Author:
Frank Seifert
Affiliation:
University of Technology, Germany
Keyword(s):
Mining Music Data, Song Detection, Pattern Recognition, Knowledge-Based Music Modelling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Information Extraction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Multimedia Data
;
Structured Data Analysis and Statistical Methods
;
Symbolic Systems
Abstract:
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.