Acoustic analysis of one or more sounds: pitch tracking, basic spectral
characteristics, formants, estimated loudness (see
getLoudness), roughness (see modulationSpectrum),
novelty (see ssm), etc. The default values of arguments are
optimized for human non-linguistic vocalizations. See
vignette('acoustic_analysis', package = 'soundgen') for details. The defaults
and reasonable ranges of all arguments can be found in
defaults_analyze. For high-precision work, first extract and
manually correct pitch contours with pitch_app, PRAAT, or
whatever, and then run analyze(pitchManual = ...) with these manual
contours.
analyze(
x,
samplingRate = NULL,
scale = NULL,
from = NULL,
to = NULL,
dynamicRange = 80,
silence = 0.04,
windowLength = 50,
step = windowLength/2,
overlap = 50,
specType = c("spectrum", "reassign", "spectralDerivative")[1],
wn = "gaussian",
zp = 0,
cutFreq = NULL,
nFormants = 3,
formants = list(),
loudness = list(SPL_measured = 70),
roughness = list(msType = "1D", windowLength = 25, step = 2, amRes = 5),
novelty = list(input = "melspec", kernelLen = 100),
pitchMethods = c("dom", "autocor"),
pitchManual = NULL,
entropyThres = 0.6,
pitchFloor = 75,
pitchCeiling = 3500,
priorMean = 300,
priorSD = 6,
priorAdapt = TRUE,
nCands = 1,
minVoicedCands = NULL,
pitchDom = list(domThres = 0.1, domSmooth = 220),
pitchAutocor = list(autocorThres = 0.7, autocorSmooth = 7, autocorUpsample = 25,
autocorBestPeak = 0.975, interpol = "sinc"),
pitchCep = list(cepThres = 0.75, cepZp = 0),
pitchSpec = list(specThres = 0.05, specPeak = 0.25, specHNRslope = 0.8, specSmooth =
150, specMerge = 0.1, specSinglePeakCert = 0.4, specRatios = 3),
pitchHps = list(hpsNum = 5, hpsThres = 0.1, hpsNorm = 2, hpsPenalty = 2),
pitchZc = list(zcThres = 0.1, zcWin = 5),
harmHeight = list(harmThres = 3, harmTol = 0.25, harmPerSel = 5),
subh = list(method = c("cep", "pitchCands", "harm")[1], nSubh = 5, tol = 0.05, nHarm =
5, harmThres = 12, harmTol = 0.25, amRange = c(10, 200)),
flux = list(thres = 0.15, smoothWin = 100),
amRange = c(10, 200),
fmRange = c(5, 1000/step/2),
shortestSyl = 20,
shortestPause = 60,
interpol = list(win = 75, tol = 0.3, cert = 0.3),
pathfinding = c("none", "fast", "slow")[2],
annealPars = list(maxit = 5000, temp = 1000),
certWeight = 0.5,
snakeStep = 0,
snakePlot = FALSE,
smooth = 1,
smoothVars = c("pitch", "dom"),
summaryFun = c("mean", "median", "sd"),
invalidArgAction = c("adjust", "abort", "ignore")[1],
reportEvery = NULL,
cores = 1,
plot = FALSE,
osc = "linear",
showLegend = TRUE,
savePlots = NULL,
pitchPlot = list(col = rgb(0, 0, 1, 0.75), lwd = 3, showPrior = TRUE),
extraContour = NULL,
ylim = NULL,
xlab = "Time",
ylab = NULL,
main = NULL,
width = 900,
height = 500,
units = "px",
res = NA,
...
