Beyond DeepJazz

This project focuses on comparison of different generative methods in music generation. We use the exact setting of DeepJazz (preprocessing, grammar, generation pipeline, input / output dimension, certain hyperparameters, etc.) such that a concise and direct of comparison among different models can be observed.

We Acknowledge the great effort by DeepJazz team, it laid a great foundation and interface for our future work. So we can focus on higher-level model selection and comparison.

Structure

/data           # store original training data
/result         # store generation result
/utils          # preprocessing, grammar, helper function
/future         # WIP, future work and adaptation
lstm.py         # models, including LSTM, VAE-LSTM, BI-LSTM
generator.py    # project interface

Reference

Code reference and baseline template

• Deep Jazz
  https://github.com/jisungk/deepjazz

Paper reference in implementation

• Chen, K., Zhang, W., Dubnov, S., Xia, G., & Li, W. (2019, January). The effect of explicit structure encoding of deep neural networks for symbolic music generation. In 2019 International Workshop on Multilayer Music Representation and Processing (MMRP) (pp. 77-84). IEEE.
  https://arxiv.org/pdf/1811.08380.pdf

• Performance-RNN by Margenta
  https://magenta.tensorflow.org/performance-rnn

  • Dynamics
  • Temperature and randomness
  • Volumes

Additional Dataset

To download the larger Yamaha e-Piano Competition Dataset, from:

• Malik, I., & Ek, C. H. (2017). Neural translation of musical style. arXiv preprint arXiv:1708.03535. Use this link: http://imanmalik.com/assets/dataset/TPD.zip

Usage

Use generator.py for public interface

E.g. use lstm model and train 2 epochs

python generator.py --model-choice "lstm" --epochs 2

E.g. use vae-lstm model and train 1 epochs

python generator.py --model-choice "vae-lstm" --epochs 1

E.g. use bi-lstm model and train 128 epochs

python generator.py --model-choice "bi-lstm" --epochs 128

E.g. use bi-lstm model and train 2 epochs, with diversity 0.7

python generator.py --model-choice "bi-lstm" --epochs 2 --diversity 0.7

Requirement

python 2.7
keras
tensorflow
music21
numpy