Soundscape Characterization Using Autoencoders and Unsupervised Learning
Daniel Alexis Nieto-Mora,
Maria Cristina Ferreira de Oliveira,
Camilo Sanchez-Giraldo
et al.
Abstract:Passive acoustic monitoring (PAM) through acoustic recorder units (ARUs) shows promise in detecting early landscape changes linked to functional and structural patterns, including species richness, acoustic diversity, community interactions, and human-induced threats. However, current approaches primarily rely on supervised methods, which require prior knowledge of collected datasets. This reliance poses challenges due to the large volumes of ARU data. In this work, we propose a non-supervised framework using … Show more
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