Abstract
We seek to improve the signal-to-noise (SNR) ratio of clicks recorded from Blainville's beaked whales (Mesoplodon densirostris). The proposed filter is based on subspace principles and projects the noisy speech vector onto signal and noise subspaces. An estimate of the clean signal is made by retaining only the components in the signal subspace. To test the filter, a detector using the filter output has been designed for the detection of beaked whale calls. Through simulations, the proposed detector is shown to be capable of detecting most of the desired clicks but is not able to differentiate other co-existing species such as Risso's dolphins and pilot whales' that is, it efficiently detects all clicks. By combining the proposed detector with the energy ratio mapping algorithm (ERMA; Klinck and Mellinger (in press), which measures energy differences between different species, higher detection accuracy for beaked whale clicks can be achieved. The filter can also be used to improve the SNR of other marine mammal acoustic signals.
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