Bioacoustics in R
I have developed several (bio)acoustic analysis tools in the R programming environment. The advantage of R over most common sound analysis software (e.g. Raven, SAP, Avisoft) is its higher flexibility, which allows the implementation of custom made analyses that better fit the research questions and the characteristics of the vocalizations. Most of the tools are now available in the R packages warbleR and Rraven. I also share R code for bioacoustic analysis on the Bioacoustic in R blog.
An R package to streamline the analysis of animal acoustic signal structure. The package offers functions for downloading avian vocalizations from the open-access online repository [Xeno-Canto](http://xeno-canto.org/), displaying the geographic extent of the recordings, manipulating sound files, detecting acoustic signals, assessing performance of methods that measure acoustic similarity, conducting cross-correlations, dynamic time warping, measuring acoustic parameters and analyzing interactive vocal signals, among others. Functions working iteratively allow parallelization to improve computational efficiency.The code in warbleR can be executed by less experienced R users, but has also been thoroughly commented, which will facilitate further customization by advanced users.
Install/load the package from CRAN as follows:
The package vignettes provide detailed examples for most warbleR functions. You can pull up the vignettes as follows:
A full description of the package can be founf in this journal article.
Please cite warbleR as follows:
Araya-Salas, M. and Smith-Vidaurre, G. (2017), *warbleR: an r package to streamline analysis of animal acoustic signals*. Methods Ecol Evol. 8, 184-191. PDF
NOTE: please also cite the tuneR and seewave packages if you use any spectrogram-creating or acoustic-measuring function
The Rraven package is designed to facilitate the exchange of data between R and Raven sound analysis software (Cornell Lab of Ornithology). Raven provides very powerful tools for the analysis of (animal) sounds. R can simplify the automatization of complex routines of analyses. Furthermore, R packages as warbleR, seewave and monitoR (among others) provide additional methods of analysis, working as a perfect complement for those found in Raven. Hence, bridging these applications can largely expand the bioacoustician’s toolkit. Currently, most analyses in Raven cannot be run in the background from a command terminal. Thus, most Rraven functions are design to simplify the exchange of data between the two programs, and in some cases, export files to Raven for further analysis.
I recommend using the latest developmental version, which is found in github. To do so, you need the R package devtools (which of course should be installed!). Some warbleR functions and example data sets will be used, so warbleR should be installed as well: