audio-fingerprint-kit

01 // The Challenge

Matching audio in the wild is not “hash the file”. Codecs, loudness and cropping change the bytes while the recording stays the same. The pipeline has to survive those transforms and still collide on the same track.

02 // Architecture

The kit splits the problem:

• Decode to PCM and window the signal.
• Build a time-frequency representation.
• Peak-pick a constellation and hash local pairs.
• Compare against a store of previously ingested prints.

Notes and talks in this site are field reports from that stack, not a product landing page.

03 // Runtime

Use it as a library from Rust tools, or as a CLI to ingest a folder of WAVs and dump a search index. The article series walks the first hash that actually stayed stable.