Abstract
For the analysis of symbolic corpora of early music we depend on existing datasets, such as the Josquin Research Project and the
CantusCorpus, or encodings in community-created resources like IMSLP and CPDL. The choice of compositions presented in these
datasets is highly dependent on the scope of the project and/or the preferences of the contributors. As a consequence, they exhibit a
selection bias that makes it hard to use them to answer a variety of musicological questions. To mitigate this problem, we propose a
method, using RISM, DIAMM among other resources to compile a dataset that is more representative of the actual repertoire.
CantusCorpus, or encodings in community-created resources like IMSLP and CPDL. The choice of compositions presented in these
datasets is highly dependent on the scope of the project and/or the preferences of the contributors. As a consequence, they exhibit a
selection bias that makes it hard to use them to answer a variety of musicological questions. To mitigate this problem, we propose a
method, using RISM, DIAMM among other resources to compile a dataset that is more representative of the actual repertoire.
| Original language | English |
|---|---|
| Pages | 1-1 |
| Number of pages | 1 |
| Publication status | Published - 6 Jul 2024 |
| Event | MedRen conference: International Medieval and Renaissance Music Conference - Escuela Técnica Superior de Arquitectura, Granada, Spain Duration: 6 Jul 2024 → 9 Jul 2024 https://www.medren2024.com/ |
Conference
| Conference | MedRen conference |
|---|---|
| Abbreviated title | MedRen |
| Country/Territory | Spain |
| City | Granada |
| Period | 6/07/24 → 9/07/24 |
| Internet address |
Keywords
- Renaissance Music
- computational musicology
- corpus creation