A new method for ecoacoustics? Toward the extraction and evaluation of ecologically-meaningful soundscape components using sparse coding methods

Abstract

Passive acoustic monitoring is emerging as a promising non-invasive proxy for ecological complexity with potential as a tool for remote assessment and monitoring (Sueur & Farina, 2015). Rather than attempting to recognise species-specific calls, either manually or automatically, there is a growing interest in evaluating the global acoustic environment. Positioned within the conceptual framework of ecoacoustics, a growing number of indices have been proposed which aim to capture community-level dynamics by (e.g., Pieretti, Farina & Morri, 2011; Farina, 2014; Sueur et al., 2008b) by providing statistical summaries of the frequency or time domain signal. Although promising, the ecological relevance and efficacy as a monitoring tool of these indices is still unclear. In this paper we suggest that by virtue of operating in the time or frequency domain, existing indices are limited in their ability to access key structural information in the spectro-temporal domain. Alternative methods in which time-frequency dynamics are preserved are considered. Sparse-coding and source separation algorithms (specifically, shift-invariant probabilistic latent component analysis in 2D) are proposed as a means to access and summarise time-frequency dynamics which may be more ecologically-meaningful.

Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring

“…Another promising avenue involves unsupervised learning of acoustic patterns directly from survey data. For example, Eldridge, Casey, Moscoso, and Peck () used sparse coding to isolate periodic sound components within bird chorus recordings, which they suggest may correlate with particular sound types or species calls. Although embryonic, such approaches might eventually facilitate estimation of vocalising species diversity without requiring comprehensive auto‐ID tools (although reference material would be required to link unsupervised classifications to species).…”

Passive acoustic monitoring as a potential tool to survey animal and ecosystem processes in freshwater environments

“…Yet another option suggests bringing together automatic detection of single sound events and classification of basic elements of the soundscape or sound types to identify acoustic diversity in soundscape recordings. These new methods, currently emerging, might be less sensitive to environmental noise (Eldridge, Casey, Moscoso, & Peck, ; Phillips, Towsey, & Roe, ; Ulloa et al., ) and would be interesting to apply in freshwater environments.…”

Spatial Variation in Sound Frequency Components Across an Urban Area Derived from Mobile Surveys

“…Many ecoacoustic indices have been proposed (Joo et al 2011, Sueur et al 2014, Eldridge et al 2016, Villanueva-Rivera and Pijanowski 2016) based on weighted combinations of SPL in frequency bands. However, most use narrow bands of 1 kHz in contrast to the octaves used here.…”

“…Methods to characterize naturalness in the acoustic environment have come from soundscape ecology (Pijanowski et al 2011, Sueur et al 2014 although they have been developed mainly for natural areas (Fairbrass et al 2017). Frequency bands have been divided into the characteristic sounds of the biotic world, human sources and the physical environment, known as biophony, anthropophony and geophony respectively (Joo et al 2011, Sueur et al 2014, Eldridge et al 2016, Hong and Jeon 2017. There remains doubt, however, whether this classification is fully applicable to urban areas because of the potentially different spectral composition present (Devos 2016, Fairbrass et al 2017.…”