Identifying acoustic features to distinguish between highly and moderately altered soundscapes in Colombia

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      <subfield code="a">Identifying acoustic features to distinguish between highly and moderately altered soundscapes in Colombia</subfield>
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      <subfield code="a"> 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</subfield>
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      <subfield code="g">13/03/2023 Volumen 26 Número 71 - marzo 2023 , pp. 34-45</subfield>
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      <subfield code="t">Revista Iberoamericana de Inteligencia Artificial</subfield>
      <subfield code="d"> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</subfield>
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