Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations

• Autor(a) principal: Turesson, Hjalmar K.
• Data de Publicação: 2016
• Outros Autores: Ribeiro, Sidarta, Pereira, Danillo R. [UNESP], Papa, Joao P. [UNESP], Albuquerque, Victor Hugo C. de
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1371/journal.pone.0163041; http://hdl.handle.net/11449/161955

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 F-1-score > 0.84) using the Optimum Path Forest classifier. Dataset and algorithms are made publicly available.