Abstract: The recognition rate of the audio retrieval algorithm is often significantly reduced under unclean interference conditions such as background music and noise,an audio fingerprint retrieval algorithm based on the mute masking and frequency segmentation is proposed to mitigate this problem.Firstly,the voice activity detection technology is used to remove the non-valid speech frames,the valid speech frames are then recombined and extracted features according to the difference of the adjacent sub-band energy,which can effectively solve the problem that silence frame fingerprint characteristics are not robust.During the search matching stage,the non-uniform frequency segmentation and weighted method computed by the distribution characteristics of different audio signals is applied on the audio fingerprint features.These transformed features are more discriminative between the template audio and the test audio.Experiments show that compared with the classic Philips baseline algorithm,the proposed algorithm doubles the retrieval speed.At the meantime,it yields a large definite improvement over Philips by 17.94% on mean average precision and 4.66% on recall rate respectively for the data set disturbed by background sounds.Compared with the latest Philips algorithm,the average accuracy rate and recall rate are definitely increased by 13.68% and 2.45% respectively.