SemantiFX

SemantiFX explores a musician-centered way to control familiar audio effects with natural language. A musician captures a representative excerpt, describes the change they want, previews the resulting effect settings, and remains free to edit, compare, refine, or reject them.

This repository is at the prototype stage. The current question is:

Does an asynchronous capture → describe → analyze → compare workflow feel compatible with music-making, and which interface makes the musician feel most in control?

Current scope

• Parametric EQ only
• Local inference
• macOS Standalone, Audio Unit, and VST3 targets
• Text input before integrated speech input
• Visible, editable parameters with compare and undo

The system is intentionally split at a narrow seam: JUCE owns deterministic real-time audio processing; the inference worker accepts an audio excerpt and a prompt, then returns a versioned set of named parameters. ML work never runs on the audio thread.

See Architecture and Initial research plan.

Try it

Explore three interaction directions in a browser:

Then open http://localhost:4173/?variant=A. The bottom switcher moves among the guided studio, conversation, and workbench variants without losing the simulated session state.

Run a real Text2FX analysis using the sibling checkout's existing environment:

Build and open the JUCE standalone app:

Use Import Analysis… in the app to load /tmp/semantifx-analysis.json. The same build also produces AU and VST3 artifacts. Run all automated checks with scripts/check.

Current integration edge

The real inference worker and real-time plugin now share a strict, versioned 18-parameter contract. Importing a result is intentionally manual in this slice. Audio capture, automatic worker process management, cancellation, and progress transport are the next vertical integration step.