he automated real-time detection and classification of cetacean and anthropogenic sounds from deep-sea observatories can play a key role to study cetaceans in the field, to quantify the impact of anthropogenic sounds or to initiate mitigation measures during potentially harmful human activities. In the area of the NEMO-ONDE deep-sea observatory, sperm whales are often present together with heavy shipping. The spatial coincidence of both sound sources allows for the long term monitoring of their interaction. Some ships produce impulsive sounds and the automated separation of these impulses from sperm whale clicks is not a trivial task. As part of a detection, classification and localisation system for acoustic data from marine observatories, we present four modules performing the automated real-time classification of clicks from sperm whales and impulsive sounds produced by ships. First, two modules detect segments that contain impulsive sounds within a specifiable frequency band and return the impulses' positions. Then, two modules classify the detected impulses as sperm whale clicks or ship impulses. Finally, at the level of 22 s segments, the classification outputs from individual impulses are combined into a decision on the presence of sperm whale clicks or ship impulses. The modules' reliability was tested on data from the NEMO-ONDE observatory. Training and testing data were separated by more than 2 months, enabling to assess the consistency of the predictions over the long term. The automated separation between segments of the two classes was high with area under the ROC curve (AUC) values between 0.94 and 0.98.