Papers for

electronic musicians

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Web tool maps microtonal chord space for new music creation

Harmonic Eigenspace: A Web-based Application for Navigating and Composing Microtonal Harmony

Abstract: This paper presents a web-based application for navigating and composing microtonal harmony, built on the Harmonic Eigenspace, a four-dimensional psychoacoustically grounded space in which tetrad chord types are located by their spectral dissonance profiles, computed with Sethares's roughness/dissonance model. The coordinate system is transposition-invariant: a coordinate triple (α, \b{eta}, γ) locates the three upper notes in relation to the root, so a chord quality corresponds to a direction in the space, the invariant ray along which transposition acts, while the root frequency sets the scale. The dissonance field over these coordinates can be computed at any register; the locations of its local minima are register-invariant, as they arise from partial-coincidence ratio conditions. The dissonance volume contains 100 local minima that align with just-intonation intervals and act as landmarks, organising the space into basins around the most consonant tetrads. We embed tetrads from three tonal equal temperaments as discrete lattices within this continuous volume. The application presents this space through two components: the Harmonic Eigenspace as a navigable 3D visualisation of the dissonance volume in which all nodes are playable, and a Modal Studio that extends modal interchange logic to the ten-gradation interval vocabulary of 53-TET. The application also functions as a MIDI controller with MIDI Polyphonic Expression support, usable in any digital audio workstation that supports this format. A listening study with 31 participants used both scenes of the application: listeners first rated isolated 53-TET chords alongside chords familiar from Western practice, such as the maj7 and the m7; they then rated chord progressions composed in the Modal Studio, measuring their acceptance or rejection of microtonal progressions heard for the first time.

Fri 2 OctSoundHuman-Computer Interaction
The gist
Some kinds of music use notes outside the standard 12 tones we usually hear, called microtonal music, which is hard to explore and compose with. The authors built a web app that shows all the possible four-note chords arranged in a special 3D space based on how dissonant or pleasant they sound. Users can hear and navigate this space to discover new harmonies and create music with many more intervals than usual. They also tested how people responded to these new chords and progressions, showing the app can help composers work with unfamiliar tones.
Open → 2610.03398v1

Neural networks synthesize controllable musical distortion tones in real time

Learned Continuous Synthesis of Quadratic Difference Tone Spectra

Abstract: Quadratic difference tones (QDTs) are a species of auditory distortion product in which a "phantom" pure tone, absent from the acoustic signal, is clearly audible to listeners. Exploiting this phenomenon, one can synthesize harmonically rich tones for musical purposes, a technique called Quadratic Difference Tone Spectrum (QDTS) synthesis. Previous works have introduced numerical methods to synthesize QDTS based on the distortion function, which links a target QDTS and an overtone-structured carrier signal. While accurate, these methods were stochastic and discontinuous, making them difficult to control for musical purposes and effectively limiting them to stationary signals. This paper proposes a neural network-based approach that learns an approximate inverse of the distortion mapping in an autoencoder-like configuration, producing a continuous approximation that addresses prior limitations. Experimental results show that, although slightly less numerically precise, the method is sufficient for perceptual and musical applications. We also implement a real-time version in Max and evaluate its performance. Various sound examples demonstrate its expressive and musical potential. The source code, audio examples, tutorials, and software accompanying this work are available at https://cordutie.github.io/projects/qdts.html

Wed 9 SeptSound
The gist
Sometimes, people hear extra tones called quadratic difference tones (QDTs) that aren't actually played but are created by the ear. These tones can make music sound richer and more interesting. The authors created a neural network that learns how to produce these tones more smoothly and continuously, overcoming problems in older methods that were harder to control and only worked on steady sounds. While this new method is slightly less precise in calculations, it sounds good enough for making music and runs in real time. They also made easy-to-use software so musicians can try it out.
Open → 2609.10913v1