Department of
Computational
Perception
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Analysis of Musical Interpretation: Herbert von Karajan
Full Project Title: Towards Interdisciplinary, Computer-assisted Analysis of Musical Interpretation: A Study on the Art of Herbert von Karajan
Sponsor: Austrian Science Fund (Fonds zur Förderung der wissenschaftlichen Forschung, FWF)
Project Number: P 29840-G26
Duration: 36 months (June 2017 - June 2020)
Central Project Website
(hosted by the Eliette and Herbert von Karajan Institute)
Persons involved at our institute:
Project Partners
Abstract
The project sets out to accomplish a data-driven study in musical interpretation, connecting information from human analyses of a number of performances by Karajan, with algorithmically derived data spanning several decades of recordings. Although the project is conceived as a case study on Karajan, we wish to demonstrate the promise of data-intensive, interdisciplinary approaches to musicological studies of expressive performance, and help in establishing this as a new open standard approach in empirical musicology. Thus our goals are:
Our approach goes beyond already existing projects (e.g., the Mazurka Project) in that we focus, for the first time, exclusively on orchestral music conducted by a specific performance artist. In addition to musicological and computational research results, the project has access to a unique collection of largely unpublished music and extra-musical sources (hosted by the Karajan Institute, Salzburg): 1,800 digitized recordings from 1939 to 1989, 100 recordings of rehearsals, 700 studio recordings, 1,000 concert recordings, concert films, rehearsal documentaries, letters and phone conversations by Karajan about the production process. Musicological research will be performed along several lines, with the help of computational methods of performance analysis and visualisation:
In parallel, computational methods for performance analysis will be developed and/or further refined, in particular,
This is a truly inter-disciplinary project, involving experienced musicologists from music and arts universities, and computer scientists with extensive experience in computer-based music performance research.
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Journals
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