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A Comparative Evaluation of Decomposition Methods Based on Pitch Estimation of Piano Notes

Publication Type : Conference Paper

Publisher : Smart Innovation, Systems and Technologies

Authors : Dr. Jyothish Lal. G., Vamsi Krishna, U., Priyamvada, R,Sowmya, V., Soman, K.P.

Url : https://link.springer.com/chapter/10.1007/978-981-16-0878-0_82

Keywords : Frequency estimation ,Decomposition ,Variational calculus ,Wavelets

Campus : Coimbatore

Center : Center for Computational Engineering and Networking, Computational Engineering and Networking

Year : 2021

Abstract : Wavelet decomposition, variational mode decomposition, and dynamic mode decomposition are the latest signal processing tools that are recently being utilized in the music domain. Most of the work on these algorithms in music domain shows results based on pitch contour. None of the work mentions the effect of different frequency ranges (octaves) on these algorithms. In this paper, the evaluation is performed to understand the effect of different octaves on these decomposition algorithms based on pitch estimation of piano notes. Wavelet decomposition, variational mode decomposition, and dynamic mode decomposition methods are evaluated based on pitch estimation for different octaves. The purpose of this evaluation is to identify the most suitable method for pitch estimation. A comparative evaluation is performed on piano recordings taken from the database of the electronic music studio, University of Iowa. Absolute mean logarithmic error is used as the metric for evaluating the algorithms. The evaluation of algorithms is performed on seven different octaves ranging from 1 to 7. Variational mode decomposition performed better throughout the 7 octaves. Wavelet decomposition also performed well but was less accurate than variational mode decomposition. Dynamic mode decomposition was the least accurate among all the methods.

Cite this Research Publication : Vamsi Krishna, U., Priyamvada, R., Jyothish Lal, G., Sowmya, V., Soman, K.P. "A Comparative Evaluation of Decomposition Methods Based on Pitch Estimation of Piano Notes." In Smart Innovation, Systems and Technologies 225, pp. 833-843, 2021.

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