article
Machine Learning Algorithmsfor Automatic Classification of Marmoset Vocalizations
Fecha
2016-09Registro en:
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
Autor
Turesson, Hjalmar K.
Ribeiro, Sidarta Tollendal Gomes
Pereira, Danillo R.
Papa, João P.
Albuquerque, Victor Hugo C. de
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.