Northwest Atlantic cod (Gadus morhua) have been heavily overfished in recent years and have not yet recovered. Passive acoustic technology offers a new approach to identify the spatial location of spawning fish, as well as their seasonal and long term persistence in an area. To date, the lack of a species-specific detector has made searching for Atlantic cod grunts in large amounts of passive acoustic data cumbersome. To address this problem, an automatic grunt detection and recognition algorithm that processes yearlong passive acoustic data recordings was designed. The proposed technique is a two-stage hypothesis testing algorithm that includes detecting and recognizing all grunt-like sounds. Test results demonstrated that the algorithm provided a detection probability of 0.93 for grunts with a signal-to-noise ratio (SNR) higher than 10 dB, and a detection probability of 0.8 for grunts with the SNR ranging from 3 to 10 dB. This detector is being used to identify cod in current and historical data from U.S. waters. Its use has significantly reduced the time required to find and validate the presence of cod grunts.
Skip Nav Destination
Article navigation
May 2016
May 09 2016
Automatic grunt detector and recognizer for Atlantic cod (Gadus morhua)
Ildar R. Urazghildiiev;
Ildar R. Urazghildiiev
a)
1
JASCO Applied Sciences
, Suite 200, 310 K Street, Anchorage, Alaska 99501, USA
Search for other works by this author on:
Sofie M. Van Parijs
Sofie M. Van Parijs
2
Northeast Fisheries Science Center
, Woods Hole, Massachusetts 02540, USA
Search for other works by this author on:
a)
Electronic mail: [email protected]
J. Acoust. Soc. Am. 139, 2532–2540 (2016)
Article history
Received:
June 22 2015
Accepted:
April 14 2016
Citation
Ildar R. Urazghildiiev, Sofie M. Van Parijs; Automatic grunt detector and recognizer for Atlantic cod (Gadus morhua). J. Acoust. Soc. Am. 1 May 2016; 139 (5): 2532–2540. https://doi.org/10.1121/1.4948569
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
A survey of sound source localization with deep learning methods
Pierre-Amaury Grumiaux, Srđan Kitić, et al.
Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural network
Seth McCammon, Nathan Formel, et al.
Related Content
Acoustic monitoring of artificial reefs reveals Atlantic cod and weakfish spawning and presence of individual bottlenose dolphins
J. Acoust. Soc. Am. (July 2024)
Click sounds produced by cod (Gadus morhua)
J Acoust Soc Am (January 2004)
Sound detection by Atlantic cod: An overview
J. Acoust. Soc. Am. (November 2020)
Sounds of Arctic cod (Boreogadus saida) in captivity: A preliminary description
J. Acoust. Soc. Am. (May 2018)
Acoustically induced streaming flows near a model cod otolith and their potential implications for fish hearing
J. Acoust. Soc. Am. (August 2011)