OTMM Score Structure Experiments for FMA 2016
<p>otmm-score-structure-experiments</p> <p>Structure Analysis Experiments on Ottoman-Turkish Makam Music Scores</p> <p>This repository contains the experiments to find the optimal melodic and lyrics similarity threshold, conducted in the paper:</p> <p>Şentürk, S., & Serra X. (2016). A method for structural analysis of Ottoman-Turkish makam music scores. In Proceedings of 6th International Workshop on Folk Music Analysis, (pp. 39-46)., Dublin, Ireland.</p> <p>For the details of the experiments, please refer to the paper. Please cite the publication above in any work using these experiments.</p> <p>The submodule turkish_makam_section_dataset stores the test scores in the SymbTr-txt format. The experiments folder have the experimental results and evaluation. Each folder in this folder stores the sections extracted from each score for the given threshold, e.g. folder "0_6" has the results obtained using a similarity threshold of 0.6 for both melodic and lyrical relationship computation. The extracted sections for each score are stored in a csv file, which has the same name as the SymbTr-name (makam--form--usul--name--composer) of the analyzed score. The fields are:</p> <p>start_note: The starting note index in the SymbTr-txt score end_note: The ending note index in the SymbTr-txt score name: The basic semantic name of the section. Right now, it is the name (TESLİM, ARANAĞME...) annotated in the score for instumental sections or "VOCAL_SECTION" for vocal sections. melodic_structure: Melodic semiotic label lyric_structure: Lyrical semiotic label lyrics: Lyrics of the section slug: The processed version of "name" field with the Turkish characters and special characters handled.</p> <p>results.json stores the evaluation and the statistics of the experiments.</p> <p>To run the experiments you have to install Jupyter notebook and the requirements.</p> <p>For additional information please contact the authors.</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 12
- Reuse readiness
- 8
- Engagement
- 12