DocumentCode :
2427491
Title :
Musical onset detection on carnatic percussion instruments
Author :
Manoj Kumar, P.A. ; Sebastian, Jilt ; Murthy, Hema A.
Author_Institution :
Indian Inst. of Technol. Madras, Chennai, India
fYear :
2015
fDate :
Feb. 27 2015-March 1 2015
Firstpage :
1
Lastpage :
6
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.
Keywords :
Hilbert transforms; acoustic signal detection; music; musical instruments; AM-FM waveform; Carnatic music; Hilbert transform; amplitude-frequency modulated waveform; concert recordings; envelope detection; ghatam; kanjira; minimum phase group delay processing; minimum-phase group delay; morsing; mridangam; musical onset detection; nonmodel based algorithm; strokes; tani avarthanams; thavil; Delays; Detection algorithms; Frequency modulation; Instruments; Mouth; Multiple signal classification; Transforms; Onset detection; envelope detection; group delay functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (NCC), 2015 Twenty First National Conference on
Conference_Location :
Mumbai
Type :
conf
DOI :
10.1109/NCC.2015.7084897
Filename :
7084897
Link To Document :
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