Harmony Generation Driven by a Perceptually Motivated Tonal Interval Space

Abstract

We present D'accord, a generative music system for creating harmonically compatible accompaniments of symbolic and musical audio inputs with any number of voices, instrumentation, and complexity. The main novelty of our approach centers on offering multiple ranked solutions between a database of pitch configurations and a given musical input based on tonal pitch relatedness and consonance indicators computed in a perceptually motivated Tonal Interval Space. Furthermore, we detail a method to estimate the key of symbolic and musical audio inputs based on attributes of the space, which underpins the generation of key-related pitch configurations. The system is controlled via an adaptive interface implemented for Ableton Live, MAX, and Pure Data, which facilitates music creation for users regardless of music expertise and simultaneously serves as a performance, entertainment, and learning tool. We perform a threefold evaluation of D'accord, which assesses the level of accuracy of our key-finding algorithm, the user enjoyment of generated harmonic accompaniments, and the usability and learnability of the system.