Assistive Model to Generate Chord Progressions Using Genetic Programming with Artificial Immune Properties

Abstract

In Western tonal music, tension in chord progressions plays an important role in defining the path that a musical composition should follow. The creation of chord progressions that reflects such tension profiles can be challenging for novice composers, as it depends on many subjective factors, and also is regulated by multiple theoretical principles. This work presents ChordAIS-Gen, a tool to assist the users to generate chord progressions that comply with a concrete tension profile. We propose an objective measure capable of capturing the tension profile of a chord progression according to different tonal music parameters, namely, consonance, hierarchical tension, voice leading and perceptual distance. This measure is optimized into a Genetic Program algorithm mixed with an Artificial Immune System called Opt-aiNet. Opt-aiNet is capable of finding multiple optima in parallel, resulting in multiple candidate solutions for the next chord in a sequence. To validate the objective function, we performed a listening test to evaluate the perceptual quality of the candidate solutions proposed by our system. Most listeners rated the chord progressions proposed by ChordAIS-Gen as better candidates than the progressions discarded. Thus, we propose to use the objective values as a proxy for the perceptual evaluation of chord progressions and compare the performance of ChordAIS-Gen with chord progressions generators.

Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening

“…Several papers in this special issue deal with music-related tasks such as the generation of bass scores [7], chord progressions [8], and the analysis of rhythmic patterns [9].…”

“…In Navarro-Caceres et al [8] the authors propose an assistive music composition system that is able to satisfy multiple criteria and find multiple candidates in chord sequence generation using an Artificial Immune System, a biologically inspired AI technique based on Genetic Programming for multi-objective optimisation. The generated chord progressions fit a desired tonal tension profile, taking for instance consonance or the melodic attraction of successive chords into account, thus aiding the composition process.…”