Landmark-based music recognition system optimisation using genetic algorithms
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.
| Main Authors: | , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Published: |
Springer
2016-12
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| Subjects: | Audio fingerprinting: Parameter optimisation, Genetic algorithms, Music recognition, |
| Online Access: | http://hdl.handle.net/10261/146534 http://dx.doi.org/10.13039/501100003329 |
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