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. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Cabral, G., Pachet, F., & Briot, J. P. (2006). Recognizing chords with EDS: Part one. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3902 LNCS, pp. 185–195). https://doi.org/10.1007/11751069_17
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