warbleR: warbleR: A package to streamline bioacoustic analysis
Description
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
Obtaining avian vocalization data
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 selectionsManaging sound files
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 filesExploring/analyzing signal structure
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 coordinationDetails
License: GPL (>= 2)