Melody recognition with learned edit distances
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http://hdl.handle.net/10045/9690
Title: | Melody recognition with learned edit distances |
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Authors: | Habrard, Amaury | Iñesta, José M. | Rizo, David | Sebban, Marc |
Research Group/s: | Reconocimiento de Formas e Inteligencia Artificial |
Center, Department or Service: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Université de Provence. Laboratoire d’Informatique Fondamentale | Université de Saint-Etienne. Laboratoire Hubert Curien |
Keywords: | Edit distance learning | Music similarity | Genetic algorithms | Probabilistic models |
Knowledge Area: | Lenguajes y Sistemas Informáticos |
Date Created: | 2008 |
Issue Date: | 2008 |
Publisher: | Springer Berlin / Heidelberg |
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 |
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. |
Sponsor: | 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. |
URI: | http://hdl.handle.net/10045/9690 |
ISBN: | 978-3-540-89688-3 |
ISSN: | 0302-9743 (Print) | 1611-3349 (Online) |
DOI: | 10.1007/978-3-540-89689-0_13 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | The original publication is available at www.springerlink.com |
Peer Review: | si |
Publisher version: | http://dx.doi.org/10.1007/978-3-540-89689-0_13 |
Appears in Collections: | INV - GRFIA - Artículos de Revistas Research funded by the EU |
Files in This Item:
File | Description | Size | Format | |
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melody-rec.pdf | Versión final (acceso restringido) | 453,75 kB | Adobe PDF | Open Request a copy |
ssspr08_cr.pdf | Versión revisada (acceso libre) | 392,22 kB | Adobe PDF | Open Preview |
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