Jazz Contrafact Detection
This work addresses a domain-specific problem in music informatics for jazz analysis, with incremental improvements in harmonic similarity detection.
The paper tackled the challenge of detecting jazz contrafacts, which involve new melodies over reharmonized chord progressions, by developing a novel vector-space model with a membrane area distance metric, and demonstrated its effectiveness on a corpus of 2,612 chord progressions.
In jazz, a contrafact is a new melody composed over an existing, but often reharmonized chord progression. Because reharmonization can introduce a wide range of variations, detecting contrafacts is a challenging task. This paper develops a novel vector-space model to represent chord progressions, and uses it for contrafact detection. The process applies principles from music theory to reduce the dimensionality of chord space, determine a common key signature representation, and compute a chordal co-occurrence matrix. The rows of the matrix form a basis for the vector space in which chord progressions are represented as piecewise linear functions, and harmonic similarity is evaluated by computing the membrane area, a novel distance metric. To illustrate our method's effectiveness, we apply it to the Impro-Visor corpus of 2,612 chord progressions, and present examples demonstrating its ability to account for reharmonizations and find contrafacts.