Shazam identifies songs by converting audio into a spectrogram using the Fast Fourier Transform, then creating a sparse "constellation map" of the loudest frequency peaks that serves as a noise-resistant fingerprint. The algorithm matches this fingerprint against a database of millions of songs in seconds, making it robust to background noise and volume variations.
Otto Beta
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Shazam identifies songs by converting audio into a spectrogram using the Fast Fourier Transform, then creating a sparse "constellation map" of the loudest frequency peaks that serves as a noise-resistant fingerprint. The algorithm matches this fingerprint against a database of millions of songs in seconds, making it robust to background noise and volume variations.