Review of automatic detection and classification techniques for cetacean vocalization

dc.contributor.authorUsman, Ayinde M.en_ZA
dc.contributor.authorOgundile, Olayinka O.en_ZA
dc.contributor.authorVersfeld, Daniel J. J.en_ZA
dc.date.accessioned2020-09-08T13:28:19Z
dc.date.available2020-09-08T13:28:19Z
dc.date.issued2020-06-03
dc.descriptionCITATION: Usman, A. M., Ogundile, O. O. & Versfeld, D. J. J. 2020. Review of automatic detection and classification techniques for cetacean vocalization. IEEE Access, 8:105181-105206, doi:10.1109/ACCESS.2020.3000477.
dc.descriptionThe original publication is available at https://ieeexplore.ieee.org
dc.descriptionPublication of this article was funded by the Stellenbosch University Open Access Fund
dc.description.abstractENGLISH ABSTRACT: Cetaceans 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_ZA
dc.description.urihttps://ieeexplore.ieee.org/document/9110497/authors#authors
dc.description.versionPublisher's version
dc.format.extent26 pagesen_ZA
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, 8:105181-105206, doi:10.1109/ACCESS.2020.3000477
dc.identifier.issn2169-3536 (online)
dc.identifier.otherdoi:10.1109/ACCESS.2020.3000477en_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/108811en_ZA
dc.language.isoen_ZAen_ZA
dc.publisherInstitute of Electrical and Electronics Engineersen_ZA
dc.rights.holderAuthors retain copyrighten_ZA
dc.subjectCetacean -- Animal vocalizationen_ZA
dc.subjectAcoustic emission testingen_ZA
dc.subjectAnthropogenic effects on natureen_ZA
dc.subjectCetacean -- Detectionen_ZA
dc.subjectCetacean -- Classificationen_ZA
dc.titleReview of automatic detection and classification techniques for cetacean vocalizationen_ZA
dc.typeArticleen_ZA
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