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

Frank Seifert

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.

References

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Paper Citation


in Harvard Style

Seifert F. (2010). KNOWLEDGE-BASED MINING OF PATTERNS AND STRUCTURE OF SYMBOLIC MUSIC FILES . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 358-363. DOI: 10.5220/0003118103580363


in Bibtex Style

@conference{kdir10,
author={Frank Seifert},
title={KNOWLEDGE-BASED MINING OF PATTERNS AND STRUCTURE OF SYMBOLIC MUSIC FILES },
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={358-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003118103580363},
isbn={978-989-8425-28-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - KNOWLEDGE-BASED MINING OF PATTERNS AND STRUCTURE OF SYMBOLIC MUSIC FILES
SN - 978-989-8425-28-7
AU - Seifert F.
PY - 2010
SP - 358
EP - 363
DO - 10.5220/0003118103580363