The development of an algorithm for automatic detection of sperm whale clicks in large recordings is described. It is based on the Teager–Kaiser (TK) energy operator and it is able to detect efficiently creaks as well as regular clicks. A matching filter is first used as a pre-processor in order to overcome the difficulties caused by the multi-pulse structure of regular clicks. Next, the TK energy operator is applied to the output of the matching filter. A first selection of clicks is performed based on statistical measurements on the TK output, while the final selection is carried out by a forward–backward search algorithm. The proposed system has been tested on a total duration of 25 min of data containing regular clicks as well as creak clicks, where the location of clicks has been marked by hand. An average rate of 94.05% of correct detections was achieved by comparison with the hand-labeled data created from the tested files. Comparing to a standard method used for the same task, the proposed algorithm is more effective in detection rate by 30% and much more accurate and robust.