An audio fingerprint is a small digest of an audio file computed from its main perceptual properties. Like human fingerprints, audio fingerprints allow to identify an audio file among a set of candidates but does not allow to retrieve any other characteristics of the files. Applications of audio fingerprint include audio monitoring on broadcast chanels, filtering peer to peer networks, meta data restoration in large audio library and the protection of author's copyrights within a Digital Right Management(DRM) system. We propose in this paper a new fingerprint extraction algorithm based on a new audio segmentation method. A scoring function based on q-grams is used to determine if an input signal is a derivated version of a fingerprint stored in the database. A rule based on this scoring function allows to either recover the original input file or to decide that no fingerprint belonging to the database correspond to the signal. The proposed method is robust against compression and time shifting alterations of audio files.