Robust Landmark-Based Audio Fingerprinting
A landmark-based Shazam-like audio fingerprinting system.
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This landmark-based audio fingerprinting system is able to match short, noisy snippets to a reference database in near-constant time.
This is my implementation of the music audio matching algorithm developed by Avery Wang for the Shazam service. Shazam can identify apparently any commercial music track from a short snippet recorded via your cell phone in a noisy bar. I don't have the database to check if my version is quite that good, but it is able to rapidly match and locate a poor-quality excerpt from within a database of (at least) hundreds of tracks.
See http://labrosa.ee.columbia.edu/~dpwe/resources/matlab/fingerprint/ for the "published" output of the demo script.
Notes for running under Windows (from Rob Macrae) are at http://labrosa.ee.columbia.edu/matlab/fingerprint/windows-notes.txt .
Cite As
Dan Ellis (2026). Robust Landmark-Based Audio Fingerprinting (https://www.mathworks.com/matlabcentral/fileexchange/23332-robust-landmark-based-audio-fingerprinting), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.2.0.0 (154 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.2.0.0 | Fixed a problem where problems would occur if query contained audio before matching reference item (i.e. negative match time offset). Improved robustness (at cost of matching speed) by dithering time framing of query. |
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| 1.1.0.0 | No change to code, but added link to notes for running on Windows. |
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| 1.0.0.0 |