)Returns a list with $detailed frame-by-frame descriptives and
a $summary with one row per file, as determined by summaryFun
(e.g., mean / median / SD of each acoustic variable across all STFT frames). Output measures include:
duration from the beginning of the first
non-silent STFT frame to the end of the last non-silent STFT frame, s (NB:
depends strongly on windowLength and silence settings)
time of the middle of each frame (ms)
frequency (Hz) and depth (0 to 1) of amplitude modulation estimated from a smoothed amplitude envelope
frequency and purity of amplitude
modulation estimated via modulationSpectrum
root mean square of amplitude per frame, calculated as sqrt(mean(frame ^ 2))
same as ampl, but
ignoring silent frames
Cepstral Peak Prominence, dB (a measure of pitch quality, the ratio of the highest peak in the cepstrum to the regression line drawn through it)
lowest dominant frequency band (Hz) (see "Pitch tracking methods / Dominant frequency" in the vignette)
Weiner entropy of the spectrum of the current frame. Close to 0: pure tone or tonal sound with nearly all energy in harmonics; close to 1: white noise
Normalized Shannon entropy of the spectrum of the current frame: 0 = pure tone, 1 = white noise
the frequency and bandwidth of the first nFormants formants per STFT frame, as calculated by phonTools::findformants
feature-based flux, the rate of change
in acoustic features such as pitch, HNR, etc. (0 = none, 1 = max); "epoch"
is an audio segment between two peaks of flux that exceed a threshold of
flux = list(thres = ...) (listed in output$detailed only)
frequency of frequency modulation (FM) such as vibrato or jitter, Hz
depth of FM, semitones
purity or dominance of the main FM frequency (fmFreq), 0 to 1
the amount of energy in upper harmonics, namely the ratio of total spectral mass above 1.25 x F0 to the total spectral mass below 1.25 x F0 (dB)
how high harmonics reach in the spectrum, based on the best guess at pitch (or the manually provided pitch values)
harmonics-to-noise ratio (dB), a measure of harmonicity returned by soundgen:::getPitchAutocor (see "Pitch tracking methods / Autocorrelation"). If HNR = 0 dB, there is as much energy in harmonics as in noise
subjective loudness, in sone, corresponding to
the chosen SPL_measured - see getLoudness
spectral novelty - a measure of how variable the spectrum is
on a particular time scale, as estimated by ssm
the frequency with maximum spectral power (Hz)
post-processed pitch contour based on all F0 estimates
the 25th, 50th, and 75th quantiles of the spectrum of voiced frames (Hz)
the amount of amplitude modulation, see modulationSpectrum
the center of gravity of the frame’s spectrum, first spectral moment (Hz)
the slope of linear regression fit to the spectrum below cutFreq (dB/kHz)
estimated depth of subharmonics per frame: 0 = none, 1 = as strong as f0. NB: this depends critically on accurate pitch tracking
the ratio of f0 to subharmonics frequency with strength subDep: 2 = period doubling, 3 = f0 / 3, etc.
is the current STFT frame voiced? TRUE / FALSE
path to a folder, one or more wav or mp3 files c('file1.wav', 'file2.mp3'), Wave object, numeric vector, or a list of Wave objects or numeric vectors
sampling rate of x (only needed if x is a
numeric vector)
maximum possible amplitude of input used for normalization of
input vector (only needed if x is a numeric vector)
if NULL (default), analyzes the whole sound, otherwise from...to (s)
dynamic range, dB. All values more than one dynamicRange under maximum are treated as zero
(0 to 1 as proportion of max amplitude) frames with RMS
amplitude below silence * max_ampl adjusted by scale are not
analyzed at all.
length of FFT window, ms
you can override overlap by specifying FFT step, ms (NB:
because digital audio is sampled at discrete time intervals of
1/samplingRate, the actual step and thus the time stamps of STFT frames
may be slightly different, eg 24.98866 instead of 25.0 ms)
overlap between successive FFT frames, %
plot the original FFT ('spectrum'), reassigned spectrogram ('reassigned'), or spectral derivative ('spectralDerivative')
window type accepted by ftwindow, currently
gaussian, hanning, hamming, bartlett, blackman, flattop, rectangle
window length after zero padding, points
if specified, spectral descriptives (peakFreq, specCentroid,
specSlope, and quartiles) are calculated only between cutFreq[1] and
cutFreq[2], Hz. If a single number is given, analyzes frequencies
from 0 to cutFreq. For ex., when analyzing recordings with varying
sampling rates, set to half the lowest sampling rate to make the spectra
more comparable. Note that "entropyThres" applies only to this frequency
range, which also affects which frames will not be analyzed with
pitchAutocor.
