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Automatic Chord-Scale Recognition Using Harmonic Pitch Class Profiles

Title Automatic Chord-Scale Recognition Using Harmonic Pitch Class Profiles
Publication Type Conference Paper
Year of Publication 2019
Conference Name Sound and Music Computing Conference
Authors Demirel, E. , Bozkurt B. , & Serra X.
Pagination 72-79
Conference Start Date 28/05/2019
Conference Location Malaga, Spain
Abstract This study focuses on the application of different computational methods to carry out a ”modal harmonic analysis” for Jazz improvisation performances by modeling the concept of chord-scales. The Chord-Scale Theory is a theoretical concept that explains the relationship between the harmonic context of a musical piece and possible scale types to be used for improvisation. This work proposes different computational approaches for the recognition of the chordscale type in an improvised phrase given the harmonic context. We have curated a dataset to evaluate different chordscale recognition approaches proposed in this study, where the dataset consists of around 40 minutes of improvised monophonic Jazz solo performances. The dataset is made publicly available and shared on To achieve the task of chord-scale type recognition, we propose one rule-based, one probabilistic and one supervised learning method. All proposed methods use Harmonic Pitch Class Profile (HPCP) features for classification. We observed an increase in the classification score when learned chordscale models are filtered with predefined scale templates indicating that incorporating prior domain knowledge to learned models is beneficial. This study has its novelty in presenting a first computational analysis on chord-scales in the context of Jazz improvisation.
preprint/postprint document