/Emotion-Guided-Piano-Accompaniment-Generation

This is the codes repository for the paper "Emotion-Guided Music Accompaniment Generation based on VAE".

Primary LanguagePython

Emotion-Guided-Piano-Accompaniment-Generation

This is the codes repository for the project "Emotion-guided Piano Accompaniment Generation".

Baseline models are from Accomontage Repo.

Training and validation set is derived from POP909 dataset and emotion-guided music generation test set is a part of Nottingham Dataset.

Harmonization module is updated (2023/2/2) The paper is accepted at International Joint Conference on Neural Networks 2023(IJCNN2023).

Paper Link

https://arxiv.org/abs/2307.04015.

Run Demos

  1. Click here to download the data folder and put them in ./data.

  2. Put the melodies (MIDI Format) in the ./original_midi;

  3. Run demo.py;

  4. Wait a while and the accompaniment will be saved in the ./generate_midi.

  5. For more emotional flow guided generation samples, please refer to https://soundcloud.com/ko9isjyplxrb/sets/demos-of-emotion-guided-generated-accompaniment.

Train the model

  1. Click here to download the processed dataset and put them in ./data.

  2. Run train.py

  3. Log files will be automatically generated to the root directory, please use tensorboard related commands to monitor the training process.

Q&A

  1. Q: Sometimes the generated chords dont fully harmonize the melody. How come?

    A: The randomness and controllabilty of LSTM-based harmonizer isnt satisfactory. Use music theory for the harmonization instead. You can rectify the solve() function from ./utils/Accompaniment_Generator.py for your personal usage.