doi: 10.7763/IJMO.2012.V2.93
Learning Singer-Specific Performance Rules
Maria Cristina Marinescu
1
,
Rafael Ramirez
2
- 1 Universidad Carlos III de Madrid, Department of Computer Science, and Leganes 28911, Spain.
- 2 Universitat Pompeu Fabra, Music Technology Group, Barcelona 08018, Spain.
Abstract
This work investigates how opera singers manipulate timing in order to produce expressive performances that have common features but also bear a distinguishable personal style. We characterize performances not only relative to the score, but also consider the contribution of features extracted from the libretto. Our approach is based on applying machine learning to extract singer-specific patterns of expressive singing from performances by Josep Carreras and Placido Domingo. We compare and contrast some of these rules, and we draw some analogies between them and some of the general expressive performance rules existing in the literature.
Keywords
- Expressive performance
- machine learning
- timing model
How to Cite
Maria Cristina Marinescu and Rafael Ramirez, "Learning Singer-Specific Performance Rules," International Journal of Modeling and Optimization, vol. 2, no. 2, pp. 97-102, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.93
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).