Boosted Binary Audio Fingerprint Based on Spectral Subband Moments

An audio fingerprinting system identifies an audio based on a unique feature vector called the audio fingerprint. The performance of an audio fingerprinting system is directly related to the fingerprint that the system uses. To reduce both the DB size and the DB search time, binary fingerprints are often used. However converting a real-valued fingerprint into a binary fingerprint results in loss of information and leads to severe degradation in performance. In this paper, an algorithm known as boosting is used as a binary conversion method which minimizes the degradation. The experimental results showed that the proposed binary audio fingerprint obtained by boosting the spectral subband moments outperformed some of the state-of-the-art binary audio fingerprints in the context of both robustness and pair-wise independence (reliability).