Conchordal: Emergent Harmony via Direct Cognitive Coupling in a Psychoacoustic Landscape
Organizations: Institute for Advanced Biosciences and Graduate School of Media and Governance, Keio University
Abstract
This paper introduces Conchordal, a bio-acoustic instrument for generative composition whose sonic agents are governed by artificial life dynamics within a psychoacoustic fitness landscape. The system is built on Direct Cognitive Coupling (DCC), a design principle requiring that generative dynamics operate directly within a landscape derived from psychoacoustic observables and read from that landscape without symbolic harmonic rules. The environment integrates roughness and harmonicity into a continuous consonance field without presupposing discrete scales or explicit harmonic rules. Agents adjust pitch through local proposal-and-accept dynamics under a crowding penalty, regulate survival via consonance-dependent metabolism, and entrain temporally through Kuramoto-style phase coupling. Four experiments are reported: (1) consonance search produces structured polyphony with enriched consonant intervals; (2) consonance-dependent metabolism yields survival differentials that vanish when recharge is disabled; (3) a minimal hereditary adaptation assay shows that parent-guided respawn plus metabolic selection can accumulate more structured polyphony without adult hill-climbing; and (4) a shared oscillatory scaffold organizes rhythmic timing under external forcing. A supplementary mechanism check reports one possible composer-configurable bridge by which spectral state can modulate temporal coupling. These findings show that a psychoacoustically derived landscape serves as an effective artificial-life terrain, yielding self-organization, selection, synchronization, and lineage-level accumulation in a non-traditional computational medium. At the level of the model, the same landscape therefore functions both as ecological terrain and as an internal proxy for musical coherence.
Figures & tables
| Search | Selection | Heredity | Entrainment | |
| Main figure | Fig. 2 | Fig. 3 | Fig. 4 | Fig. 5 |
| agents | 24 | 32 | 16 | 32 |
| Seeds | 20 | 20 | 20 | 20 |
| Hill climb | abl. | × | × | × |
| Crowding | ✓ | × | ✓ | × |
| Metabolism | × | abl. | abl. | × |
Music Generation
Music generation studies computational methods for composing, synthesizing, and editing music from symbolic, audio, textual, and multimodal inputs.
See all 107 papers