure. In addition to the rhythmic features, the melodic shape is also used to improve the effectiveness of the music segmentation. Experiments are performed to show that our approach is practical. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICME.2004.1394566 | ICME |
Keywords | Field | DocType |
musicology,music,melodic shapes,music classification,rhythmic features,musical content,feature extraction,music analysis,musical structure,audio signal processing,music retrieval,automatic music segmentation,multiple signal classification,databases,statistics,shape,computer science,data mining,information analysis | Information structure,Melody,Segmentation,Computer science,Musical acoustics,Musical,Musical syntax,Musicology,Speech recognition,Artificial intelligence,Natural language processing,Musical form | Conference |
Volume | ISBN | Citations |
3 | 0-7803-8603-5 | 2 |
PageRank | References | Authors |
0.39 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hung-chen Chen | 1 | 126 | 8.59 |
| Chih-hsiang Lin | 2 | 67 | 4.03 |
| Arbee L. P. Chen | 3 | 1769 | 886.26 |