Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Presence-absence estimation in audio recordings of tropical frog
  communities   One non-invasive way to study frog communities is by analyzing long-term
samples of acoustic material containing calls. This immense task has been
optimized by the development of Machine Learning tools to extract ecological
information. We explored a likelihood-ratio audio detector based on Gaussian
mixture model classification of 10 frog species, and applied it to estimate
presence-absence in audio recordings from an actual amphibian monitoring
performed at Yasun\'i National Park in the Ecuadorian Amazonia. A modified
filter-bank was used to extract 20 cepstral features that model the spectral
content of frog calls. Experiments were carried out to investigate the
hyperparameters and the minimum frog-call time needed to train an accurate GMM
classifier. With 64 Gaussians and 12 seconds of training time, the classifier
achieved an average weighted error rate of 0.9% on the 10-fold cross-validation
for nine species classification, as compared to 3% with MFCC and 1.8% with PLP
features. For testing, 10 GMMs were trained using all the available
training-validation dataset to study 23.5 hours in 141, 10-minute long samples
of unidentified real-world audio recorded at two frog communities in 2001 with
analog equipment. To evaluate automatic presence-absence estimation, we
characterized the audio samples with 10 binary variables each corresponding to
a frog species, and manually labeled a sub-set of 18 samples using headphones.
A recall of 87.5% and precision of 100% with average accuracy of 96.66%
suggests good generalization ability of the algorithm, and provides evidence of
the validity of this approach to study real-world audio recorded in a tropical
acoustic environment. Finally, we applied the algorithm to the available
corpus, and show its potentiality to gain insights into the temporal
reproductive behavior of frogs.

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The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
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The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph