Audio fingerprint based on Spectral Flux for audio retrieval

In audio fingerprinting, an audio clip must be recognized by matching an extracted fingerprint to a database of previously computed fingerprints. The fingerprints should reduce the dimensionality of the input significantly, provide discrimination among different audio clips, and, at the same time, be invariant to distorted versions of the same audio clip. In this paper, we design fingerprints addressing the above issues by extracting the audio fingerprints from the Spectral Flux of the clipped signal. Spectral Flux (SF) is a measure of how quickly the power spectrum of a signal is changing, calculated by comparing the power spectrum for one frame against the power spectrum from the previous frame. More precisely, it is usually calculated as the 2-norm (also known as the Euclidean distance) between the two normalised spectra. By using the AF as the feature of our algorithm we retrieval the audio clips from the database which has store some fingerprints computed previously. We test the robustness of the fingerprints under a large number of distortions. And the experimental results show that the proposed algorithm performance well in audio retrieval.