Abstract
The paper gives an overview of an inter-disciplinary research project whose goal is to elucidate the complex phenomenon of expressive music performance with the help of machine learning and automated discovery methods. The general research questions that guide the project are laid out, and some of the most important results achieved so far are briefly summarized (with an emphasis on the most recent and still very speculative work). A broad view of the discovery process is given, from data acquisition issues through data visualization to inductive model building and pattern discovery. It is shown that it is indeed possible for a machine to make novel and interesting discoveries even in a domain like music. The report closes witha few general lessons learned and withth e identification of a number of open and challenging research problems.
The full version of this paper is published in the Proceedings of the 5th International Conference on Discovery Science, Lecture Notes in Artificial Intelligence Vol. 2534
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© 2002 Springer-Verlag Berlin Heidelberg
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Widmer, G. (2002). In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project. In: Cesa-Bianchi, N., Numao, M., Reischuk, R. (eds) Algorithmic Learning Theory. ALT 2002. Lecture Notes in Computer Science(), vol 2533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36169-3_5
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DOI: https://doi.org/10.1007/3-540-36169-3_5
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