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
Figure 1: Psychoacoustic landscape around 220 Hz. (A) Harmonicity H01 ; (B) roughness R01 ; (C) consonance field Cfield ; (D) consonance density Cdensity . Grey: 0.5-oct grid; dashed: integer ratios. Simple-ratio peaks in H and troughs in R create attractor structure in both views. Reduced density outside ±1 oct is a finite-order property ( N=16 ).
Figure 2: Consonance search. Top —(A) Mean LOO consonance Cscore over time (95% CI); vertical line = phase switch, shaded band = burn-in excluded from statistics. (B) Scene consonance G(F) (Eq. 5 ) after singleton subtraction (95% CI). (C) Representative local-search trajectories (cents from drone). (D) Final unique pitch bins (95% CI). Bottom —(E) Pairwise interval histogram (25 ct bins): local-search concentrates mass at consonant intervals; random-walk spreads broadly. (F) Entropy of the 5 ct interval distribution (95% CI).
Figure 3: Consonance as selection pressure. (A, B) Kaplan–Meier survival by early consonance ( CfirstK ) median split: with recharge, high-consonance agents survive longer; without recharge, the separation disappears. (C, D) Lifetime versus early consonance shows the same contrast. Curves pool events across 20 seeds for display; inference is seed-level ( n=20 ).
Search
Selection
Heredity
Entrainment
Main figure
Fig. 2
Fig. 3
Fig. 4
Fig. 5
N agents
24
32
16
32
Seeds
20
20
20
20
Hill climb
abl.
×
×
×
Crowding
✓
×
✓
×
Metabolism
×
abl.
abl.
×
Table 1: Experiment conditions. ✓/× = on/off; abl. = ablated (compared with both states). Results are discussed in the order consonance search, selection, hereditary adaptation, and temporal scaffolding. All experiments use a fixed 220 Hz reference; in the consonance-search assay this is realised as a fixed drone.
Figure 4: Hereditary adaptation through lineage-biased respawn and metabolic selection (20 matched seeds, 4 conditions). (A) Mean leave-one-out contextual Cscore over simulation steps (95% CI). (B) Pitch heatmap for heredity + selection over simulation steps. (C) Final leave-one-out contextual Cscore by condition (95% CI). (D) Final just-intonation proximity score by condition (95% CI). Teal denotes heredity and rose denotes matched random; dark colors indicate selection-on and light colors indicate no-selection.
Figure 5: Temporal scaffold assay (20 seeds × 3 conditions). (A) Group mean PLV to the canonical 2 Hz (120 BPM) beat over time (95% CI). (B) Seed-averaged onset phase histogram relative to the canonical beat (bin probabilities normalized within seed, then averaged across seeds; shaded bands indicate 95% CI across seeds). (C) Seed-level onset vector strength: shared rhythm produces the strongest phase concentration, scrambled forcing is weaker, and off is lowest.
This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The proposed system combines quantum-inspired candidate exploration over overlapping melodic contexts with explicit rule-based optimization to balance generative flexibility and structural control. The architecture is evaluated using explicit and reproducible metrics covering structural coherence, functional agreement, harmonic similarity, and robustness. The results show that the proposed approach produces harmonizations that preserve tonal structure and cadential behavior while allowing multiple valid harmonic realizations. Furthermore, the optimization layer improves structural coherence, stability, and predictability without requiring a training corpus. The study demonstrates that transparent and controllable hybrid generative systems can be systematically designed and evaluated within the context of Information Systems Development.
Josef Pavlicek
Czech Technical University in Prague / Faculty of Information technology / Department of Software Engineering Prague/ Czech Republic
I show how to evoke the pitch-class content of a chord from an arbitrary source sound by convolving the source with an impulse response whose grains are one windowed sinusoid per pitch-class, across each octave of hearing range; while, at the same time, minimizing artifacts. A Csound user-defined opcode, chord_convolver, mixes a dry Dirac component into that response, and applies partitioned convolution once. I contrast the effect with a linear-frequency comb filter and with a generic constant-Q resonator bank, and I demonstrate musical use on a twilight field recording alongside the ruins of Chateau de Lagarde.
I present the generation and analysis of the largest known open-source corpus of playable piano chords (approximately 19.3 million entries). This dataset enumerates the two-handed search space subject to biomechanical constraints (two hands, each with 1.5 octave reach) to an unprecedented extent. To demonstrate the corpus's utility, the relationship between voicing shape and psychoacoustic targets was modeled. Harmonicity proved intrinsic to pitch-class identity: voicing statistics added negligible variance (ΔR2≈0.014%, p≈0.13). Conversely, voicing significantly predicted dissonance (ΔR2≈6.75%, p≈0.0008). Crucially, skewness (β≈+0.145) was approximately 5.8× more effective than spread (β≈−0.025) at predicting roughness. The analysis challenges the pedagogical emphasis on spread'': skewness is a stronger predictor of dissonance than spread. This suggests that clarity in open voicings'' is driven less by width than by negative skewness; achieving lower-register clearance by placing wide gaps at the bottom and allowing tighter clustering in the treble. The results demonstrate the corpus's ability to enable future research, especially in areas such as generative modeling, voice-leading topology, and psychoacoustic analysis.