The automated acoustic detection of cetaceans in real time is an important tool to study their behaviour and distribution and for activating mitigation measures in the context of harmful anthropogenic activities at sea. Acoustic data from the NEMO ONDE deep sea observatory (Sicily) indicated that sperm whale clicks were present in 15 % of the recordings and impulsive ship noise in 10 %. The ship noise poses a serious challenge to the detection of sperm whale clicks, since it is an important source of false positives. As part of an integrated classification system, we present a classification module aimed at the automated and real time classification of impulses from sperm whales and shipping. The achieved classification performance indicates that it reliably separates a large proportion of sperm whale clicks from shipping impulses.