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warbleR (version 1.1.2)

warbleR: warbleR: A package to streamline bioacoustic analysis

Description

warbleR is a package designed to streamline analysis of (bio)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

Arguments

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 selections

Managing sound files

mp32wav: Convert several .mp3 files in working directory to .wav format checkwavs: Check whether .wav files can be read by subsequent functions and the minimum windows length ("wl" argument) that can be used wavdur: Determine the duration of sound files

Streamlining analysis of animal acoustic signal structure in R

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 lspec: Produce spectrograms of whole recordings split into multiple rows 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 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 as a time series ffts: Extract the fundamental frequency values as a time series dfDTW: Calculates acoustic dissimilarity using dynamic time warping on dominant frequency contours ffDTW: Calculates acoustic dissimilarity using dynamic time warping on fundamental frequency contours compare.methods: Produces graphs to visually assess performance of acoustic distance measurements coor.graph: Creat graphs of coordinated singing coor.test: Assess statistical significance of singing coordination seltailor: nteractive view of spectrograms to tailor start and end of selections

Details

License: GPL (>= 2)