Finding temporal structure in music: blues improvisation with LSTM recurrent networks

@article{Eck2002FindingTS,
  title={Finding temporal structure in music: blues improvisation with LSTM recurrent networks},
  author={D. Eck and J. Schmidhuber},
  journal={Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing},
  year={2002},
  pages={747-756}
}
  • D. Eck, J. Schmidhuber
  • Published 2002
  • Computer Science
  • Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing
  • We consider the problem of extracting essential ingredients of music signals, such as a well-defined global temporal structure in the form of nested periodicities (or meter). We investigate whether we can construct an adaptive signal processing device that learns by example how to generate new instances of a given musical style. Because recurrent neural networks (RNNs) can, in principle, learn the temporal structure of a signal, they are good candidates for such a task. Unfortunately, music… CONTINUE READING
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