CNN based musical instrument identification using time-frequency localized features
Article Type
Research Article
Publication Title
Internet Technology Letters
Abstract
In this paper, the authors make an attempt to solve the convoluted problem of identifying musical instruments based on their audio excerpts, using a deep convolutional neural network. Continuous wavelet transform of audio signals are realized through Morse wavelet and two-dimensional feature maps are formed, which are then fed to a simple yet robust convolutional neural network. The outcome is appreciable in the sense that training the model with just 20% of the data and testing on the rest gives a classification accuracy of 85%.
DOI
10.1002/itl2.191
Publication Date
1-1-2022
Recommended Citation
Dutta, Arindam; Sil, Dibakar; Chandra, Aniruddha; and Palit, Sarbani, "CNN based musical instrument identification using time-frequency localized features" (2022). Journal Articles. 3301.
https://digitalcommons.isical.ac.in/journal-articles/3301
Comments
Open Access, Bronze