Detection and identification of manatee individual vocalizations in Panamanian wetlands using spectrogram clustering.
J Acoust Soc Am
; 146(3): 1745, 2019 09.
Article
en En
| MEDLINE
| ID: mdl-31590493
ABSTRACT
This work presents a methodology to automatically detect and identify manatee vocalizations in continuous passive acoustic underwater recordings. Given that vocalizations of each manatee present a slightly different frequency content, it is possible to identify individuals using a non-invasive acoustic approach. The recordings are processed in four stages, including detection, denoising, classification, and manatee counting and identification by vocalization clustering. The main contribution of this work is considering the vocalization spectrogram as an image (i.e., two-dimensional pattern) and representing it in terms of principal component analysis coefficients that feed a clustering approach. A performance study is carried out for each stage of the scheme. The methodology is tested to analyze three years of recordings from two wetlands in Panama to support ongoing efforts to estimate the manatee population.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Vocalización Animal
/
Trichechus manatus
Tipo de estudio:
Diagnostic_studies
Límite:
Animals
País/Región como asunto:
America central
/
Panama
Idioma:
En
Revista:
J Acoust Soc Am
Año:
2019
Tipo del documento:
Article
País de afiliación:
Panamá