Estimating the number of marine mammals using recordings of clicks from one microphone

An important but challenging task is to extract information on the location and/or number of marine mammals present given recordings from an array of hydrophones. Systems such as the Marine Mammal Monitoring on Navy Ranges (M3R) attempt to localize marine mammals as well as to get an estimate of the...

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Bibliographic Details
Main Authors: Xanadu C. Halkias, Daniel P. W. Ellis
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2006
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.3963
http://info.fuw.edu.pl/~dragan/Fizyka/Dragan2007.pdf
Description
Summary:An important but challenging task is to extract information on the location and/or number of marine mammals present given recordings from an array of hydrophones. Systems such as the Marine Mammal Monitoring on Navy Ranges (M3R) attempt to localize marine mammals as well as to get an estimate of their number using cross-correlation techniques on all available hydrophones. Our methodology offers the possibility to extract an estimate of the number of marine mammals given recordings from a single hydrophone, thus providing information to a researcher who does not have access to a larger array. The algorithm is based on three steps: detection of the clicks in the spectrogram using their energy, extraction of meaningful features, such as cepstral coefficients that are descriptive of the detected calls, and, lastly, choosing the appropriate number of clusters when using spectral clustering through the maximization of a given metric. The chosen number of clusters that best represents the data is an estimate of marine mammals present in the area. Informal analysis of the clustered clicks from example recordings shows that they are a good fit of the data, although a formal evaluation would require additional ground-truth. The algorithm was performed on several hydrophones in order to obtain some cross-validation of our results. Finally, the clusters were tracked in time using KL divergence. This algorithm could provide a first approximation on the number of vocalizing marine mammals using only one hydrophone. 1.