warbleR is a package designed to streamline analysis of animal acoustic signals in R. This package allows users to collect open-access avian vocalizations data or input their own data into a workflow that facilitates spectrographic visualization and measurement of acoustic parameters. warbleR makes fundamental sound analysis tools from the R package seewave, as well as new tools not yet offered in the R environment, readily available for batch process analysis. The functions facilitate searching and downloading avian vocalizations from Xeno-Canto http://www.xeno-canto.org/, creating maps of Xeno-Canto recordings, converting .mp3 files to .wav files, checking .wav files, automatically detecting acoustic signals, selecting them manually, printing spectrograms of whole recordings or individual signals, measuring signal to noise ratio, cross-correlation and performing acoustic measurements.
The warbleR package offers three overarching categories of functions:
Obtaining avian vocalization data
Sound file management
Streamlined (bio)acoustic analysis in R
querxc: Download recordings and metadata from Xeno-Canto
xcmaps: Create maps to visualize the geographic spread of Xeno-Canto recordings
imp.syrinx: Importing Syrinx selections
imp.raven: Importing Raven selections
mp32wav: Convert several .mp3 files in working directory to .wav
format
checksels: Check whether selections can be read by subsequent functions
checkwavs: Check whether .wav files can be read by subsequent
functions and the minimum windows length ("wl" argument) that can be used
fixwavs: Fix .wav files to allow importing them into R
wavdur: Determine the duration of sound files
autodetec: Automatically detect start and
end of acoustic signals
manualoc: Interactive spectrographic view to measure start and
end of acoustic signals
autodetec: Automatic detection of acoustic signals based on ampltiude
seltailor: Interactive view of spectrograms to tailor start and end of selections
lspec: Produce spectrograms of whole recordings split into
multiple rows
lspec2pdf: Combine lspec images to single pdf files
specreator: Create spectrograms of manualoc selections
snrspecs: Create spectrograms to visualize margins over which
noise will be measured by sig2noise
sig2noise: Measure signal-to-noise ratio across multiple files
trackfreqs: Create spectrograms to visualize frequency
measurements
filtersels: Filter selection data frames based on filtered image files
specan: Measure acoustic parameters on selected acoustic
signals
xcorr: Pairwise cross-correlation of multiple signals
xcorr.graph: Pairwise cross-correlation of multiple signals
dfts: Extract the dominant frequency values across the signal as a time series
ffts: Extract the fundamental frequency values across the signal as a time series
sp.en.ts: Extract the spectral entropy values across the signal as a time series
dfDTW: Calculate acoustic dissimilarity using dynamic time warping
on dominant frequency contours
ffDTW: Calculate acoustic dissimilarity using dynamic time warping
on fundamental frequency contours
compare.methods: Produce graphs to visually assess performance of acoustic
distance measurements
catalog: Produce a vocalization catalog with spectrograms in and array with
several rows and columns
catalog2pdf: Combine catalog images to single pdf files
coor.graph: Creat graphs of coordinated singing
coor.test: Assess statistical significance of singing coordination
License: GPL (>= 2)