Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations

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Data

2016-09-21

Autores

Turesson, Hjalmar K.
Ribeiro, Sidarta
Pereira, Danillo R. [UNESP]
Papa, Joao P. [UNESP]
Albuquerque, Victor Hugo C. de

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Public Library Science

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

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Plos One. San Francisco: Public Library Science, v. 11, n. 9, 14 p., 2016.