Recognizing chords with EDS: Part one

Giordano Cabral François Pachet 1 Jean-Pierre Briot 1
1 SMA - Systèmes Multi-Agents
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : This paper presents a comparison between traditional and automatic approaches for the extraction of an audio descriptor to recognize chord into classes. The traditional approach requires signal processing (SP) skills, constraining it to be used only by expert users. The Extractor Discovery System (EDS) [1] is a recent approach, which can also be useful for non expert users, since it intends to discover such descriptors automatically. This work compares the results from a classic approach for chord recognition, namely the use of KNN-learners over Pitch Class Profiles (PCP), with the results from EDS when operated by a non SP expert.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01336914
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Submitted on : Friday, June 24, 2016 - 10:58:53 AM
Last modification on : Thursday, March 21, 2019 - 1:07:29 PM

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Giordano Cabral, François Pachet, Jean-Pierre Briot. Recognizing chords with EDS: Part one. Computer Music Modeling and Retrieval: Third International Symposium, CMMR 2005. Revised Papers International Symposium on Computer Music Modeling and Retrieval, Sep 2005, Pisa, Italy. pp.185-195, ⟨10.1007/11751069_17⟩. ⟨hal-01336914⟩

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