This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Eldridge AC, Casey M, Moscoso P, Peck M. (2016) A New Method for Ecoacoustics? Toward the Extraction and Evaluation of Ecologically-Meaningful Sound Objects using Sparse Coding Methods. PeerJ Preprints4:e1407v3https://doi.org/10.7287/peerj.preprints.1407v3
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.
This is a revision version. This is a submission to PeerJ for review.
Audio example 1: Primary Forest at SLR
Audio excerpt as shown in Figure 1 (top spectrogram)
"Following" is like subscribing to any updates related to a preprint.
These updates will appear in your home dashboard each time you visit PeerJ.
You can also choose to receive updates via daily or weekly email digests.
If you are following multiple preprints then we will send you
no more than one email per day or week based on your preferences.
Note: You are now also subscribed to the subject areas of this preprint
and will receive updates in the daily or weekly email digests if turned on.
You can add specific subject areas through your profile settings.