the number of formants to extract per STFT frame (0 = no formant analysis, NULL = as many as possible)
a list of arguments passed to
findformants - an external function called to
perform LPC analysis
a list of parameters passed to getLoudness for
measuring subjective loudness, namely SPL_measured, Pref,
spreadSpectrum. NULL = skip loudness analysis
a list of parameters passed to
modulationSpectrum for measuring roughness. NULL = skip
roughness analysis
a list of parameters passed to ssm for measuring
spectral novelty. NULL = skip novelty analysis
methods of pitch estimation to consider for determining pitch contour: 'autocor' = autocorrelation (~PRAAT), 'cep' = cepstral, 'spec' = spectral (~BaNa), 'dom' = lowest dominant frequency band, 'hps' = harmonic product spectrum, NULL = no pitch analysis
manually corrected pitch contour. For a single sound,
provide a numeric vector of any length. For multiple sounds, provide a
dataframe with columns "file" and "pitch" (or path to a csv file) as
returned by pitch_app, ideally with the same windowLength and
step as in current call to analyze. A named list with pitch vectors per
file is also OK (eg as returned by pitch_app)
pitch tracking is only performed for frames with Weiner
entropy below entropyThres, but other spectral descriptives are
still calculated (NULL = analyze everything)
absolute bounds for pitch candidates (Hz)
specifies the mean (Hz) and standard deviation
(semitones) of gamma distribution describing our prior knowledge about the
most likely pitch values for this file. For ex., priorMean = 300,
priorSD = 6 gives a prior with mean = 300 Hz and SD = 6 semitones (half
an octave). To avoid using any priors, set priorMean = NA, priorAdapt
= FALSE
adaptive second-pass prior: if TRUE, optimal pitch contours
are estimated first with a prior determined by priorMean,priorSD, and
then with a new prior adjusted according to this first-pass pitch contour
maximum number of pitch candidates per method, normally 1...4
(except for dom, which returns at most one candidate per frame)
minimum number of pitch candidates that have to be
defined to consider a frame voiced (if NULL, defaults to 2 if dom is
among other candidates and 1 otherwise)
a list of control parameters for pitch tracking using the
lowest dominant frequency band or "dom" method; see details and
?soundgen:::getDom
a list of control parameters for pitch tracking using the
autocorrelation or "autocor" method; see details and
?soundgen:::getPitchAutocor
a list of control parameters for pitch tracking using the
cepstrum or "cep" method; see details and ?soundgen:::getPitchCep
a list of control parameters for pitch tracking using the
BaNa or "spec" method; see details and ?soundgen:::getPitchSpec
a list of control parameters for pitch tracking using the
harmonic product spectrum or "hps" method; see details and
?soundgen:::getPitchHps
a list of control parameters for pitch tracking based on zero
crossings in bandpass-filtered audio or "zc" method; see
getPitchZc
a list of control parameters for estimating how high
harmonics reach in the spectrum; see details and ?soundgen:::harmHeight
a list of control parameters for estimating the strength of
subharmonics per frame - that is, spectral energy at integer ratios of f0:
see ?soundgen:::getSHR
a list of control parameters for calculating feature-based flux
(not spectral flux) passed to getFeatureFlux
target range of frequencies for amplitude modulation, Hz: a
vector of length 2 (affects both amMsFreq and amEnvFreq)
target range of frequencies for analyzing frequency
modulation, Hz (fmFreq): a vector of length 2
the smallest length of a voiced segment (ms) that constitutes a voiced syllable (shorter segments will be replaced by NA, as if unvoiced)
the smallest gap between voiced syllables (ms): large value = interpolate and merge, small value = treat as separate syllables separated by an unvoiced gap
a list of parameters (currently win, tol, cert) passed
to soundgen:::pathfinder for interpolating missing pitch candidates
(NULL = no interpolation)
method of finding the optimal path through pitch
candidates: 'none' = best candidate per frame, 'fast' = simple heuristic,
'slow' = annealing. See soundgen:::pathfinder
a list of control parameters for postprocessing of
pitch contour with SANN algorithm of optim. This is
only relevant if pathfinding = 'slow'
(0 to 1) in pitch postprocessing, specifies how much we prioritize the certainty of pitch candidates vs. pitch jumps / the internal tension of the resulting pitch curve
optimized path through pitch candidates is further
processed to minimize the elastic force acting on pitch contour. To
disable, set snakeStep = 0
if TRUE, plots the snake
if smooth is a positive number, outliers of
the variables in smoothVars are adjusted with median smoothing.
