Improving Music Classification Using Harmonic Complexity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10272347" target="_blank" >RIV/00216208:11320/14:10272347 - isvavai.cz</a>

Výsledek na webu

<a href="http://artax.karlin.mff.cuni.cz/~bajel3am/itat2014/local/13_Marsik.pdf" target="_blank" >http://artax.karlin.mff.cuni.cz/~bajel3am/itat2014/local/13_Marsik.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Improving Music Classification Using Harmonic Complexity

Popis výsledku v původním jazyce

Publicly available multimedia systems provide users with plenty of music files offered in different genres. These systems should process the music as fast as possible while satisfying the needs of their users as well. In this context, reliable music classification represents one of the major challenges. Classification systems without deeper knowledge of music structure and composition yield to considerable errors. In some cases, music can not be classified clearly due to an overlap in genres. However, in other cases, we can clarify the classification simply by using the approach of a skilled musician. In this paper, we develop a new approach to automatic music classification inspired by the theory of neural networks, enhanced by deeper knowledge of tonal harmony. Based on a new measure derived from harmonic movements, harmonic complexity, our supporting experiments proved a significant improvement in classification accuracy.

Název v anglickém jazyce

Improving Music Classification Using Harmonic Complexity

Popis výsledku anglicky

Publicly available multimedia systems provide users with plenty of music files offered in different genres. These systems should process the music as fast as possible while satisfying the needs of their users as well. In this context, reliable music classification represents one of the major challenges. Classification systems without deeper knowledge of music structure and composition yield to considerable errors. In some cases, music can not be classified clearly due to an overlap in genres. However, in other cases, we can clarify the classification simply by using the approach of a skilled musician. In this paper, we develop a new approach to automatic music classification inspired by the theory of neural networks, enhanced by deeper knowledge of tonal harmony. Based on a new measure derived from harmonic movements, harmonic complexity, our supporting experiments proved a significant improvement in classification accuracy.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 14th conference Information Technologies - Applications and Theory (ITAT 2014) - Workshops and Posters

ISBN

978-80-87136-19-5

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

13-17

Název nakladatele

Ústav informatiky AV ČR

Místo vydání

Praha, Česká republika

Místo konání akce

Demänovská Dolina, Slovakia

Datum konání akce

25. 9. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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