1. An automated method for extracting an acoustic sub-fingerprint from an audio signal fragment, said method comprising: using at least one computer processor to perform the steps of: a: dividing an audio signal into a plurality of time-separated signal frames (frames) of equal time lengths of at least 0.5 seconds, wherein all frames overlap in time by at least 50% with at least one other frame, but wherein at least some frames are non-overlapping in time with other frames; b: selecting a plurality of non-overlapping frames to produce at least one cluster of frames, each selected frame in a given cluster of frames thus being a cluster frame; wherein the minimal distance between centers of said cluster frames is equal or greater than a time-length of one frame; c: decomposing each cluster frame into a plurality of substantially overlapping frequency bands to produce a corresponding plurality of frequency band signals, wherein said frequency bands overlap in frequency by at least 50% with at least one other frequency band, and wherein at least some frequency bands are non-adjacent frequency bands that do not overlap in frequency with other frequency bands; d: for each cluster frame, calculating a quantitative value of a selected signal property of frequency band signals of selected frequency bands of that cluster frame, thus producing a plurality of calculated signal property values, said selected signal property being any of: average energy, peak energy, energy valley, zero crossing, and normalized energy; e: using a feature vector algorithm and said calculated signal property values of said cluster frames to produce a feature-vector of said cluster; f: using a sub-fingerprint algorithm to digitize said feature-vector of said cluster and produce said acoustic sub-fingerprint.