Sound Classification Using Convolutional Neural Networks.

soundClass

Provides an all-in-one solution for automatic classification of sound events using convolutional neural networks (CNN). From annotating sound events in recordings to automating model usage in real-life situations. This package is aimed at (but not limited to) biologists and ecologists working with sound events that could benefit greatly from machine learning algorithms applied to their research. 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 and 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.

The package is now available on CRAN:

install.packages("soundClass")

Example files can be downloaded at:

https://doi.org/10.6084/m9.figshare.19550605.v1