Robust Landmark-Based Audio Fingerprinting

Versión 1.2.0.0 (154 KB) por Dan Ellis
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 .

Citar como

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

Compatibilidad con la versión de MATLAB
Se creó con R2009a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Categorías
Más información sobre Audio Processing Algorithm Design en Help Center y MATLAB Answers.

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fingerprint/

Versión Publicado Notas de la versión
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