title: Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations.
abstract: 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.
authors.affiliation: Instituto do Cérebro, Universidade Federal do Rio Grande do Norte, Natal, Brazil.
authors.forename: Hjalmar K
authors.identifier: http://orcid.org/0000-0002-8971-5349
authors.initials: HK
authors.lastname: Turesson
authors.affiliation: Instituto do Cérebro, Universidade Federal do Rio Grande do Norte, Natal, Brazil.
authors.forename: Sidarta
authors.initials: S
authors.lastname: Ribeiro
authors.affiliation: Departamento de Computação, Universidade Estadual Paulista "Júlio de Mesquita Filho", Bauru, São Paulo, Brazil.
authors.forename: Danillo R
authors.initials: DR
authors.lastname: Pereira
authors.affiliation: Departamento de Computação, Universidade Estadual Paulista "Júlio de Mesquita Filho", Bauru, São Paulo, Brazil.
authors.forename: João P
authors.initials: JP
authors.lastname: Papa
authors.affiliation: Programa de Pós-Graduação em Informática Aplicada, Laboratório de Bioinformática, Universidade de Fortaleza, Fortaleza, CE, Brazil.
authors.forename: Victor Hugo C
authors.initials: VH
authors.lastname: de Albuquerque