| Títol: | Melody recognition with learned edit distances |
| Autors: | Habrard, Amaury | Iñesta Quereda, José Manuel | Rizo Valero, David | Sebban, Marc |
| Grups d'investigació o GITE: | Reconocimiento de Formas e Inteligencia Artificial |
| Centre, Departament o Servei: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Université de Provence. Laboratoire d’Informatique Fondamentale | Université de Saint-Etienne. Laboratoire Hubert Curien |
| Paraules clau: | Edit distance learning | Music similarity | Genetic algorithms | Probabilistic models |
| Àrees de coneixement: | Lenguajes y Sistemas Informáticos |
| Data de creació: | 2008 |
| Data de publicació: | 2008 |
| Editor: | Springer Berlin / Heidelberg |
| Citació bibliogràfica: | 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 |
| Resum: | 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. |
| Patrocinadors: | 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 |
| Idioma: | eng |
| Tipus: | info:eu-repo/semantics/article |
| Drets: | The original publication is available at www.springerlink.com |
| Revisió científica: | si |
| Versió de l'editor: | http://dx.doi.org/10.1007/978-3-540-89689-0_13 |
| Apareix a la col·lecció: | INV - GRFIA - Artículos de Revistas
Investigacions finançades pel FP7 de la UE
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