Species-specific audio detection: A comparison of three template-based classification algorithms using random forests
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Abstract
We developed a web-based cloud-hosted system that allow users to archive, listen, visualize, and annotate recordings. The system also provides tools to convert these annotations into datasets that can be used to train a computer to detect the presence or absence of a species. The algorithm used by the system was selected after comparing the accuracy and efficiency of three variants of a template-based classification. The algorithm computes a similarity vector by comparing a template of a species call with time increments across the spectrogram. Statistical features are extracted from this vector and used as input for a Random Forest classifier that predicts presence or absence of the species in the recording. The fastest algorithm variant had the highest average accuracy and specificity; therefore, it was implemented in the ARBIMON web-based system.
Cite this as
2017. Species-specific audio detection: A comparison of three template-based classification algorithms using random forests. PeerJ Preprints 5:e2713v1 https://doi.org/10.7287/peerj.preprints.2713v1note This preprint is not peer-reviewed. You may wish to reference the subsequent peer-reviewed version of this article.
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This is a submission to PeerJ Computer Science for review.
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Competing Interests
The authors declare there are no competing interests.
Author Contributions
Carlos J Corrada Bravo conceived and designed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Rafael Álvarez Berríos conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, performed the computation work.
T. Mitchell Aide conceived and designed the experiments, analyzed the data, wrote the paper, reviewed drafts of the paper.
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The following information was supplied regarding data availability:
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Funding
The authors received no funding for this work.
