A New Method for Ecoacoustics? Toward the Extraction and Evaluation of Ecologically-Meaningful Sound Objects using Sparse Coding Methods
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Abstract
Efficient methods of biodiversity assessment and monitoring are central to ecological research and crucial in conservation management. Technological advances in remote acoustic sensing inspire new perspectives in ecology: environmental sound monitoring is emerging as a reliable non-invasive proxy for ecological complexity (Sueur and Farina, 2015). Rather than attempting to recognise species-specific calls, either manually or automatically, we are interested in monitoring the global acoustic environment, tackling the problem of diversity assessment at the community (rather than species) level. Preliminary work has attempted to make a case for community-level acoustic indices (e.g. Pieretti et al., 2011; Farina, 2014; Sueur et al., 2008b) which provide simple statistical summaries of the frequency or time domain signal. We suggest that under this approach, the opportunity to analyse spectro-temporal structural information is diminished, limiting their power both as monitoring and investigative tools. In this paper we consider sparse-coding and source separation algorithms (specifically, shift-invariant probabilistic latent component analysis in 2D) as a means to access and summarise ecologically-meaningful sound objects. In doing so we highlight a possible new approach for understanding and assessing ecologically relevant interactions within the conceptual framework of ecoacoustics.
Cite this as
2016. A New Method for Ecoacoustics? Toward the Extraction and Evaluation of Ecologically-Meaningful Sound Objects using Sparse Coding Methods. PeerJ Preprints 4:e1407v3 https://doi.org/10.7287/peerj.preprints.1407v3note This preprint is not peer-reviewed.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 revision version. This is a submission to PeerJ for review.
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Supplemental Information
Audio example 1: Primary Forest at SLR
Audio excerpt as shown in Figure 1 (top spectrogram)
Audio example 1: Secondary Forest at SLR
Audio excerpt as shown in Figure 1 (middle spectrogram)
Audio example 1: Silvopasture at SLR
Audio excerpt as shown in Figure 1 (bottom spectrogram)
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Alice C Eldridge conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper, field work (data collection).
Michael Casey conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.
Paola Moscoso conceived and designed the experiments, analyzed the data, reviewed drafts of the paper, field work (data collection).
Mika Peck conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper, field work (data collection).
Data Deposition
The following information was supplied regarding data availability:
Audio files attached
Funding
Data collection was funded by a University of Sussex Research Development Fund grant; Analysis was funded by a Leverhulme Trust Research Project Grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
