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

Eldridge A, Casey M, Moscoso P, Peck M - PeerJ (2016)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Evolution, Behaviour and Environment, University of Sussex , Brighton , East Sussex , UK.

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.

No MeSH data available.


Related in: MedlinePlus

Over-complete Dictionaries (A), (C), (E) and sparse-approximations of original spectrogram (B), (D), (F) for Primary Forest site dawn chorus for Mini-batch gradient learning, Gabor Field Dictionary and SI- PLCA2D Component Dictionary.
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fig-3: Over-complete Dictionaries (A), (C), (E) and sparse-approximations of original spectrogram (B), (D), (F) for Primary Forest site dawn chorus for Mini-batch gradient learning, Gabor Field Dictionary and SI- PLCA2D Component Dictionary.

Mentions: Dictionaries and sparse-approximations for FP using mini-batch gradient descent, Gabor atoms and SI-PLCA2D are shown in Fig. 3. The input for each is a log-frequency spectrogram (constant-Q transform) of samples from the field recordings, as shown in Fig. 1. Example dictionaries (Figs. 3A, 3C, 3E) and sparse approximations of the input spectrogram (Figs. 3B, 3D, 3F) for site FP are shown for each method (component reconstructions not shown). Comparing the sparse-approximation of the original spectrogram for FP (see Fig. 1A), the superior performance of SI-PLCA2D over the other two methods is evident.


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

Eldridge A, Casey M, Moscoso P, Peck M - PeerJ (2016)

Over-complete Dictionaries (A), (C), (E) and sparse-approximations of original spectrogram (B), (D), (F) for Primary Forest site dawn chorus for Mini-batch gradient learning, Gabor Field Dictionary and SI- PLCA2D Component Dictionary.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4933085&req=5

fig-3: Over-complete Dictionaries (A), (C), (E) and sparse-approximations of original spectrogram (B), (D), (F) for Primary Forest site dawn chorus for Mini-batch gradient learning, Gabor Field Dictionary and SI- PLCA2D Component Dictionary.
Mentions: Dictionaries and sparse-approximations for FP using mini-batch gradient descent, Gabor atoms and SI-PLCA2D are shown in Fig. 3. The input for each is a log-frequency spectrogram (constant-Q transform) of samples from the field recordings, as shown in Fig. 1. Example dictionaries (Figs. 3A, 3C, 3E) and sparse approximations of the input spectrogram (Figs. 3B, 3D, 3F) for site FP are shown for each method (component reconstructions not shown). Comparing the sparse-approximation of the original spectrogram for FP (see Fig. 1A), the superior performance of SI-PLCA2D over the other two methods is evident.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Evolution, Behaviour and Environment, University of Sussex , Brighton , East Sussex , UK.

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.

No MeSH data available.


Related in: MedlinePlus