spectro_analysis measures acoustic parameters on acoustic signals for which the start and end times
are provided.
spectro_analysis(X, bp = "frange", wl = 512, wl.freq = NULL, threshold = 15,
parallel = 1, fast = TRUE, path = NULL, pb = TRUE, ovlp = 50,
wn = "hanning", fsmooth = 0.1, harmonicity = FALSE, nharmonics = 3, ...)'selection_table', 'extended_selection_table' or data frame with the following columns: 1) "sound.files": name of the .wav
files, 2) "sel": number of the selections, 3) "start": start time of selections, 4) "end":
end time of selections. The output auto_detec can
be used as the input data frame.
A numeric vector of length 2 for the lower and upper limits of a frequency bandpass filter (in kHz) or "frange" (default) to indicate that values in bottom.freq and top.freq columns will be used as bandpass limits. Lower limit of bandpass filter is not applied to fundamental frequencies.
A numeric vector of length 1 specifying the spectrogram window length. Default is 512. See 'wl.freq' for setting windows length independently in the frequency domain.
A numeric vector of length 1 specifying the window length of the spectrogram
for measurements on the frequency spectrum. Default is 512. Higher values would provide
more accurate measurements. Note that this allows to increase measurement precision independently in the time and frequency domain. If NULL (default) then the 'wl' value is used.
amplitude threshold (%) for fundamental frequency and dominant frequency detection. Default is 15.
Numeric. Controls whether parallel computing is applied. It specifies the number of cores to be used. Default is 1 (i.e. no parallel computing).
Logical. If TRUE (default) then the peakf acoustic parameter (see below) is not computed, which
substantially increases performance (~9 times faster). This argument will be removed in future version.
Character string containing the directory path where the sound files are located.
If NULL (default) then the current working directory is used.
Logical argument to control progress bar and messages. Default is TRUE.
Character vector of length 1 specifying window name. Default is hanning'.
See function ftwindow for more options.
A numeric vector of length 1 to smooth the frequency spectrum with a mean sliding window (in kHz) used for mean peak frequency detection. This help to average amplitude "hills" to minimize the effect of amplitude modulation. Default is 0.1.
Logical. If TRUE harmonicity related parameters (fundamental frequency parameters [meanfun, minfun, maxfun], hn_freq,
hn_width, harmonics and HNR) are measured. Note that measuring these parameters
considerably increases computing time.
Numeric vector of length 1 setting the number of harmonics to analyze.
Additional parameters to be passed to analyze, which measures parameters related to harmonicity.
Data frame with 'sound.files' and 'selec' as in the input data frame, plus the following acoustic parameters:
duration: length of signal (in s)
meanfreq: mean frequency (in kHz). Mean of frequency spectrum (i.e. weighted average of frequency by amplitude within supplied band pass).
sd: standard deviation of frequency (in kHz).
freq.median: median frequency. The frequency at which the signal is divided in two frequency
intervals of equal energy (in kHz)
freq.Q25: first quartile frequency. The frequency at which the signal is divided in two
frequency intervals of 25% and 75% energy respectively (in kHz)
freq.Q75: third quartile frequency. The frequency at which the signal is divided in two
frequency intervals of 75% and 25% energy respectively (in kHz)
freq.IQR: interquartile frequency range. Frequency range between 'freq.Q25' and 'freq.Q75'
(in kHz)
time.median: median time. The time at which the signal is divided in two time
intervals of equal energy (in s)
time.Q25: first quartile time. The time at which the signal is divided in two
time intervals of 25% and 75% energy respectively (in s). See acoustat
time.Q75: third quartile time. The time at which the signal is divided in two
time intervals of 75% and 25% energy respectively (in s). See acoustat
time.IQR: interquartile time range. Time range between 'time.Q25' and 'time.Q75'
(in s). See acoustat
skew: skewness. Asymmetry of the spectrum (see note in specprop description)
kurt: kurtosis. Peakedness of the spectrum (see note in specprop description)
sp.ent: spectral entropy. Energy distribution of the frequency spectrum. Pure tone ~ 0;
noisy ~ 1. See sh
time.ent: time entropy. Energy distribution on the time envelope. Pure tone ~ 0;
noisy ~ 1. See th
entropy: spectrographic entropy. Product of time and spectral entropy sp.ent * time.ent.
