Architecture
Sonic Vector is a local-first audio mastering application. It bridges the gap between static equalization profiles and dynamic playback, using vector interpolation over preprocessed semantic audio centroids to generate optimal 5-band parametric filters in real time.
The system runs as a local Flask web dashboard and background service. It polls active Spotify playback to harvest metadata and writes synthesized parametric curves directly to the system-wide Equalizer APO configuration file, adjusting hardware output frequencies on song transitions.
Centroid Synthesis Engine
The core technical contribution is the real-time interpolation of crowdsourced semantic audio data:
- Semantic Centroids. The system parses crowdsourced parametric curves from the SAFE Equaliser Database. It mathematically filters out outlier entries using standard deviation thresholds and calculates average 5-band parametric “sonic centroids” for descriptors such as warm, bright, muddy, presence, airy, and punchy.
- Tag Matching. On song changes, the background service collects Last.fm crowdsourced acoustic tags and Spotify genres. It computes overlap scores against the semantic vocabularies, generating normalized interpolation weights.
- Curve Interpolation. The engine executes a weighted average of active centroids, dynamically synthesizing a custom 5-band parametric curve tailored to the active song’s acoustic profile.
Key Features
- Hardware Control. Compiles and writes synthesized parametric curves straight to the Equalizer APO
config.txtpath, enabling system-wide audio modification. - Mastering Overlays. Provides advanced processing overlays (such as Preamp, intensity Strength, Bass Boost, Vocal Clarity, and Airiness) that adjust the output curve.
- State Caching. Automatically saves manual user adjustments or AI-guided tuning to a local SQLite database, recalling the custom profile instantly whenever that track plays again.
- Fail-Safe Router. Includes a dynamic context router that can query local or remote language models for expert EQ profiles, fallback-routing to vector similarity centroids if the AI is offline.