A method for filtering bioacoustic transients by spectrogram image convolution
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TL;DR
The method detects bowhead calls well, performing better than a matched filter and a hidden Markov model on the task, and weaknesses of the method are discussed.
Abstract
A method is presented for detecting bioacoustic transients. The desired transient-an animal call-is modeled as a sequence of frequency sweeps. Sweeps are detected by convolving a spectrogram of the signal with a kernel designed for the call of interest; convolution output is high when the call of interest is present and low other times. The method is tested on a set of bowhead whale (Balaena mysticetus) calls recorded in a noisy Arctic environment. The method detects bowhead calls well, performing better than a matched filter and a hidden Markov model on the task. Strengths and weaknesses of the method are discussed.>