smooth of 1 corresponds to a window of ~100 ms and tolerated
deviation of ~4 semitones. To disable, set smooth = 0
functions used to summarize each acoustic characteristic, eg "c('mean', 'sd')"; user-defined functions are fine (see examples); NAs are omitted automatically for mean/median/sd/min/max/range/sum, otherwise take care of NAs yourself
what to do if an argument is invalid or outside the
range in defaults_analyze: 'adjust' = reset to default value,
'abort' = stop execution, 'ignore' = throw a warning and continue (may
crash)
when processing multiple inputs, report estimated time left every ... iterations (NULL = default, NA = don't report)
number of cores for parallel processing
if TRUE, produces a spectrogram with pitch contour overlaid
"none" = no oscillogram; "linear" = on the original scale; "dB" = in decibels
if TRUE, adds a legend with pitch tracking methods
full path to the folder in which to save the plots (NULL = don't save, '' = same folder as audio)
a list of graphical parameters for displaying the final
pitch contour. Set to list(type = 'n') to suppress
name of an output variable to overlap on the pitch
contour plot, eg 'peakFreq' or 'loudness'; can also be a list with extra
graphical parameters, eg extraContour = list(x = 'harmHeight', col =
'red')
frequency range to plot, kHz (defaults to 0 to Nyquist frequency). NB: still in kHz, even if yScale = bark, mel, or ERB
plotting parameters
parameters passed to
png if the plot is saved
other graphical parameters passed to spectrogram
Each pitch tracker is controlled by its own list of settings, as follows:
pitchAutocor (autocorrelation)autocorThres voicing threshold (unitless, ~0 to 1)
autocorSmooth the width of smoothing interval (in bins) for
finding peaks in the autocorrelation function. Defaults to 7 for sampling
rate 44100 and smaller odd numbers for lower values of sampling rate
autocorUpsample upsamples acf to this resolution (Hz) to improve
accuracy in high frequencies
autocorBestPeak amplitude of the
lowest best candidate relative to the absolute max of the acf
pitchCep (cepstrum)cepZp zero-padding of the spectrum
used for cepstral pitch detection (final length of spectrum after
zero-padding in points, e.g. 2 ^ 13)
pitchSpec (ratio of
harmonics - BaNa algorithm)specThres voicing
threshold (unitless, ~0 to 1)
specPeak,specHNRslope when looking
for putative harmonics in the spectrum, the threshold for peak detection is
calculated as specPeak * (1 - HNR * specHNRslope)
specSmooth the width of window for detecting peaks in the spectrum, Hz
specMerge pitch candidates within specMerge semitones are
merged with boosted certainty
specSinglePeakCert (0 to 1) if F0
is calculated based on a single harmonic ratio (as opposed to several ratios
converging on the same candidate), its certainty is taken to be
specSinglePeakCert
hpsThres voicing threshold (unitless, ~0 to 1)
hpsNorm the amount of inflation of hps pitch certainty (0 = none)
hpsPenalty the amount of penalizing hps candidates in low
frequencies (0 = none)
Each of these lists also accepts graphical
parameters that affect how pitch candidates are plotted, eg pitchDom =
list(domThres = .5, col = 'yellow'). Other arguments that are lists of
subroutine-specific settings include:
harmonicHeight
(finding how high harmonics reach in the spectrum)harmPerSel
the number of harmonics per sliding selection
harmTol maximum
tolerated deviation of peak frequency from multiples of f0, proportion of f0
pitch_app getLoudness
segment getRMS