Name
Abstract | ||
|---|---|---|
In this work, we explore the task of musical onset detection in Carnatic music by choosing five major percussion instruments: the mridangam, ghatam, kanjira, morsing and thavil. We explore the musical characteristics of the strokes for each of the above instruments, motivating the challenge in designing an onset detection algorithm. We propose a non-model based algorithm using the minimum-phase group delay for this task. The music signal is treated as an Amplitude-Frequency modulated (AM-FM) waveform, and its envelope is extracted using the Hilbert transform. Minimum phase group delay processing is then applied to accurately determine the onset locations. The algorithm is tested on a large dataset with both controlled and concert recordings (tani avarthanams). The performance is observed to be the comparable with that of the state-of-the-art technique employing machine learning algorithms. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/NCC.2015.7084897 | NCC |
Keywords | Field | DocType |
onset detection,envelope detection,group delay functions,frequency modulation,multiple signal classification | Multiple signal classification,Percussion,Musical,Computer science,Waveform,Group delay and phase delay,Speech recognition,Frequency modulation,Hilbert transform,Minimum phase | Conference |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manoj Kumar, P A | 1 | 4 | 0.80 |
| Sebastian, Jilt | 2 | 6 | 2.55 |
| hema a murthy | 3 | 2 | 0.78 |