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b290144670
Modular sub-engines computed amp_val as a pure function of mod_amp (the matrix d08_amp destination sum), so once the MLP drove the matrix cells every joystick movement had a chance to silence the voice: matrix cells have signed range [-1, 1], sigmoid outputs near 0.5 denormalise to 0, and the amp gate collapsed. Additive survived in scattered regions because it only has one kill-switch (d08_amp); subtractive and fm were almost always dead because they also have d05_cutoff and d01_op1_level. Two changes: 1. DSP: each sub-engine gets a base_amp hslider (default 1.0) so amp_val = clamp(base_amp + mod_amp) * level * vel_gain. At the default the voice is always fully open and d08_amp modulation is purely additive decoration; drop base_amp to 0 for classic ADSR-gated VCA behaviour. 2. ModularEngine._rebuildParamMeta: restore the _exposedMatrixCells gate (default empty). paramCount drops from 512 to 32 (4 ADSR * 4 + 8 LFO * 2); matrix cells are opt-in via setExposeMatrixCell. _applyDefaultPatch no longer writes s00_d08_amp since base_amp keeps the voice audible without routing. Tests updated for the new 32-param baseline; matrix-cell persistence test now calls setExposeMatrixCell(1, 5, true) before asserting the cell lands in paramMeta. Drive-by: engine-switching test bumped from 3 to 4 engine cards (stale since the modular engine was added). |
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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.