TY - GEN
T1 - Beat Onset Detection in an Audio Clip of a Percussion Instrument-Mridanga
AU - Vishnu Swaroop, G.
AU - Koolagudi, Shashidhar G.
AU - Srinivasa Murthy, Y. V.
N1 - Publisher Copyright:
Copy Right © INDIACom-2018.
PY - 2018
Y1 - 2018
N2 - The process of automating MIR tasks is essential due to the availability of enormous number of tracks. Of these, beat onset detection is a base for the task of Tala identification which is a part of Indian Classical Music (ICM). In this paper, an effort has been made to detect the onset of a specific percussion instrument called Mridanga as it is highly used instrument in Carnatic music. The dataset has been recorded at studio by playing the Mridanga for different Talas. Further, various signal to noise ratio (SNR) values have added in the range of 40 dB - 10 dB to generalize the system for real-time applications. The features such as centroid flux, and rate of change in energy have been computed for every sub-band. Various filtering approaches have been used to optimize the process of stroke onset detection. The results are found to be appreciable and an average accuracy of 95.01% is obtained with 40dB and 89.73% is with 10dB.
AB - The process of automating MIR tasks is essential due to the availability of enormous number of tracks. Of these, beat onset detection is a base for the task of Tala identification which is a part of Indian Classical Music (ICM). In this paper, an effort has been made to detect the onset of a specific percussion instrument called Mridanga as it is highly used instrument in Carnatic music. The dataset has been recorded at studio by playing the Mridanga for different Talas. Further, various signal to noise ratio (SNR) values have added in the range of 40 dB - 10 dB to generalize the system for real-time applications. The features such as centroid flux, and rate of change in energy have been computed for every sub-band. Various filtering approaches have been used to optimize the process of stroke onset detection. The results are found to be appreciable and an average accuracy of 95.01% is obtained with 40dB and 89.73% is with 10dB.
UR - https://www.scopus.com/pages/publications/105010513091
UR - https://www.scopus.com/inward/citedby.url?scp=105010513091&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:105010513091
T3 - 12th INDIACom; 5th International Conference on "Computing for Sustainable Global Development", INDIACom 2018
SP - 5053
EP - 5057
BT - 12th INDIACom; 5th International Conference on "Computing for Sustainable Global Development", INDIACom 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th INDIACom; 5th International Conference on Computing for Sustainable Global Development, INDIACom 2018
Y2 - 14 March 2018 through 16 March 2018
ER -