See H
sfm: spectral flatness. Similar to sp.ent (Pure tone ~ 0;
noisy ~ 1). See sfm
meandom: average of dominant frequency measured across the acoustic signal
mindom: minimum of dominant frequency measured across the acoustic signal
maxdom: maximum of dominant frequency measured across the acoustic signal
dfrange: range of dominant frequency measured across the acoustic signal
modindx: modulation index. Calculated as the cumulative absolute
difference between adjacent measurements of dominant frequencies divided
by the dominant frequency range. 1 means the signal is not modulated.
startdom: dominant frequency measurement at the start of the signal
enddom: dominant frequency measurement at the end of the signal
dfslope: slope of the change in dominant frequency through time ((enddom-startdom)/duration). Units are kHz/s.
peakf: peak frequency. Frequency with the highest energy. This
parameter can take a considerable amount of time to measure. It's only
generated if fast = FALSE. It provides a more accurate measure of peak
frequency than 'meanpeakf' but can be more easily affected by background noise.
meanpeakf: mean peak frequency. Frequency with highest energy from the
mean frequency spectrum (see meanspec). Typically more consistent than peakf.
meanfun: average of fundamental frequency measured across the acoustic signal. Only measured if harmonicity = TRUE.
minfun: minimum fundamental frequency measured across the acoustic signal. Only measured if harmonicity = TRUE.
maxfun: maximum fundamental frequency measured across the acoustic signal. Only measured if harmonicity = TRUE.
hn_freq: mean frequency of the 'n' upper harmonics (kHz) (see analyze).
Number of harmonics is defined with the argument 'nharmonics'. Only measured if harmonicity = TRUE.
hn_width: mean bandwidth of the 'n' upper harmonics (kHz) (see analyze). Number of harmonics is defined with the argument 'nharmonics'. Only measured if harmonicity = TRUE.
harmonics: the amount of energy in upper harmonics, namely the
ratio of total spectral power above 1.25 x F0 to the total spectral power
below 1.25 x F0 (dB) (see analyze). Number of
harmonics is defined with the argument 'nharmonics'. Only measured if harmonicity = TRUE.
HNR: harmonics-to-noise ratio (dB). A measure of the harmonic content generated by getPitchAutocor. Only measured if harmonicity = TRUE.
The output of auto_detec can be used
directly without any additional modification. The function measures 29 acoustic parameters (if fast = TRUE) on
each selection in the data frame. Most parameters are produced internally by
specprop, fpeaks, fund,
and dfreq from the package seewave and analyze
from the package soundgen. NAs are produced for fundamental and dominant
frequency measures when there are no amplitude values above the threshold.
Additional parameters can be provided to the internal function analyze, which measures parameters related to harmonicity.
Araya-Salas, M., & Smith-Vidaurre, G. (2017). warbleR: An R package to streamline analysis of animal acoustic signals. Methods in Ecology and Evolution, 8(2), 184-191.
# NOT RUN {
{
data(list = c("Phae.long1", "Phae.long2", "Phae.long3", "lbh_selec_table"))
writeWave(Phae.long1, file.path(tempdir(), "Phae.long1.wav"))
writeWave(Phae.long2, file.path(tempdir(), "Phae.long2.wav"))
writeWave(Phae.long3, file.path(tempdir(), "Phae.long3.wav"))
# measure acoustic parameters
sp_param <- spectro_analysis(X = lbh_selec_table[1:8,], pb = FALSE, path = tempdir())
# measuring peakf
sp_param <- spectro_analysis(X = lbh_selec_table[1:8,], pb = FALSE, fast = FALSE, path = tempdir())
# measuring harmonic-related parameters using progress bar
sp_param <- spectro_analysis(X = lbh_selec_table[1:8,], harmonicity = TRUE, path = tempdir())
}
# }
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