Audio fingerprint retrieval algorithm using anti-fingerprint and frequency domain segmentation

In order to solve the problem of low audio fingerprint retrieval recognition rate under background sound and noise conditions,a novel algorithm based on mute masking and frequency segmentation is proposed.In the fingerprint extraction stage,voice activity detection technology is used to remove the non-valid speech frames,and then the valid speech frames are recombined and features are extracted according to the difference of the adjacent sub-band energy,which can effectively solve the problem that silence frame fingerprint characteristics are not robust.In the matching stage,according to the distribution characteristics of different audio signals in the frequency domain,the audio fingerprints are segmented and weighted in different frequencies to calculate the similarity between the template and the test audio more accurately.Experiments show that the proposed algorithm doubles the retrieval speed compared with the classic Philips algorithm.In the meantime,it yields a large definite improvement over Philips by 17.94％on mean average precision and 4.66％on recall respectively for the data set disturbed by background sounds.Compared with the latest Philips algorithm,the mean average precision and recall have been increased by 13.68％and 2.45％respectively.