Abstract
This chapter examines questions of what is to be analysed in computational music analysis, what is to be produced, and how one can have confidence in the results. These are not new issues for music analysis, but their consequences are here considered explicitly from the perspective of computational analysis. Music analysis without computers is able to operate with multiple or even indistinct conceptions of the material to be analysed because it can use multiple references whose meanings shift from context to context. Computational analysis, by contrast, must operate with definite inputs and produce definite outputs. Computational analysts must therefore face the issues of error and approximation explicitly. While computational analysis must retain contact with music analysis as it is generally practised, I argue that the most promising approach for the development of computational analysis is not systems to mimic human analysis, but instead systems to answer specific music-analytical questions. The chapter concludes with several consequent recommendations for future directions in computational music analysis.
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Keywords
- Computational Analysis
- Kolmogorov Complexity
- Music Notation
- Music Perception
- Music Information Retrieval
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Marsden, A. (2016). Music Analysis by Computer: Ontology and Epistemology. In: Meredith, D. (eds) Computational Music Analysis. Springer, Cham. https://doi.org/10.1007/978-3-319-25931-4_1
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