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0a5f2544ca
Faust DSP sources, compiled WASM + JSON descriptors, AudioWorklet processors, and EOCModule subclasses for all three effects. - meml-4b4: 4-band parametric EQ (fi.low_shelf, fi.peak_eq × 2, fi.high_shelf) 10 params: freq/gain per band, Q for the two mid bell bands - meml-cpe: stereo feed-forward compressor (co.compressor_mono × 2) 7 params: threshold, ratio, attack, release, knee, makeup, mix (parallel) - meml-wwc: zita reverb (re.zita_rev1_stereo) with pre-delay and M/S width 8 active params + mod_rate placeholder (zita internal mod not yet exposed) All three DSPs compile cleanly under Faust 2.83.1. moduleFactory in eoc-chain-ui.js now returns real instances for eq/compressor/reverb. |
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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.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.