Research data from the thesis "Computational Analysis of Audio Recordings and Music Scores for the Description and Discovery of Ottoman-Turkish Makam Music".

Tomato is a comprehensive and easy-to-use toolbox in Python for the analysis of audio recordings and music scores of Turkish-Ottoman makam music. The toolbox includes the state of art methodologies applied on this music tradition. The analysis tasks include: * Audio Analysis: audio metadata crawling, predominant melody extraction, tonic and transposition identification, makam recognition, histogram analysis, tuning analysis, melodic progression analysis * Symbolic Analysis: score metadata extraction, score section extraction, score phrase segmentation, semiotic section and phrase analysis * Joint Analysis: score-informed tonic identification and tempo estimation, section linking, note-level audio-score alignment, predominant melody octave correction, note models, (usul tracking is coming soon) The aim of the toolbox is to facilitate the analysis of large-scale audio recording and music score collections of Turkish-Ottoman makam music, using the state of the art methodologies specifically designed for the culture-specific characteristics of this tradition. The analysis results can then be further used for several tasks such as automatic content description, music discovery/recommendation and musicological analysis.