MEI2JSON: a pre-processing music scores converter. (13th December 2021) - Achkar, Charbel El; Atéchian, Talar
Converting music score content from symbolic formats to simplified data formats is found useful for artificial intelligence purposes. The conversion can be applied using XSL stylesheets and ontologies to ensure the preserving of the data quality throughout the transformation. In this paper, we proposed a new converter capable of transforming music scores encoded in MEI to JSON format for pre-processing purposes, and future usage into artificial intelligence techniques. The proposed converter uses an eastern music score ontology capable of structuring standard music scores content in addition to elements and attributes specific to eastern music. Thus, the converter shares the same support for eastern music scores. We illustrate the conversion process by assessing the performance analysis, the data quality, and the storage of the proposed converter in comparison with a combined approach composed of two state-of-the-art converters.