Package: soundClass
Title: Sound Classification Using Convolutional Neural Networks
Version: 0.0.9.2
Author: Bruno Silva [aut, cre]
Maintainer: Bruno Silva <bmsasilva@gmail.com>
Description: 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>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.2
BugReports: https://github.com/bmsasilva/soundClass/issues
Imports: seewave, DBI, dplyr, dbplyr, RSQLite, signal, tuneR, zoo,
        magrittr, shinyFiles, shiny, utils, graphics, generics, keras,
        shinyjs
Depends: shinyBS, htmltools
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-29 13:38:00 UTC; bruno
Repository: CRAN
Date/Publication: 2022-05-29 22:40:02 UTC
Built: R 4.6.0; ; 2026-04-30 03:54:54 UTC; unix
