OpenKeyScan uses advanced AI to "see" your music, not just listen to it. The system converts audio into a visual spectrogram—like sheet music made of glowing bars—then uses a Convolutional Neural Network (CNN) to recognize harmonic patterns, chord progressions, and tonal textures.
By comparing your track against thousands of known key fingerprints, OpenKeyScan identifies the correct musical key and outputs it in Open Key notation, Alphanumeric, or traditional notation—all while running completely offline on your machine.
OpenKeyScan uses smart Artificial Intelligence to "listen" to your music and identify its musical key instantly. Think of it as a professional musician analyzing every track in your library in milliseconds, ensuring your DJ mixes are always perfectly in harmony using the Open Key notation system.
Your audio file enters the system—an MP3, WAV, FLAC, or any supported format.
The audio becomes a colorful heat map (spectrogram) analyzed by a neural network.
The system identifies the correct key and maps it to Open Key (2m) or traditional notation.
Most key finders listen to audio — but OpenKeyScan “sees” it.
Here's the step-by-step process in technical detail:
First, OpenKeyScan converts audio into a Constant-Q Transform (CQT) spectrogram. Think of it as sheet music made of glowing bars — bass notes at the bottom, highs at the top.
A Convolutional Neural Network (CNN) scans the spectrogram the same way self-driving cars identify road signs. It recognizes harmonic textures, chord progressions, and tonal patterns.
The system compares your track against thousands of known “key fingerprints,” ignoring noise, drums, and irrelevant elements.
The AI converts its findings into Open Key Notation (e.g., 2m) or traditional musical notation (E Minor). Adjacent values mix perfectly for flawless harmonic blending.
MP3, FLAC, WAV, M4A, AAC, OGG, AIFF.
Runs 100% offline. No uploads. Your music stays yours.
Analyzes tracks in under a second on modern hardware.
Open REST API available for developers.