An improved audio fingerprinting algorithm with robust and efficient

An audio fingerprint is a content-based compact feature that summarizes an audio clip. As same as we using human fingerprint to recognize people, audio fingerprint can be used to retrieval unknown audio clips. In this paper, we propose an algorithm which extracts audio fingerprint based on spectral bark-band energy and PCA (Principle Components Analysis). By using this algorithm, search a huge audio database efficient and highly robust in the presence of noise be possible. Especially, the algorithm enhances the efficiency to a higher level. The preliminary result of our experiments shows prominent performance.