/chord-generator-attention-lstm

Keras implementation of "Chord Generation from Symbolic Melody Using BLSTM Networks"

Primary LanguagePython

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Chord Generator with Attention LSTM

Keras implementation of "Chord Generation from Symbolic Melody Using BLSTM Networks"

Result

SoundCloud Link

  • Piano Melody Sound : MuseScore2
  • Guitar Backing Sound : I play

Dependencies

  • Python 3.6
  • Numpy
  • Pandas
  • Keras 2.2.4

Workflow

WorkFlow

data_preprocess.py

  • Transpose to the C key
  • Convert to 2 kinds of chords (maj or min)

make_npy.py

  • Create numpy array file for training

train.py

  • Feed input/target vector into Neural net
  • Train the model

generate.py

  • Generate the Chord from note sequence

Difference with The Paper

  • Neural Network Algorithm
    I compared Attention LSTM with other RNN algorithms(LSTM, BLSTM, GRU), but there was no performance difference.

  • Some hyper parameters

  • Preprocess method
    I didn't use the feature about note's time information(time, duration).

Dataset

I used the dataset provided in the paper, the dataset is based on the Wikifonia Dataset.