Landmark-based music recognition system optimisation using genetic algorithms

  1. Gutiérrez, S. 3
  2. García, S. 12
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 King Abdulaziz University
    info

    King Abdulaziz University

    Jeddah, Arabia Saudí

    ROR https://ror.org/02ma4wv74

  3. 3 Instituto de Ciencias de la Vid y del Vino
    info

    Instituto de Ciencias de la Vid y del Vino

    Logroño, España

    ROR https://ror.org/01rm2sw78

Revista:
Multimedia Tools and Applications

ISSN: 1380-7501

Año de publicación: 2015

Volumen: 75

Número: 24

Páginas: 16905

Tipo: Artículo

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DOI: 10.1007/S11042-015-2963-0 SCOPUS: 2-s2.0-84944705639 WoS: WOS:000389604600009 GOOGLE SCHOLAR

Otras publicaciones en: Multimedia Tools and Applications

Resumen

Audio fingerprinting allows us to label an unidentified music fragment within a previously generated database. The use of spectral landmarks aims to obtain a robustness that lets a certain level of noise be present in the audio query. This group of audio identification algorithms holds several configuration parameters whose values are usually chosen based upon the researcher’s knowledge, previous published experimentation or just trial and error methods. In this paper we describe the whole optimisation process of a Landmark-based Music Recognition System using genetic algorithms. We define the actual structure of the algorithm as a chromosome by transforming its high relevant parameters into various genes and building up an appropriate fitness evaluation method. The optimised output parameters are used to set up a complete system that is compared with a non-optimised one by designing an unbiased evaluation model. © 2015 Springer Science+Business Media New York