Automatic x traditional descriptor extraction: The case of chord recognition

Giordano Cabral François Pachet 1 Jean-Pierre Briot 1
1 SMA - Systèmes Multi-Agents
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Audio descriptor extraction is the activity of finding mathematical models which describe properties of the sound, requiring signal processing skills. The scientific literature presents a vast collection of descriptors (e.g. energy, tempo, tonality) each one representing a significant effort of research in finding an appropriate descriptor for a particular application. The Extractor Discovery System (EDS) [1] is a recent approach for the discovery of such descriptors, which aim is to extract them automatically. This system can be useful for both non experts – who can let the system work fully automatically – and experts – who can start the system with an initial solution expecting it to enhance their results. Nevertheless, EDS still needs to be massively tested. We consider that its comparison with the results of problems already studied would be very useful to validate it as an effective tool. This work intends to perform the first part of this validation, comparing the results from classic approaches with EDS results when operated by a completely naïve user building a guitar chord recognizer.
Type de document :
Communication dans un congrès
ISMIR 2005 - 6th International Conference on Music Information Retrieval, Sep 2005, London, United Kingdom. University of London, ISMIR 2005 - 6th International Conference on Music Information Retrieval, pp.444-449
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https://hal.archives-ouvertes.fr/hal-01416436
Contributeur : Lip6 Publications <>
Soumis le : mercredi 14 décembre 2016 - 14:50:31
Dernière modification le : mercredi 21 mars 2018 - 18:58:11

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  • HAL Id : hal-01416436, version 1

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Giordano Cabral, François Pachet, Jean-Pierre Briot. Automatic x traditional descriptor extraction: The case of chord recognition. ISMIR 2005 - 6th International Conference on Music Information Retrieval, Sep 2005, London, United Kingdom. University of London, ISMIR 2005 - 6th International Conference on Music Information Retrieval, pp.444-449. 〈hal-01416436〉

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