Abstract

Audio fingerprint is also named audio hashing, which is a content-based identification technology that can be used to label an unknown audio recording. Here we introduce an audio fingerprinting algorithm based on harmonic enhancement and SSC (spectral subband centroid). First, the audio signal is processed by harmonic enhancement to extract predominant pitches that are most audible for human auditory system. Then SSC features of audio are computed and audio fingerprints are produced accordingly. Preliminary experimental results suggest that the proposed audio fingerprinting algorithm can achieve good recognition accuracy and is possible to be used in applications such as broadcast monitoring and audio excerpt identification by mobile devices.

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