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Chord-Scales Dataset created & annotated for 'automatic scale detection' task

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Chord-Scale_Detection

Repository for "Chroma Based Automatic Chord-Scale Detection for Monophonic Jazz Solos" task.

Chord-Scale Dataset
Artists - instrument :

Jamey Aebersold - tenor saxophone
Toprak Barut - tenor saxophone
Hikmet Altunbaslier - trumpet

List of chord-scales annotated & taxonomy :

Major (major)
Dorian (dorian)
Phyrgian (phyrgian)
Lydian (lydian)
Mixolydian (mixolydian)
Natural Minor (minor)
Locrian (locrian)
Lydian b7 (lydianb7)
Super Locrian / Altered (slocrian)
Half-whole Step Symmetrical Diminished (hwdiminished)
Melodic Minor (mminor)
Harmonic Minor (hminor)
Whole-tone* Chromatic*

  • : The last two scales are only included in the estimation class set as scale templates.

Installation

In order to use the tools and notebooks, you need to install 'docker' . Docker provides a virtual environment with all the desired dependencies and libraries already installed. In this toolbox for 'Chroma Based Automatic Chord-Scale Detection for Monophonic Jazz Solos', we have used the tools in 'MIR-Toolbox' which contains a set of tools (including numpy,matplotlib, scikit-learn,'Essentia' ) installed and compiled for several Music Information Retrieval applications. For more information regarding toolbox, please refer to https://github.com/MTG/MIR-toolbox-docker :

  1. Install docker-compose Follow instructions.

Windows https://docs.docker.com/docker-for-windows/install/

Mac https://docs.docker.com/docker-for-mac/install/

Ubuntu https://docs.docker.com/engine/installation/linux/docker-ce/ubuntu/#install-docker-ce

  1. Clone the repository into target directory.
git clone https://github.com/emirdemirel/Supervised_Mode_Recognition.git
  1. On MacOS or Windows, run:
docker-compose up

On Linux, run the following (this command ensures that any files you create are owned by your own user):

JUPYTER_USER_ID=$(id -u) docker-compose up

Then accesss http://localhost:8888 with your browser and when asked for a password use mir

  1. Open the Jupyter notebook 'Chord-scale_Detection.ipynb' for the implementation of the work presented in paper [1].

Authors

Emir Demirel [email protected]

License: CC BY-NC-SA 4.0

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Chord-Scales Dataset created & annotated for 'automatic scale detection' task

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