Voice and Landscape — Sound–Environment Feedback

A Voice routed to the habitat bus changes the Landscape. The changed Landscape then affects placement, movement, and viability. This chapter traces that runtime feedback path and the energy, death, and respawn processes it supports.

Voice bodies
    |-- presentation bus --> listener / Listener Twin
    |
    `-- habitat bus --> Landscape --> placement, movement, viability
                              ^                         |
                              `------ new sound <------'

By default every voice feeds both buses, so the audience and the ecology share the same physical event. Routing can split them deliberately; see Routing and the Listener Twin.

From sound to terrain

The Landscape analyzes the habitat bus in log-frequency space and computes:

• roughness potential: interference and beating within critical bands;
• harmonicity potential: periodicity and support for virtual roots;
• Consonance Field: the combined terrain used to evaluate candidate frequencies.

A voice changes the spectrum on the habitat bus, which changes these scans. That is why consonance(...).peak() does not return a fixed scale degree: its answer depends on what is sounding now.

Score, level, mass, and density

Several representations are derived from the same terrain. They are related, but they are not interchangeable.

.peak() selects an extremum. The default density placement samples a PMF, so several voices can form a cloud around supported regions instead of collapsing onto one bin. tension(degree) targets a field-score step below the strongest peak. A viability window reads a bounded or environment-relative fit signal.

The suffixes in reports preserve the same distinction: for example, mean_c_field_score and mean_c_field_level are different quantities.

Placement is not movement

Placement answers where a voice enters. Pitch behavior answers what happens after entry.

let fixed_strain = harmonic()
    .amp(0.035)
    .sustain()
    .anchor();

let resolving_strain = harmonic()
    .amp(0.035)
    .sustain()
    .seek_consonance()
    .glide(0.4);

section("two responses to dissonance", || {
    place(fixed_strain, dissonance(140.0, 900.0).count(3));
    place(resolving_strain, dissonance(140.0, 900.0).count(3));
    wait(6.0);
});

Both Populations enter a dissonant region. One holds it; the other treats it as a starting point for resolution.

Evaluate the environment, not the self

A voice contributes energy to the field it later evaluates. Without care, a strong voice could appear viable merely because it hears its own footprint. consonance_viability() therefore enables environment-relative evaluation by default: the system approximately removes the voice’s own contribution before judging its fit.

This is a survival rule, not a routing rule. The voice may still feed the habitat bus and reshape the terrain for every other voice. Use viability_scope("total") only when the intended question is explicitly whether the voice fits the total field including itself.

Energy, death, and replacement

The ecological lifecycle belongs to brain("entrain"). Its energy is normalized to 0..1:

1. endurance(seconds) establishes the nominal zero-fit lifetime.
2. Each attack spends attack_cost_fraction.
3. A consonant attack can restore up to attack_recharge_fraction.
4. recovery(seconds) enables continuous recovery; the viability window determines how much of that recovery is available at the current pitch.
5. At zero energy the voice dies and enters its release tail.
6. If a respawn policy exists, the Population may create a replacement.

let settlement = consonance(70.0, 1100.0).spacing(0.8);

let ecology = harmonic()
    .brain("entrain")
    .entrained()
    .cycles(2)
    .seek_consonance()
    .endurance(8.0)
    .recovery(4.0)
    .attack_cost_fraction(0.017)
    .attack_recharge_fraction(0.70)
    .consonance_viability(0.32, 0.82)
    .respawn_consonance()
    .respawn_capacity(8)
    .respawn_settle(settlement);

place(ecology, consonance(70.0, 1100.0).count(8));
wait(20.0);

Respawn policies answer different compositional questions:

• respawn_random() creates no parent lineage. Candidates come from the Population’s original Placement and are weighted by the current scene score; it is not uniform random placement.
• respawn_hereditary(sigma_oct) selects a living parent by energy, proposes offspring near it, and keeps the candidate with the best current Field level.
• respawn_consonance() selects an energy-weighted living parent and chooses among high field-score peaks with a bias around that parent.
• respawn_capacity(n) bounds how many living members the Population maintains; without it, the founder count is the capacity, and an explicit value cannot be lower than that founder count.
• respawn_settle(placement) adds candidates from that Placement; the respawn policy’s own baseline still contributes one candidate.

Respawn preserves the Population and its population_id while individual voice_id and generation values change. The report stream makes that turnover observable.

Runtime feedback and human revision

Two different processes are involved:

• Runtime feedback is automatic: sound reshapes the terrain, which changes voice behavior and survival.
• Human revision happens between runs: run, listen, inspect a report, revise the scenario, and run again.

The practical run-and-revise procedure is described in Performance.