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Título : Machine Learning Algorithmsfor Automatic Classification of Marmoset Vocalizations
Otros títulos : Machine Learning Algorithmsfor Automatic Classification of Marmoset Vocalizations
Autor : Turesson, Hjalmar K.
Ribeiro, Sidarta
Pereira, Danillo R.
Papa, João P.
Albuquerque, Victor Hugo C. de
Palabras clave : Machine Learning Algorithms;Marmoset Vocalizations
Fecha de publicación : sep-2016
Citación : TURESSON, H.K.; RIBEIRO, S.; PEREIRA, D.R.; PAPA, J.P.; DE ALBUQUERQUE, V.H.C. Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations. PLoS ONE. v.11, n.9, p.e0163041, 2016. doi:10.1371/journal.pone.0163041
Resumen : Automatic classification of vocalization type could potentially become a useful tool for acoustic the monitoring of captive colonies of highly vocal primates. However, for classification to be useful in practice, a reliable algorithm that can be successfully trained on small datasets is necessary. In this work, we consider seven different classification algorithms with the goal of finding a robust classifier that can be successfully trained on small datasets. We found good classification performance (accuracy > 0.83 and F1-score > 0.84) using the Optimum Path Forest classifier. Dataset and algorithms are made publicly available.
Resumo: Automatic classification of vocalization type could potentially become a useful tool for acoustic the monitoring of captive colonies of highly vocal primates. However, for classification to be useful in practice, a reliable algorithm that can be successfully trained on small datasets is necessary. In this work, we consider seven different classification algorithms with the goal of finding a robust classifier that can be successfully trained on small datasets. We found good classification performance (accuracy > 0.83 and F1-score > 0.84) using the Optimum Path Forest classifier. Dataset and algorithms are made publicly available.
URI : http://hdl.handle.net/123456789/21398
Aparece en las colecciones: ICe - Artigos publicados em periódicos

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