Exploiting cepstral coefficients and CNN for efficient musical instrument classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12530-023-09540-x.pdf
Reference33 articles.
1. Aucouturier JJ, Pachet F (2003) Representing musical genre: a state of the art. J New Music Res 32(1):83–93
2. Bhalke D, Rao CR, Bormane DS (2016) Automatic musical instrument classification using fractional Fourier transform based-MFCC features and counter propagation neural network. J Intell Inf Syst 46(3):425–446
3. Bormane D, Dusane M (2013) A novel techniques for classification of musical instruments. Inf Knowl Manag 3:1–8
4. Chakraborty SS, Parekh R (2018) Improved musical instrument classification using cepstral coefficients and neural networks. Methodologies and application issues of contemporary computing framework. Springer, Cham, pp 123–138
5. Deng JD, Simmermacher C, Cranefield S (2008) A study on feature analysis for musical instrument classification. IEEE Trans Syst Man Cybern Part B (Cybernetics) 38(2):429–438
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