Creating Parts from MEI-Encoded Musical Scores: Encoding Guidelines and a Part-Extraction Tool
Musical performance requires the availability of individual instrumental or vocal parts from a full score. While it is possible to manually encode a score and its parts separately, automating this process is more efficient. This can be achieved through two converse methodologies: either by encoding...
Salvato in:
| Pubblicato in: | URI:https://journals.openedition.org/jtei, |
|---|---|
| Autore principale: | |
| Natura: | Article ou chapitre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Journal of the Text Encoding Initiative
2025
|
| Soggetti: | |
| Accesso online: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Riassunto: | Musical performance requires the availability of individual instrumental or vocal parts from a full score. While it is possible to manually encode a score and its parts separately, automating this process is more efficient. This can be achieved through two converse methodologies: either by encoding the full score first and then extracting the parts, or by encoding the parts first and then combining them into a score. For both purposes, however, the tools available within the Music Encoding Initiative (MEI) are limited. This paper explores the concept of extracting parts from a score. The foundation for this is a consistent and semantically coherent encoding. So far, however, when encoding parts in a score, the available MEI encodings have focused mainly on the visual representation. A key challenge arises from the common engraving practice of notating multiple parts on a single staff, such as two clarinets sharing one staff. While the encoding of such parts should enable the score to be rendered in accordance with established engraving conventions, for automatic processing the semantic independence of the parts needs to be captured. To address these challenges, the paper proposes guidelines for encoding musical scores within the MEI framework, developed by the Digital Mozart Edition (DME). In addition, the DME is providing the MEI community with a part-extraction tool that uses the encoding structure outlined in these guidelines. This tool marks a significant advance in MEI-based score management and creates new opportunities for digital scholarly editing and performance preparation. |
|---|