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To date, there are no systems that can identify symbolic music in a generic way. That is, it should be possible to associate the countless potential occurrences of a certain song with at least one generic description. The contribution of this paper is twofold: First, we sketch a generic model for music representation. Second, we develop a framework that correlates free symbolic piano performances with such a knowledge base. Based on detected pattern instances, the framework generates hypotheses for higher-level structures and evaluates them continuously. Thus, one or more hypotheses about the identity of such a music performance should be delivered and serve as a starting point for further processing stages. Finally, the framework is tested on a database of symbolic piano music.

KNOWLEDGE-BASED MINING OF PATTERNS AND STRUCTURE OF SYMBOLIC MUSIC FILES