Name
Abstract | ||
|---|---|---|
We propose a novel system able to modify the rhythm of a given drum loop, known as the original, to match the rhythmic pattern of a second loop, known as the model. Our approach is fully automated, thus eliminating the need for MIDI sequencing. The presented methodology combines standard and state-of-the-art techniques for the segmentation and classification of drum sounds, the matching of drum sequences and the transformation of the original loop. We discuss the advantages and disadvantages of the proposed approach and provide links to examples for the qualitative evaluation of the system's o utput. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/LSP.2006.887783 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
audio signal processing,pattern matching,signal classification,drum sequence,rhythmic pattern matching,signal segmentation,sound classification,state-of-the-art technique,Audio effects,automatic drum transcription,content-based transformation,rhythm patterns,sequence alignment | Pattern recognition,Computer science,Segmentation,MIDI,Drum,Speech recognition,Sound classification,Artificial intelligence,Signal classification,Audio signal processing,Rhythm,Pattern matching | Journal |
Volume | Issue | ISSN |
14 | 4 | 1070-9908 |
Citations | PageRank | References |
2 | 0.46 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmanuel Ravelli | 1 | 38 | 4.70 |
| Juan Pablo Bello | 2 | 1215 | 108.94 |
| Mark Sandler | 3 | 102 | 9.81 |