Recognizing Chords with EDS: Part One

  • Giordano Cabral
  • François Pachet
  • Jean-Pierre Briot
Conference paper

DOI: 10.1007/11751069_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3902)
Cite this paper as:
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

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Giordano Cabral
    • 1
  • François Pachet
    • 2
  • Jean-Pierre Briot
    • 1
  1. 1.Laboratoire d’Informatique de Paris 6ParisFrance
  2. 2.Sony Computer Science LabParisFrance

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