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PRE-TRAINED DEEP NEURAL NETWORK USING SPARSE AUTOENCODERS AND SCATTERING WAVELET TRANSFORM FOR MUSICAL GENRE RECOGNITION
2015
Computer Science
Research described in this paper tries to combine the approach of Deep Neural Networks (DNN) with the novel audio features extracted using the Scattering Wavelet Transform (SWT) for classifying musical genres. The SWT uses a sequence of Wavelet Transforms to compute the modulation spectrum coefficients of multiple orders, which has already shown to be promising for this task. The DNN in this work uses pre-trained layers using Sparse Autoencoders (SAE). Data obtained from the Creative Commons
doi:10.7494/csci.2015.16.2.133
fatcat:xza6xkrcqrcgpixnpyf6ek4imq