Merge Examples/RL tabs into single unified toolbar across all four UIs.
Users can now freely mix supervised learning (Add Example + Train) with
RL feedback (thumbs up/down) without switching modes. Param bar dragging
is always enabled.
Add Web MIDI input module (js/synth/midi-input.js) for external MIDI
controllers — routes note on/off to C15 synth, CC 1/2 to joystick.
Add gamepad module (js/ui/gamepad.js) with auto-detection, deadzone,
and axis normalization across all UIs.
Fix synth parameter sync: routeOutputs() now called after trainModel()
in onThumbsUp and loadState to prevent stale params on first joystick
move. Add separate Clear Examples button (dataset only, keeps weights).
Control all sonically meaningful C15 parameters through NISPS ML outputs.
Excludes hardware routing, macros, scale/tuning, key tracking, velocity,
envelope mod depths, discrete switches, and dangerous volume/pitch params.
- Expand param-map.js with 126 curated params grouped by synthesis section
- Widen MLP architecture from [3,10,10,14,20] to [3,32,48,64,126]
- Add ParamDisplay.rebuild() for mode-dependent bar count (20 visual, 126 synth)
- Add scrollable compact layout for synth mode param bars
- Pad visual presets and old saves to 126 outputs for backward compatibility
Adds a secondary Synth mode (toggled via collapsible left side panel)
where the NISPS ML engine's 20 outputs control curated C15 synthesizer
parameters (oscillator PM, shapers, filters, reverb, echo, flanger,
output mixer) through a WASM AudioWorklet bridge.
Includes a chord progression arpeggiator with controls for tempo (BPM),
octave range, octave offset, and 4 selectable progressions. The C15
engine runs in an AudioWorklet with lock-free SharedArrayBuffer ring
buffer communication.
New files: c15/ (WASM assets), js/synth/ (bridge, arpeggiator, param map),
serve-coop.py (COOP/COEP headers for SharedArrayBuffer support).
Faithful JS port of nisps-core MLP + IML engine with a touch-friendly
UI for exploring neural parameter mapping visually. Two learning modes:
example-based (set slider targets) and RL feedback (thumbs up/down with
exploration noise). Flow field particle system controlled by 8 MLP outputs.
