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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

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A non-spectrogram-correlation method of automatically detecting minke whale boings.

Hui Ou¹, Whitlow W L Au, Julie N Oswald

¹Marine Mammal Research Program, Hawaii Institute of Marine Biology, University of Hawaii, P.O. Box 1106, Kaneohe, Hawaii 96734, USA. ou@hawaii.edu

The Journal of the Acoustical Society of America

|October 9, 2012

Summary

A new algorithm efficiently detects minke whale boing sounds by analyzing frequency features, reducing computational time. This method offers improved accuracy, detecting faint calls and minimizing false alarms compared to existing tools.

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Area of Science:

Marine bioacoustics
Signal processing

Background:

Minke whale boing sounds are important bioacoustic signals.
Previous detection methods, like XBAT, can be computationally intensive and may miss low-signal calls.

Purpose of the Study:

To introduce a novel algorithm for automatic detection of minke whale boing sounds.
To improve efficiency and accuracy in identifying these vocalizations.

Main Methods:

The algorithm identifies frequency features of boing sounds directly.
It avoids calculating continuous spectrograms, reducing computational load.
Tested on 8 hours of acoustic data from Station ALOHA Cabled Observatory.

Main Results:

The new detector demonstrates fewer false alarms than the XBAT cross-correlation detector.
It successfully identifies low-signal-to-noise ratio (SNR) minke whale calls missed by XBAT.
Reduced computational time is a key advantage.

Conclusions:

The proposed algorithm offers a more efficient and accurate method for minke whale sound detection.
This advancement aids in marine mammal acoustic monitoring and research.