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Recognizing Chords with EDS: Part One

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 3902)

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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© 2006 Springer-Verlag Berlin Heidelberg

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Cabral, G., Pachet, F., Briot, JP. (2006). Recognizing Chords with EDS: Part One. In: Kronland-Martinet, R., Voinier, T., Ystad, S. (eds) Computer Music Modeling and Retrieval. CMMR 2005. Lecture Notes in Computer Science, vol 3902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751069_17

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  • DOI: https://doi.org/10.1007/11751069_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34027-0

  • Online ISBN: 978-3-540-34028-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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