Research described in this paper tries to combine the approach of Deep Neural Networks (DNN) with the novel audio features extracted using the Scatter- Ing Wavelet Transform (SWT) for classifying musical genres. The SWT uses A sequence of Wavelet Transforms to compute the modulation spectrum coef- Ficients 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 website jamendo.com is Used to boost the well-known GTZAN database, which is a standard bench- mark for this task. The final classifier is tested using a 10-fold cross validation To achieve results similar to other state-of-the-art approaches.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.