Robust Landmark-Based Audio Fingerprinting

Version 1.2.0.0 (154 KB) von Dan Ellis
A landmark-based Shazam-like audio fingerprinting system.
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Aktualisiert 5. Nov 2009

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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 .

Zitieren als

Dan Ellis (2024). Robust Landmark-Based Audio Fingerprinting (https://www.mathworks.com/matlabcentral/fileexchange/23332-robust-landmark-based-audio-fingerprinting), MATLAB Central File Exchange. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2009a
Kompatibel mit allen Versionen
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fingerprint/

Version Veröffentlicht Versionshinweise
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.
1.1.0.0

No change to code, but added link to notes for running on Windows.
1.0.0.0