Learning Rhythm And Melody Features With Deep Belief Networks

  title={Learning Rhythm And Melody Features With Deep Belief Networks},
  author={Erik M. Schmidt and Youngmoo Kim},
Deep learning techniques provide powerful methods for the development of deep structured projections connecting multiple domains of data. But the fine-tuning of such networks for supervised problems is challenging, and many current approaches are therefore heavily reliant on pretraining, which consists of unsupervised processing on the input observation data. In previous work, we have investigated using magnitude spectra as the network observations, finding reasonable improvements over standard… CONTINUE READING
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