Identifying Acoustic Features to Distinguish Highly and Moderately Altered Soundscapes in Colombia

Authors

  • Fernando Martínez-Tabares Universidad Nacional de Colombia - Sede Manizales, Colombia
  • Mauricio Orozco-Alzate Universidad Nacional de Colombia - Sede Manizales, Colombia

DOI:

https://doi.org/10.4114/intartif.vol26iss71pp34-45

Keywords:

Acoustic features, Classification, Feature selection methods, Soundscapes

Abstract

Numerous acoustic features have been proposed as useful measures to characterize natural soundscapes, which can be employed to examine the impact of land transformation on the audible properties of a location. The extensive collection of available features demands an examination to identify the most informative and discriminative ones for a given problem. In this study, we conduct an empirical investigation into the selection of acoustic features for discriminating between highly and moderately transformed versions of four Colombian soundscapes: Moorlands, coffee plantations, dry tropical forests, and pastures. We employ classical supervised feature selection techniques along with exploratory tools such as correlation matrices and scatter plots. Our results indicate that a few acoustic features are sufficient to differentiate between the classes. Specifically, those features that estimate acoustic complexity via intrinsic variability of sound intensities or biodiversity through species richness or abundance in specific frequency bands are the most discriminative ones. These findings suggest that the selection of acoustic features can assist in analyzing and distinguishing between different soundscapes.

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Published

2023-03-24

How to Cite

Martínez-Tabares, F., & Orozco-Alzate, M. (2023). Identifying Acoustic Features to Distinguish Highly and Moderately Altered Soundscapes in Colombia. Inteligencia Artificial, 26(71), 34–45. https://doi.org/10.4114/intartif.vol26iss71pp34-45