Corpus ID: 12305926

GRUV : Algorithmic Music Generation using Recurrent Neural Networks

@inproceedings{Nayebi2015GRUVA,
  title={GRUV : Algorithmic Music Generation using Recurrent Neural Networks},
  author={Aran Nayebi and M. Vitelli},
  year={2015}
}
  • Aran Nayebi, M. Vitelli
  • Published 2015
  • We compare the performance of two different types of recurrent neural networks (RNNs) for the task of algorithmic music generation, with audio waveforms as input. In particular, we focus on RNNs that have a sophisticated gating mechanism, namely, the Long Short-Term Memory (LSTM) network and the recently introduced Gated Recurrent Unit (GRU). Our results indicate that the generated outputs of the LSTM network were significantly more musically plausible than those of the GRU. 
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