Review of Automatic Detection and Classification Techniques for Cetacean Vocalization

Simple item page
dc.contributor.authorUsman, A. M
dc.contributor.authorOgundile, O. O
dc.contributor.authorVersfeld, D. J. J
dc.date.accessioned2021-03-31T14:14:28Z
dc.date.available2021-03-31T14:14:28Z
dc.date.issued2020-06-08
dc.description.abstractCetaceans have elicited the attention of researchers in recent decades due to their importance to the ecosystem and their economic values. They use sound for communication, echolocation and other social activities. Their sounds are highly non-stationary, transitory and range from short to long sounds. Passive acoustic monitoring (PAM) is a popular method used for monitoring cetaceans in their ecosystems. The volumes of data accumulated using PAM are usually big, so they are difficult to analyze using manual inspection. Therefore different techniques with mixed outcomes have been developed for the automatic detection and classification of signals of different cetacean species. So far, no single technique developed is perfect to detect and classify the vocalizations of over 82 known species due to variability in time-frequency, difference in the amplitude among species and within species' vocal repertoire, physical environment, among others. The accuracy of any detector or classifier depends on the technique adopted as well as the nature of the signal to be analyzed. In this article, we review the existing techniques for the automatic detection and classification of cetacean vocalizations. We categorize the surveyed techniques, while emphasizing the advantages and disadvantages of these techniques. The article suggests possible research directions that can improve existing detection and classification techniques. In addition, the article recommends other suitable techniques that can be used to analyze non-linear and non-stationary signals such as the cetaceans' signals. Several research have been dedicated to this topic, however, there is no review of these past results that gives a quick overview in the area of cetacean detection and classification. This review will help researchers and practitioners in the field to make insightful decisions based on their requirements.en_US
dc.description.sponsorshipNational Research Foundation (NRF) South Africaen_US
dc.identifier.citationUsman, A. M., Ogundile, O. O., & Versfeld, D. J. J. (2020): Review of Automatic Detection and Classification Techniques for Cetacean Vocalization. IEEE Access, Vol 8; pp 105181-105206, Published by the Institute of Electrical and Electronics Engineers (IEEE). Available online at 10.1109/ACCESS.2020.3000477en_US
dc.identifier.uri10.1109/ACCESS.2020.3000477
dc.identifier.urihttp://hdl.handle.net/123456789/4638
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE).en_US
dc.relation.ispartofseries8;2020
dc.subjectCetaceanen_US
dc.subjectClassificationen_US
dc.subjectDetectionen_US
dc.subjectFeature Extractionen_US
dc.subjectPassive Acoustic Monitoring (PAM)en_US
dc.titleReview of Automatic Detection and Classification Techniques for Cetacean Vocalizationen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
IEEE Access_Review of Cetacean techniques.pdf
Size:
4.61 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.69 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections