train_metadata

Output of function <a rd-options="" href="/link/spectro_calls?package=soundClass&version=0.0.9.2" data-mini-rdoc="soundClass::spectro_calls">spectro_calls</a>.

train_data

Obtain train metadata from
the output of function <a rd-options="" href="/link/spectro_calls?package=soundClass&version=0.0.9.2" data-mini-rdoc="soundClass::spectro_calls">spectro_calls</a>. Needed to run a fitted model

Provides an all-in-one solution for automatic classification of
sound events using convolutional neural networks (CNN). The main purpose
is to provide a sound classification workflow, from annotating sound events
in recordings to training and automating model usage in real-life
situations. Using the package requires a pre-compiled collection of
recordings with sound events of interest and it can be employed for:
1) Annotation: create a database of annotated recordings,
2) Training: prepare train data from annotated recordings and fit CNN models,
3) Classification: automate the use of the fitted model for classifying
new recordings. By using automatic feature selection and a user-friendly GUI
for managing data and training/deploying models, this package is intended
to be used by a broad audience as it does not require specific expertise in
statistics, programming or sound analysis. Please refer to the vignette for
further information.
Gibb, R., et al. (2019) <doi:10.1111/2041-210X.13101>
Mac Aodha, O., et al. (2018) <doi:10.1371/journal.pcbi.1005995>
Stowell, D., et al. (2019) <doi:10.1111/2041-210X.13103>
LeCun, Y., et al. (2012) <doi:10.1007/978-3-642-35289-8_3>.

Bruno Silva

soundClass

Sound Classification Using Convolutional Neural Networks

train_metadata function

Output of function <a rd-options='' href='spectro_calls'>spectro_calls</a>.

Obtain train metadata from
the output of function <a rd-options='' href='spectro_calls'>spectro_calls</a>. Needed to run a fitted model

train_metadata: Obtain train metadata to run a fitted model

Description

Usage

Arguments

Value