Turesson HK, Ribeiro S, Pereira DR, Papa JP, de Albuquerque VHC. Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations.
PLoS One 2016;
11:e0163041. [PMID:
27654941 PMCID:
PMC5031457 DOI:
10.1371/journal.pone.0163041]
[Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Accepted: 09/01/2016] [Indexed: 01/15/2023] Open
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.
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