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afff406d92
New "Modular" engine in a-immersive with three hot-swappable Faust sub-engines (subtractive/additive/fm) sharing a common modulation pool: 16 ADSR slots + 32 LFO slots (single-knob sine->tri->square->saw wavemorph) routed through a 48-source x 10-destination matrix per engine. Per-connection scalar amounts in [-1, 1], summed at each destination. Default MLP output count is 512 (32 mod-source params + 480 matrix cells); model reinits on sub-engine swap, count change, or engine-param exposure toggle. Faust layer: - mod-pool.lib: shared ADSR/LFO/source-bus library - gen-modular-dsp.py: byte-reproducible generator (source of truth) - modular-subtractive: faithful Minimoog (3 osc, ladder filter, no envs) - modular-additive: 64-partial, spectral shape + formants, no envs/LFOs - modular-fm: 4-op matrix + self-feedback, no envs - All three share d08=amp, d09=pan conventions - MODULAR_DESTINATIONS.md: authoritative destination table JS layer: - ModularEngine: self-contained SynthEngine with getState/setState, setSubEngine, setModSourceCount, setExposeEngineParam - modular-ui: drawer with sub-engine toggle, ADSR/LFO count steppers, per-slot enable switches, matrix grid editor (tap-cycle, long-press precise, right-click menu, negative amounts), preset overlay - modular-presets: 6 named presets (Slow pad, Plucky bass, Crystal, DX bell, Morphing drone + default) - a-app.js: Modular mode registered, paramMeta:change -> resizeMLP, modular DSP state persisted under modularDspState, window.__nisps debug hooks for programmatic control Tests: tests/e2e/modular-mode.spec.js (11 Playwright tests, all passing including DSP state survives reload, sub-engine swap keeps paramCount, preset apply verification). Also fixes a pre-existing build.sh bug where the -e flag caused faust to overwrite .wasm outputs with expanded DSP source text, leaving additive/fm-matrix/eoc-* committed as invalid WebAssembly. Rebuilt all affected engines with the corrected script. Added an early-message buffer to faust-worklet-processor.js so setParam calls arriving before wasm instantiation are queued rather than dropped (needed when the user configures modular state before clicking Start Audio). |
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| .beads | ||
| .claude/worktrees/agent-ae87fe47/playground/js/shapeseq | ||
| .github/workflows | ||
| .vscode | ||
| data | ||
| modes | ||
| nisps-core | ||
| playground | ||
| src | ||
| tests/e2e | ||
| vcv | ||
| voicespaces | ||
| .gitignore | ||
| .gitmodules | ||
| AGENTS.md | ||
| ChannelStripAudioApp.hpp | ||
| CLAUDE.md | ||
| IMLInterface.hpp | ||
| LICENSE | ||
| MEMLNaut-NISPS.ino | ||
| NISPS_CORE_EXTRACTION_PLAN.md | ||
| NISPS_CORE_TASKS.md | ||
| package-lock.json | ||
| package.json | ||
| PAFSynthAudioApp.hpp | ||
| playwright.config.js | ||
| README.md | ||
| ThruAudioApp.hpp | ||
| XiasriAnalysis.cpp | ||
| XiasriAnalysis.hpp | ||
| XIASRIAudioApp.hpp | ||
Neural Interactive Shaping of Parameter Spaces
https://musicallyembodiedml.github.io/memlnaut/approaches/nisps
Web Playground
Try NISPS in your browser — no hardware required:
cd playground
python3 -m http.server
# Open http://localhost:8000
Train a neural network to map joystick positions to generative visuals through interactive machine learning. Two learning modes: direct example mapping and reinforcement learning with thumbs up/down feedback.
The playground UI includes an Expand toggle on the visual surface so you can make the canvas nearly full-screen while compressing parameter/control panels into a minimal strip beneath it.