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. However, this requires some proficiency in R coding that may dissuade beginners. Hopefully the codes I make available here will encourage bioacousticians to take advantage of this powerful tool.

Most of the tools I have developed for acoustic analysis are now available in the package warbleR. I will also post R scripts to detail the usage of new addtions to this package. Check out the article describing warbleR. Please cite this paper when using any of the package functions.

Sound analysis in R has been made possible owing to the awesome package seewave. I recommend taking a look at seewave’s website to learn more about its different tools. I will also post code containing functions from the packages monitoR and tuneR.


Signal detection with cross-correlation using monitoR

Here I show how to detect signals with cross-correlation using the very cool package monitoR. This package aims to facilitate acoustic template detection. The code here is similar but much less detailed than the quick start vignette of the monitoR package, so I encourage to look at the vignette if... [Read More]

Creating dynamic spectrograms (videos)

This code creates a video with a spectrogram scrolling from right to left. The spectrogram is synchronized with the audio. This is done by creating single image files for each of the movie frames and then putting them together in .mp4 video format. You will need the ffmpeg UNIX application... [Read More]