  The North Atlantic right whale (Eubalaena glacialis) is an endangered
species. These whales continuously suffer from deadly vessel impacts alongside
the eastern coast of North America. There have been countless efforts to save
the remaining 350 - 400 of them. One of the most prominent works is done by
Marinexplore and Cornell University. A system of hydrophones linked to
satellite connected-buoys has been deployed in the whales habitat. These
hydrophones record and transmit live sounds to a base station. These recording
might contain the right whale contact call as well as many other noises. The
noise rate increases rapidly in vessel-busy areas such as by the Boston harbor.
This paper presents and studies the problem of detecting the North Atlantic
right whale contact call with the presence of noise and other marine life
sounds. A novel algorithm was developed to preprocess the sound waves before a
tree based hierarchical classifier is used to classify the data and provide a
score. The developed model was trained with 30,000 data points made available
through the Cornell University Whale Detection Challenge program. Results
showed that the developed algorithm had close to 85% success rate in detecting
the presence of the North Atlantic right whale.
