Melody recognition with learned edit distances
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor | Reconocimiento de Formas e Inteligencia Artificial | en |
dc.contributor.author | Habrard, Amaury | - |
dc.contributor.author | Iñesta, José M. | - |
dc.contributor.author | Rizo, David | - |
dc.contributor.author | Sebban, Marc | - |
dc.contributor.other | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | en |
dc.contributor.other | Université de Provence. Laboratoire d’Informatique Fondamentale | en |
dc.contributor.other | Université de Saint-Etienne. Laboratoire Hubert Curien | en |
dc.date.accessioned | 2009-02-19T12:22:41Z | - |
dc.date.available | 2009-02-19T12:22:41Z | - |
dc.date.created | 2008 | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | HABRARD, Amaury, et al. "Melody recognition with learned edit distances". En: Structural, Syntactic, and Statistical Pattern Recognition : joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008 : proceedings. Berlin : Springer, 2008. (Lecture Notes in Computer Science; 5342/2008). ISBN 978-3-540-89688-3, pp. 86-96 | en |
dc.identifier.isbn | 978-3-540-89688-3 | - |
dc.identifier.issn | 0302-9743 (Print) | - |
dc.identifier.issn | 1611-3349 (Online) | - |
dc.identifier.uri | http://hdl.handle.net/10045/9690 | - |
dc.description.abstract | In a music recognition task, the classification of a new melody is often achieved by looking for the closest piece in a set of already known prototypes. The definition of a relevant similarity measure becomes then a crucial point. So far, the edit distance approach with a-priori fixed operation costs has been one of the most used to accomplish the task. In this paper, the application of a probabilistic learning model to both string and tree edit distances is proposed and is compared to a genetic algorithm cost fitting approach. The results show that both learning models outperform fixed-costs systems, and that the probabilistic approach is able to describe consistently the underlying melodic similarity model. | en |
dc.description.sponsorship | This work was funded by the French ANR Marmota project, the Spanish PROSEMUS project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018), and the Pascal Network of Excellence. | en |
dc.language | eng | en |
dc.publisher | Springer Berlin / Heidelberg | en |
dc.rights | The original publication is available at www.springerlink.com | en |
dc.subject | Edit distance learning | en |
dc.subject | Music similarity | en |
dc.subject | Genetic algorithms | en |
dc.subject | Probabilistic models | en |
dc.subject.other | Lenguajes y Sistemas Informáticos | en |
dc.title | Melody recognition with learned edit distances | en |
dc.type | info:eu-repo/semantics/article | en |
dc.peerreviewed | si | en |
dc.identifier.doi | 10.1007/978-3-540-89689-0_13 | - |
dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-540-89689-0_13 | - |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | - |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/216886 | - |
Aparece en las colecciones: | INV - GRFIA - Artículos de Revistas Investigaciones financiadas por la UE |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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melody-rec.pdf | Versión final (acceso restringido) | 453,75 kB | Adobe PDF | Abrir Solicitar una copia |
ssspr08_cr.pdf | Versión revisada (acceso libre) | 392,22 kB | Adobe PDF | Abrir Vista previa |
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