This repo contains a jupyter notebook for the research: EXPLORING FURTHER RELATIONS OF METRICAL STRENGTH AND PITCH RELATIONS IN TURKISH MAKAM MUSIC
In this research we further develop the research of Holzapfelet et al [1] exploring the reinforcement of meter in the music of Turkish Makam. Our research follows a similar methodology to that described by Holzapfel, deriving note onset distributions which we subsequently correlate to weighted usul histograms used to formalise meter.
In particular, we aim to answer three main questions:
RQ1 - To what extent are the findings andconclusions drawn in Holzapfel et al’s work reproducible on a different data-set?
RQ2 - To what degree does thechoice ofmakamalso act to reinforce or diminish metricalstrength?
RQ3 - To what extent do pitch relations acrossmakamswith differingusulsact to also reinforce metre?
We find the results of [1] to be reproducible such that our research is able to identify similar
correlation patterns across all usul considered.
Consistent correlation variation acros smakams are also identified.
In addition, our work goes further to assess the extent to which pitch is used to reinforce
metrical structure in makam (to the best ofour knowledge, not previously addressed in past works).
Although no immediate patterns are identified, we suggest subsequent developments which could be made in future works to
further explore the role of pitch in metrical reinforcement.
[1]
Andre Holzapfel and Barıs Bozkurt. Metrical strength and contradiction in turkish makam music. In Proceedings of the 2nd CompMusic Workshop; 2012 July 12-13, pages 79–84, 2012. http://mtg.upf.edu/node/3886
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Python and the following modules are necessary to run the notebook correctly: music21, numpy, matplotlib, scipy and pandas.
You can install the modules required simply typing on the terminal the following command:
$ pip install -r requirements.txt
(the file requiremennts.txt is in the repository)
Otherwise, you can manually install the single modules with the following commands:
In Ubuntu the user can install all these modules it is as simple as typing on the terminal:
$ sudo apt-get install python-dev python-numpy python-matplotlib python-scipy python-pandas
$ pip install music21
In OSX the user can install these modules by typing on the terminal:
$ brew install python
$ pip install numpy matplotlib scipy pandas
$ pip install music21
In Windows the user can refer to this link to install python on your local machine: https://docs.python.org/3/using/windows.html and install the other modules by typing on the terminal:
$ pip install pandas numpy scipy matplotlib music21
Clone or download the repository. It contains a jupyter notebook, please read Jupyter Notebook instruction to properly change directories paths and run the notebook correctly.
Command to clone the repository:
$ git clone https://github.com/RonFrancesca/makam_research.git
The dataset can be downlaoded at the following links:
- download the full pdf score dataset here: https://github.com/MTG/SymbTr-pdf
- download the full xml files dataset here: https://github.com/MTG/SymbTr/releases/tag/v2.4.3
Install Jupyter Notebook according to the its instructions https://jupyter.org/install
Start up jupyter notebook
$ jupyter notebook
Follow the instructions appearing in the console regarding navigating your browser to the notebook
The user will also need a score editor to follow the examples. MuseScore (suggested) could be download at the following link: https://musescore.org
This project is licensed under a Creative Commons Attribution 4.0 International License (CC BY4.0). Attribution:Dougal Shakespeare, Francesca Ronchini. “Exploring Further Relations of Metrical Strength and Pitch Relations in Turkish Makam music”.
- Francesca Ronchini
- Dougal Shakespeare