Audio ML Noise Reduction
2026Real-time background noise suppression for Teams and Zoom. Custom U-Net trained on DNS Challenge 4. ONNX CPU inference. Built from scratch — dataset, model, training, live pipeline.
View repo →Audio ML Engineer, Senior AV/AI Engineer, and Recording artist in Chicago. I build stuff!
Real-time speech enhancement, edge ML, and production AI architecture and much more! Selected open source below — more on GitHub.
Real-time background noise suppression for Teams and Zoom. Custom U-Net trained on DNS Challenge 4. ONNX CPU inference. Built from scratch — dataset, model, training, live pipeline.
View repo →Production hybrid retrieval combining Qdrant (vector) and SQLite FTS5 (keyword), plus hierarchical conversation memory with LLM-powered fact extraction. Deployed on Raspberry Pi 5.
View repo →Real-time audio analysis as an MCP server — frequency reports, stereo imaging, mix analysis, key detection. Built to let AI assistants reason about what's playing during a production session.
View repo →See what audio processing actually does. Interactive STFT explorer across linear, mel and MFCC scales — plus an A/B difference view on a shared dB reference that shows exactly what a plugin, filter or bounce changed.
View repo →I write and produce as Stavion Colquitt. Singer, pianist, and engineer of my own records. New material in the pipeline; older work below.
Write-up in progress
Current project: an AI backing vocalist. Existing tools execute an arrangement decision you have already made — pick the harmony, set the interval, print it. This system makes the decision instead. Given a lead vocal, the instrumental and the lyrics, it predicts what belongs on each beat: a double, a harmony, a call and response, an ad‑lib, a sound effect, or nothing at all.
Trained on separated stems from my own catalogue, where I know what was sung and why it was sung there. Being written up with two research advisors. More here once it is further along.
Lewis University
Currently enrolledCisco
Audinate
University of St. Francis
Best for: research collaborations, audio ML conversations, music questions. Slow for cold outreach — I read carefully before I reply. For more on who I am, head to about me.
Socials
Where I show up online — music drops, work in progress, the occasional life moment.